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Review

Technical Losses in Power Networks: Mechanisms, Mitigation Strategies, and Future Directions

by
Pooya Parvizi
1,
Milad Jalilian
2,3,
Alireza Mohammadi Amidi
3,4,
Mohammad Reza Zangeneh
3 and
Jordi-Roger Riba
5,*
1
Department of Mechanical Engineering, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
2
Department of Physics, Faculty of Science, Lorestan University, Khorramabad 4431668151, Iran
3
Pooya Power Knowledge Enterprise, Tehran 1466993771, Iran
4
Department of Electrical Engineering, Razi University, Kermanshah 6714414971, Iran
5
Department of Electrical Engineering, Universitat Politècnica de Catalunya, 08222 Terrassa, Spain
*
Author to whom correspondence should be addressed.
Electronics 2025, 14(17), 3442; https://doi.org/10.3390/electronics14173442
Submission received: 11 July 2025 / Revised: 22 August 2025 / Accepted: 26 August 2025 / Published: 28 August 2025
(This article belongs to the Section Power Electronics)

Abstract

Technical losses (TLs) in power systems are an inevitable outcome of energy dissipation in components such as conductors, transformers, and transmission lines. These losses arise from the combined effects of material properties, operational conditions, and environmental factors, creating ongoing challenges for energy efficiency and grid sustainability. Their reduction requires a coordinated approach that integrates material improvements, smart grid technologies, and optimized operational practices. Reducing TLs not only improves economic efficiency but also contributes significantly to global sustainability efforts by enabling more efficient energy use and reducing carbon emissions associated with power generation. A review of recent publications shows that the literature on network losses is heavily skewed toward non-technical losses (NTLs), with TL-focused studies being fewer, often dated, and lacking comprehensive scope. This paper addresses the existing research gap by presenting a comprehensive, section-oriented taxonomy of TL mechanisms in power systems, accompanied by precise definitions for each category and a direct linkage between these categories and applicable loss mitigation measures. In addition, selected real-world projects and global initiatives aimed at reducing TLs, together with current regulatory approaches, emerging trends in this domain, and an assessment of the maturity level of technologies employed for TL reduction, are analyzed. This study aims to serve as a scientific reference to support future research and to guide policymakers, regulators, and utilities in developing more effective strategies for minimizing TLs.

1. Introduction

Electricity is a cornerstone of global economic growth, with demand increasing due to industrialization, urbanization, and digitalization [1,2]. Power systems are complex networks designed to generate, transmit, and distribute electrical energy to end-users, yet a substantial portion of this energy is dissipated as TLs [3,4]. These losses arise from inherent physical phenomena such as resistive heating, electromagnetic radiation, and dielectric dissipation, and represent a significant portion of the energy generated worldwide [5]. TLs not only reduce operational efficiency but also contribute to higher greenhouse gas emissions, underscoring the urgency of their mitigation in achieving sustainable energy systems [6,7]. The IEA estimates that reducing global TLs by just 1% could save over 200 TWh annually, highlighting their economic and environmental significance [8]. Also, as the IEA projects electricity’s share in final energy consumption to double by 2050 [9], mitigating TLs has become imperative for sustainable energy systems.
Power losses in electrical grids are typically categorized into technical and non-technical components. NTLs stem from unmetered or unbilled energy consumption, often influenced by socio-economic factors such as theft, metering inaccuracies, or administrative inefficiencies. These losses can be further subdivided, though their classification varies across countries due to inconsistent regulatory definitions. Numerous studies have extensively examined NTLs in T&D networks, providing a wide range of research for interested readers seeking further information on this subject [10,11]. In contrast, TLs arise from inherent physical principles, such as resistive heating in conductors and transformer inefficiencies. While advancements in equipment efficiency can mitigate these losses, TLs are broadly categorized into fixed (no-load) and variable (load-dependent) losses [12,13,14]. Fixed losses persist irrespective of load conditions and stem from core magnetization in transformers, dielectric absorption in insulators, and corona discharge in HV lines [15,16].
Transformer core losses, primarily due to hysteresis and eddy currents in laminated steel cores, account for a significant portion (25–30%) of total distribution losses. Mitigating these losses requires a comprehensive strategy, as the interplay between material properties, operating conditions, and environmental factors significantly impacts their magnitude. The physical characteristics of grid components are crucial in determining TLs. Conductor resistance, for example, varies with material choice—aluminum conductors exhibit 60% higher resistance than copper, exacerbating Joule losses [17]. Similarly, transformer efficiency hinges on core material quality; amorphous metal cores can reduce no-load losses by 70% compared to conventional silicon steel [18]. Insulation degradation, exacerbated by ultraviolet exposure and thermal cycling, further elevates dielectric losses, particularly in aging infrastructure [19]. Operational factors such as load fluctuations, voltage levels, and temperature also modulate TLs. Elevated temperatures increase conductor resistance by 0.4% per °C, amplifying Joule losses during heatwaves, while under-voltage conditions raise current demand, compounding resistive dissipation. These dynamics highlight how both environmental conditions and technological constraints can adversely impact energy transmission efficiency [20]. The gains achieved by reducing losses can be categorized into economic and financial gains, as well as institutional advantages [21]. For instance, minimizing TLs leads to tangible energy savings and reduces the need for large-scale capital investments in infrastructure. The existing literature demonstrates a growing interest in mitigating TLs within power transmission networks [22,23,24]. The primary operational concern regarding network systems is not the mere existence of TLs, which are unavoidable, but rather how to effectively evaluate and minimize them. Any improvement in TL management directly lowers the amount of energy needed to be bought or produced for the system. TL reduction employs measures like network upgrades, equipment replacement, and operational optimization to minimize energy losses. Research has advanced loss quantification and mitigation strategies. Grid digitization further enables data-driven solutions, supporting loss reduction platforms for improved efficiency [24]. Also, contemporary research employs diverse analytical frameworks, from time-series load coefficient models to spectral methods in frequency-domain analyses [22,25]. Research has also addressed the estimation of losses arising from control and conversion processes, focusing on Joule, corona, and insulation losses [26], reduced equivalent network models with simulation in OpenDSS [27], intelligent modeling and simulation [23], and specialized methods for single-phase systems [28], highlighting the importance of combining accurate calculation methods, monitoring tools, and economic analysis to reduce costs and enhance grid sustainability. However, these studies often exhibit notable limitations, such as restricted applicability to specific system configurations, reliance on simplified or idealized models, insufficient validation with real-world measurements, and omission of integrated cost–benefit assessments. Gu et al. [24] present a provincial-level design scheme for an interactive control platform aimed at TL reduction. The proposed approach leverages reactive power compensation potential on both the supply and demand side, with the goal of enhancing operational efficiency, reducing losses, and improving the monitoring and control capabilities of power distribution companies.
A comprehensive review of data from Scopus and Google Scholar, particularly from reputable publishers such as MDPI, IEEE, Elsevier, and Springer, reveals a significant gap between the number of publications addressing TLs and NTLs (see Table 1). In the field of NTLs, there is an abundance of research (including review papers, research articles, books, and conference proceedings) covering various aspects of the topic. However, in the area of TLs, most of the available papers are conference proceedings, and these are predominantly dated rather than recent. Moreover, the majority of these papers do not focus exclusively on TLs; instead, they typically consider both technical and non-technical losses together and rarely address all technical aspects comprehensively [29,30,31]. Most existing studies tend to focus on only one or two specific aspects of TLs. Additionally, there is a noticeable scarcity of research that provides a thorough and practical investigation of TLs in real-world contexts. Therefore, this work addresses a critical gap in the literature, as to date no comprehensive classification or review has been conducted encompassing all TL mechanisms in electrical power systems. While numerous classifications exist for NTLs [11], the integrated taxonomy presented here establishes a fundamental framework for future specialized research and provides electrical engineers with a structured classification for system development. By consolidating previously fragmented concepts and establishing unified terminology, this work serves as an essential foundational step preceding more advanced, domain-specific investigations. The proposed classification system makes three key contributions to the field: First, it synthesizes current knowledge on TLs, identifies key mitigation strategies, and outlines future research directions to enhance power system efficiency. Second, the causes of TLs are examined separately in each sector, which resolves existing ambiguities in loss characterization. Third, it also examines the role of TLs in environmental damage and the global efforts of various countries to reduce losses. The international case studies presented provide not only benchmarking data for utilities and policymakers, but also reveal important patterns in technology adoption across different regulatory and infrastructural contexts. This review approach enables researchers to (1) identify knowledge gaps more effectively, (2) enables utilities to prioritize strategies in modern grids, and (3) allows us to develop targeted solutions with a clearer understanding of system-wide impacts.
For power system operators, this framework offers practical benefits in loss assessment and reduction strategies. The classification enables more accurate benchmarking of TLs across different network configurations and operating conditions. Furthermore, by distinguishing between fundamental physical phenomena and implementation-dependent factors, it provides clearer guidance for prioritizing loss reduction investments. In summary, this review distinguishes itself by presenting an integrated analytical structure that unifies all major categories of TLs across transmission and distribution, including subcategories rarely assessed together in earlier works. The identified research gaps primarily stem from original research papers rather than review articles, as comprehensive reviews remain scarce in the field of TL analysis. These gaps present valuable opportunities for future researchers to advance the understanding and mitigation of power losses in electrical systems: (1) Incomplete loss assessment: Most works focus solely on line losses, neglecting transformer losses [85,86,87]. (2) Methodological inconsistencies: Variability in load flow techniques and omission of high-frequency loss contributions limit accuracy [22,86]. (3) Lack of comparative analysis: The efficacy of different mitigation strategies (e.g., compensation devices, smart grids) remains unquantified [88,89].
The significance of addressing TLs cannot be overstated, as they have far-reaching implications for the economic viability, operational efficiency, and environmental sustainability of power networks [13]. Although we can continuously work to minimize these losses, achieving zero loss is not realistic [22]. Mitigating TLs requires a multifaceted approach, leveraging advanced materials, smart grid technologies, and optimized operational practices [90]. Emerging challenges such as the integration of renewable energy sources and cyber–physical vulnerabilities further complicate the landscape, necessitating ongoing research and innovation [91,92]. Mitigation techniques for TLs encompass a combination of technological, operational, and planning interventions. Advanced solutions include the deployment of high-efficiency transformers, conductor uprating, reactive power compensation, and the integration of smart grid technologies such as real-time monitoring and demand-side management. Furthermore, DERs and microgrids can reduce line losses by localizing generation and minimizing long-distance power flows. Each approach must be evaluated based on cost-effectiveness, scalability, and compatibility with existing infrastructure to ensure sustainable implementation. Reducing these losses and enhancing reliability within the power sector can significantly boost the competitive edge of the industrial field, leading to increased profits for electricity providers. The insights provided herein are intended to inform utility operators, policymakers, and researchers in their efforts to enhance the efficiency and sustainability of power networks. This paper is structured as follows: Section 2 classifies TLs and elucidates their mechanisms, including fixed losses (core, dielectric, corona) and variable losses (Joule, impedance, contact resistance). Section 3 reviews mitigation strategies, emphasizing material advancements such as amorphous metal cores, grid modernization such as (DLR systems), and reactive power management. Section 4 provides an overview of the current global status of power system losses, detailing recent trends, regional variations, and the underlying factors across different countries. Section 5 discusses environmental impacts, linking TLs to SDGs. Section 6 identifies future research directions, such as AI-driven predictive maintenance and hybrid AC/DC grids. Finally, Section 7 concludes the study by synthesizing key findings and proposing actionable recommendations for utilities and policymakers.

2. Classification and Mechanisms of TLs

TLs in power systems are an inherent consequence of the physical and electromagnetic phenomena occurring in electrical components during energy generation, transmission, and distribution. These losses are broadly classified into fixed losses—those that occur regardless of the load—and variable losses, which scale with the load current [13]. A comprehensive understanding of these mechanisms is critical for designing strategies to enhance grid efficiency, reduce operational costs, and meet sustainability objectives. Table 2 summarizes the categories of TLs in T&D networks. It details the nature of these losses, provides examples, and outlines their key characteristics.
The commonly cited generalized split of TLs of approximately 25–33% fixed and 67–75% variable applies broadly to mixed transmission and distribution networks but remains highly sensitive to the underlying asset composition. Transformer-intensive systems exhibit elevated fixed losses, driven primarily by core hysteresis and eddy current phenomena, both governed by magnetic material properties and operational flux density. Under normal excitation, these core losses depend predominantly on applied voltage; however, once the core approaches magnetic saturation, the non-linear B–H relationship alters the flux–current interaction, introducing a non-negligible current component to otherwise voltage-dependent losses. In such regimes, the magnetizing branch draws a disproportionately higher current, increasing the hysteresis loop area and eddy current magnitudes. In transmission line-dominated networks, variable losses—principally I2R dissipation—are the primary concern. Voltage harmonics and current distortions exacerbate both categories of losses:—dielectric heating and incremental core losses on the fixed side, and increased conductor and stray losses on the variable side—through elevated RMS values and intensified skin/proximity effects. Additionally, at lower operating voltages, variable losses grow quadratically with current in accordance with Joule’s law, as higher currents are required to maintain constant power transfer. Conductor type further shapes the profile: aluminum conductor steel-reinforced (ACSR) designs contribute negligibly to fixed losses yet dominate the variable component in line-heavy systems. These interactions highlight the necessity for context-specific loss modeling and targeted mitigation strategies rooted in network topology, equipment characteristics, and operating regimes.

2.1. Fixed Losses

Fixed losses, also referred to as constant or no-load losses, are inherent energy dissipation mechanisms that persist in power networks irrespective of load level, arising from steady-state physical phenomena intrinsic to electrical components. These include magnetization-related losses in magnetic materials (hysteresis and eddy currents), dielectric dissipation due to polarization lag in insulating media, leakage currents through deteriorated or contaminated insulation, and, in high-voltage systems, corona discharge. The latter occurs when the local electric field at a conductor surface exceeds the air ionization threshold, producing a partial discharge region that converts electrical energy into light, heat, sound, and chemical by-products. Dielectric losses reflect the periodic alignment and relaxation of dipoles within the insulation under alternating fields, with magnitude determined by material permittivity and loss tangent, while leakage currents are governed by surface conductivity and contamination level [12,93]. Effective mitigation of fixed losses requires multi-domain optimization, selecting low-loss dielectric materials with reduced dissipation factors, engineering magnetic cores with minimal hysteresis loop area, enhancing insulation surface integrity, and, in the case of HV corona, deploying conductor bundling, optimized sub-conductor spacing, and surface conditioning to suppress peak electric stress.

2.1.1. Core Losses in Transformers

Transformer core losses, often termed iron losses, stem from the alternating magnetic fields acting on the core material. They can be divided into two main types:
(A) Hysteresis Loss: When the magnetic domains within the core material realign under an alternating magnetic field, energy is dissipated as heat. Hysteresis losses occur due to the repeated magnetization and demagnetization of the transformer core material. These losses depend on the material properties and can be described by Steinmetz’s equation [94]:
P h = η B m a x n f V             ( W )
Here, η represents the hysteresis coefficient (which depends on the material’s intrinsic properties), B m a x n is the peak flux density, n is an exponent typically ranging between 1.6 and 2.5 (reflecting the non-linear behavior of magnetic materials), f is the operating frequency, and V is the core volume [95]. Materials with low coercivity—such as amorphous metals—exhibit reduced hysteresis loss because their magnetic domains require less energy to realign, resulting in lower energy dissipation. In distribution transformers of all sizes, minimizing core loss has become an essential design and manufacturing priority. Due to their thin structure and high resistivity, amorphous alloy ribbons exhibit low eddy current loss, while their small magnetic anisotropy results in low hysteresis loss [96]. These characteristics make amorphous ribbons increasingly favored for use in power systems, including distribution transformers and inductive devices. Compared with silicon steel cores, transformers using amorphous cores can achieve 60–70% lower no-load losses, depending on their capacity [97]. Kurita et al. [98] proposed a support structure and design method for large-capacity amorphous wound cores to reduce core losses. In a 10 MVA test transformer, the combination of stress-buffered supports, winding-induced electromagnetic reinforcement, and stray loss reduction shields led to a 35% reduction in total loss at 50% load compared with a conventional silicon–steel core, demonstrating the effectiveness of the design in lowering core losses. Additionally, Najafi and Iskandar [99] applied amorphous alloys in distribution transformers to improve efficiency and reduce no-load losses. Using the 2605SA1 amorphous core with higher saturation induction, they compared transformers with amorphous cores and conventional M5-type silicon steel cores. Three-dimensional finite element simulations and tests on 630 kVA 34.5/0.4 kV prototypes showed strong agreement, demonstrating that amorphous cores can reduce no-load losses by approximately 63% while enhancing transformer efficiency. Li et al. [97] investigated the loss deterioration mechanism and influencing factors of amorphous cores for distribution transformers. They found that increasing distributed gaps and fluctuations in boron content led to higher losses and changes in the optimal annealing temperature, while a sophisticated magnetic field annealing technique significantly reduced core loss.
In practical transformer design, hysteresis losses are addressed by optimizing both the core material composition and the operational flux level. While the frequency and flux density are dictated by application requirements, engineers can minimize losses by selecting materials with higher electrical resistivity and lower hysteresis coefficients, such as grain-oriented silicon steel or amorphous alloys. Moreover, precise control of the maximum flux density during operation ensures that the material is utilized below its saturation point, preventing a disproportionate increase in hysteresis loss. These considerations form part of a broader core loss optimization strategy, where hysteresis loss reduction complements eddy current mitigation through lamination thickness control and core stacking techniques.
  • Higher frequencies lead to increased hysteresis losses.
  • Material choice significantly affects hysteresis behavior.
  • Thinner laminations primarily reduce eddy current losses, while hysteresis losses depend dominantly on core material properties and operating flux density.
Table 3 summarizes hysteresis losses based on key factors, material properties, and reduction techniques.
This table provides a structured overview of the factors affecting hysteresis losses and suggests practical approaches to minimize them. To mitigate these losses, engineers should prioritize low-coercivity materials (e.g., amorphous metals or nanocrystalline alloys) that exhibit narrower hysteresis loops, thereby reducing energy dissipation during domain realignment. Additionally, optimizing core design to operate at lower flux densities, selecting materials with smaller Steinmetz exponents (n), and employing thermal annealing to refine grain structure can collectively minimize losses. For high-frequency applications, material stability must be validated across the intended temperature range. Practical implementation of these strategies coupled with advanced modeling techniques like dynamic hysteresis loop visualization enables targeted loss reduction while maintaining transformer efficiency.
(B) Eddy Current Loss: The changing magnetic field also induces circulating currents (eddy currents) within the conductive core material. These currents produce Joule heating, which constitutes an additional loss component. The eddy current loss can be modeled as follows: [100]
P e = V B m a x f t 2 ( W )
In this expression, t is the lamination thickness. Consequently, by using thinner laminations—such as amorphous or nanocrystalline alloys—and materials with higher resistivity, both the available loop area and the effective conductivity for eddy currents are reduced, which in turn minimizes Joule heating and substantially lowers eddy current losses [101]. Advanced core designs employing GOES or amorphous alloys can significantly reduce combined losses compared to traditional core configurations. Regulatory initiatives—such as those introduced by India’s BEE—now require the use of star-rated transformers, which have been shown to offer substantial improvements in efficiency through reduced energy losses.
Eddy current losses in transformer cores originate from circulating currents induced by time-varying magnetic flux, as dictated by Faraday’s law, and manifest as localized Joule heating within the conductive core material. These losses exhibit a distinct spatial non-uniformity, frequently intensifying in regions near joints, corners, and air gaps where fringing fields and flux leakage are most pronounced. The magnitude of eddy current losses is determined by a combination of factors, including the electrical resistivity of the core material, the lamination thickness, the uniformity of interlaminar insulation, the operating frequency, and the peak magnetic flux density. Cutting-edge mitigation strategies target three primary domains: (i) material engineering—the application of high-resistivity amorphous metals or nanocrystalline alloys to weaken induced current loops; (ii) microstructural and geometric optimization—employing ultra-thin laminations (≤0.3 mm) with high-fidelity interlayer insulation and precise stacking factor control to impede current circulation; and (iii) operational refinement—adjusting flux density and reducing operating frequency where feasible to proportionally lower loss magnitude.
Galván et al. [102] examines transformer losses by categorizing them into three main types: high-current bushing losses, core joint losses, and stray losses in the transformer tank. A significant portion of these losses arises from eddy currents in the core and surrounding metallic components, leading to heat generation and reduced efficiency. High-resolution FEA has emerged as a pivotal technique for mapping localized loss hotspots, enabling early detection of thermal stress regions and guiding iterative design improvements. Advanced materials, such as domain-refined grain-oriented electrical steels treated through laser scribing, and hybrid core architectures that combine different material layers, have demonstrated in-field loss reductions and improved thermal stability. Compliance with international efficiency standards (e.g., IEC 60076, Power transformers—Part 1: General, International Electrotechnical Commission, Geneva, Switzerland, 2011) ensures the translation of laboratory-scale optimizations into measurable performance gains under real-world operating conditions. Implementing these strategies can lead to substantial reductions in eddy current losses, enhancing overall transformer efficiency [103].
(C) Trade-Off between Losses: Understanding the trade-off between eddy current and hysteresis losses is crucial for optimizing transformer efficiency. Since both losses are functions of magnetic flux density (B) and frequency (f), altering these parameters impacts the total fixed loss differently. This section presents a comparative analysis table to illustrate the interplay between these two loss mechanisms. Table 4 summarizes key observations regarding the interaction between eddy current and hysteresis losses.
This trade-off analysis helps in selecting optimal transformer design parameters to minimize overall fixed losses.

2.1.2. Dielectric Losses

Dielectric losses occur in insulating materials used in cables, bushings, and other components due to the molecular friction caused by the oscillation of dipoles under an alternating electric field. This phenomenon is characterized by the loss tangent ( tan γ ), which provides a measure of the material’s inefficiency in storing electrical energy. The dielectric loss can be expressed as follows [104]:
P d = 2 π f ε 0 · ε r E 2 t a n γ ( W / m 3 )
where C is the capacitance of the insulating system and V is the applied voltage. Materials such as XLPE show a much lower tan γ (typically between 0.001 and 0.002) compared to traditional materials like PVC, which may exhibit values as high as 0.02–0.05. Moreover, HVDC systems can inherently eliminate dielectric losses associated with capacitive charging currents, thereby offering improved efficiency for long-distance power transmission [19]. Table 5 presents a comparative analysis of dielectric losses across prominent insulation materials used in power networks.
Table 5 highlights the trade-offs between different insulation materials in terms of dielectric performance. While mineral and silicone oils provide lower dielectric losses, solid-state insulation materials like epoxy resin have higher losses but offer better mechanical and thermal resilience. SF6 gas has the lowest dielectric loss but is now largely prohibited in new installations due to its extreme global warming potential. It is restricted under international agreements and replaced by eco-friendly alternatives like fluoronitriles or dry air in modern systems. To further illustrate the variation in dielectric losses, Figure 1 illustrates the primary mechanisms contributing to dielectric losses, namely conduction loss, dipolar polarization, defect induced polarization, and interfacial polarization. Conduction loss typically dominates at low frequencies due to leakage currents, with its influence diminishing as frequency increases. Dipolar polarization, arising from the reorientation of polar molecules under an alternating field, becomes more significant at intermediate frequencies but decreases at higher frequencies due to relaxation time limitations. Defect-induced polarization, often associated with charge trapping in structural defects or impurities, affects a broad frequency range and contributes to dispersion behavior. Interfacial polarization, especially relevant in heterogeneous or composite materials, originates from dielectric and conductivity mismatches at phase boundaries and is more pronounced at low frequencies. The superposition of these mechanisms results in a frequency-dependent loss profile with distinct dominant regions, each exhibiting different slopes and patterns. Therefore, a frequency resolved perspective that accounts for the simultaneous contribution of multiple mechanisms is essential for accurate understanding and optimization of dielectric material performance.
Dielectric losses have significant implications for equipment design, performance, and longevity. High dielectric losses lead to excessive heating, which can degrade insulation materials and ultimately compromise equipment reliability. To minimize these losses and improve efficiency, several mitigation strategies can be employed [105]:
(A) Material Selection: The choice of insulation material plays a critical role in minimizing dielectric losses. Materials with a lower dielectric loss tangent ( tan δ ) should be preferred, as they exhibit reduced energy dissipation.
(B) Temperature Control: Since dielectric losses are temperature-dependent, excessive heating accelerates insulation degradation and increases losses. Effective thermal management strategies, such as forced cooling systems, proper ventilation, and heat dissipation mechanisms, help maintain insulation integrity and reduce losses.
(C) Moisture Management: The presence of moisture significantly increases dielectric losses by altering the electrical properties of insulation materials. Implementing stringent moisture control measures, including the use of desiccants, sealed transformer enclosures, and periodic oil filtration, can enhance insulation performance.
(D) Voltage Stress Reduction: HV stress intensifies dielectric losses and accelerates insulation aging. Proper transformer design, including optimized winding configurations, controlled voltage gradients, and the use of stress-relief coatings, can help mitigate voltage-induced dielectric losses.
(E) Relationship Between Operating Frequency and Dielectric Behavior: Since dielectric losses are frequency-dependent, transformers operating at higher frequencies require specialized insulation materials with minimal dielectric dissipation. Understanding the relationship between operating frequency and dielectric behavior enables engineers to design transformers with optimized loss characteristics.
By implementing these strategies, efficiency can be significantly improved, ensuring a longer operational lifespan and reduced maintenance costs.

2.1.3. Corona Losses

Corona loss occurs when the electric field around a high-voltage conductor exceeds the ionization threshold of air, producing a visible glow or audible noise due to partial ionization [106]. This leads to energy dissipation that increases with voltage, surface defects, and adverse weather. Besides power losses, corona discharge causes electromagnetic interference, may affect nearby communications, and generates ozone and NOx with environmental impacts. As shown in Figure 2, corona typically appears near regions of the highest electric stress, such as sharp edges or geometries that intensify the field.
This ionization leads to corona discharge—a partial breakdown of the air—resulting in energy loss, audible noise, and EMI. Peek’s formula is commonly used to estimate the critical disruptive voltage ( V c ) for corona onset [107]:
V c = 21.2 m ρ r ln D r [ k V P h a s e ]
Here, m is a factor accounting for surface irregularities, ρ represents the relative air density (which varies with altitude and weather conditions), r is the conductor radius, and D is the spacing between conductors. In adverse weather conditions such as high humidity or rain, corona losses can escalate dramatically, reaching values between 10 and 20 kW/km. To mitigate these losses, engineers often employ bundled conductors, which increase the effective radius and can reduce losses by up to 40%, or install corona rings to redistribute the electric field stress along insulator strings. Field studies, including an investigation on Brazil’s 500 kV TRLs, suggest that such mitigation measures can reduce corona losses [17].
Under the typical electric field intensities at which TRLs are designed to operate, corona discharge primarily manifests in two distinct modes. In the case of positive corona, the pulse exhibits a sharp initial rise due to the rapid acceleration of electrons and sudden ionization of surrounding air molecules, followed by a gradual decay corresponding to the slower processes of charge carrier recombination and density reduction. Conversely, the negative corona initiates with a short, sharp negative peak resulting from the prompt emission and acceleration of electrons from the cathode, subsequently transitioning to a smoother positive component attributable to recombination and the return motion of charge carriers. Both of these corona discharge modes generate current pulses that exhibit a rapid rise time and a brief duration, as illustrated in Figure 3.
Both AC and DC TRLs experience both positive and negative corona discharges, but their behavior differs significantly between the two systems. In AC TRLs, corona discharge of both polarities occurs on all phase conductors due to the alternating nature of the voltage. In contrast, DC TRLs exhibit a more localized corona effect, with positive corona forming near the positively charged conductor and negative corona occurring near the negatively charged conductor [109].
This distinction also affects how charged particles behave in the surrounding air. In an AC system, ions generated during one half-cycle are drawn back to the conductor during the opposite half-cycle, preventing significant accumulation of space charge—such as small air ions and charged aerosols. However, in a DC system, the charge does not oscillate in this manner. Instead, positive ions accumulate around the positively charged conductor, while electrons and negative ions cluster around the negatively charged conductor. Over time, this leads to a notable buildup of space charge in the vicinity of the conductors with opposite polarities [106,110].
An important consequence of this space charge accumulation in DC systems is its influence on the electric field near the conductors. The presence of a larger number of ions near the conductors tends to lower the local electric field. This contrasts with AC TRLs, where corona activity—and consequently potential EMI—is most intense during adverse weather conditions. In DC TRLs, however, the increased presence of corona-generated ions in poor weather conditions actually mitigates the intensity and extent of corona discharge by weakening the electric field near the conductor [95,111]. To minimize corona-induced losses in AC TRLs, optimizing conductor geometry—such as employing bundled conductors or increasing diameter—reduces the electric field gradient, suppressing discharge initiation. Surface smoothing and corona rings further mitigate localized field enhancements. For DC systems, balanced bipolar configurations and optimal conductor spacing mitigate space charge accumulation. Advanced solutions include hydrophobic coatings to minimize water-induced corona and real-time monitoring for predictive maintenance, enhancing efficiency while reducing corona-related energy dissipation. Trapezoidal surface profiles, semiconductor coatings, and hybrid conductor bundles (such as ACSS/TW) can be utilized to homogenize surface electric fields. Also, dynamic adjustment of operating voltages relative to real-time atmospheric pressure/visibility conditions using predictive algorithms can reduce field strength during loss-favorable conditions without compromising voltage regulation. Corona management is not merely about eliminating audible noise or radio interference—it constitutes a fundamental strategy for breaking the chain of harmonic-induced loss amplification. When integrated with harmonic filtering and adaptive voltage control, corona suppression delivers non-linear reductions in cumulative TLs by disrupting the inter-component loss reinforcement mechanisms.
Nawi et al. [112] studied the impact of corona on 275 kV TRLs subjected to lightning surge propagation. A comparative analysis between ACSR and ACCC conductors was carried out using PSCAD/EMTDC simulations. The results showed that ACCC conductors reduce corona-related losses more effectively, providing higher efficiency than ACSR. Additionally, Riba et al. [113] reviewed the impact of high-altitude conditions on air-insulated TRLs, highlighting discrepancies in existing atmospheric and voltage correction factors. They emphasize the need for updated standards and research to ensure accurate testing and reliable insulation performance at high altitudes. In another study, Tonmitr et al. [114] analyzed corona-induced power losses in 115 kV and 230 kV transmission lines and identified optimal conductor radii and spacing to minimize losses. Adjusting these parameters reduced power losses. Also, weather conditions and voltage levels have a major impact on corona-induced power losses. Energy losses in high-voltage overhead lines can be significantly reduced when voltage drops slightly during rain or frost accumulates on the wires [115]. Salameh et al. [116] applied genetic algorithm optimization to optimize HV TRL conductors, reducing electric and magnetic field emissions, preventing corona, and increasing power capacity. The method was validated against measured data and compared with PSO and unoptimized lines, showing significant improvements while maintaining conductor spacing within IEC-71 limits. In a significant and prominent work, Riba and Moreno [117] demonstrated that corona losses, as part of the TLs in overhead TRLs, are generally negligible under fair weather conditions, typically accounting for less than 2% of Joule losses. However, under light loading, severe conductor contamination, or adverse weather such as rain and hoarfrost, corona losses can match or even exceed Joule losses, leading to substantial reductions in current-carrying capacity. Although international standards including IEEE, IEC, and Cigré often disregard corona losses in thermal conductor models and DLR approaches, Riba and Moreno’s findings underscore that under certain operating and environmental conditions, corona losses constitute a significant portion of TLs and should be incorporated into advanced modeling frameworks to ensure accurate ampacity predictions and enhance system reliability. To minimize corona-induced losses in AC TRLs, optimizing conductor geometry—such as employing bundled conductors or increasing diameter—reduces the electric field gradient, suppressing discharge initiation [118].

2.1.4. Leakage Current Losses

Leakage current losses arise from imperfections in insulation that allow small currents to flow over or through insulating materials. Factors such as aging, contamination from pollutants, moisture ingress, and salt deposition in coastal areas can exacerbate these losses. In polluted or humid environments, the conductive path provided by contaminants can increase leakage losses by 30–50%. Modern composite insulators employing hydrophobic silicone rubber are designed to repel moisture and contaminants, thereby cutting leakage losses by as much as 70% compared to traditional porcelain insulators. Regular maintenance practices, including cleaning and the application of RTV silicone coatings, are essential to maintaining insulation integrity and minimizing leakage currents. By addressing each of these fixed loss mechanisms through material innovations, optimized design, and proactive maintenance, utilities can achieve significant improvements in energy efficiency and system reliability. Advances in material science and numerical modeling, including finite element analysis and harmonic testing, continue to refine our understanding of these losses, paving the way for more efficient power systems [119,120]. Accurately predicting flashover voltage on single-disc insulators is possible through advanced statistical analysis of leakage current. Extensive studies have explored the connection between leakage current and flashover voltage. However, applying these findings to real-time insulator monitoring presents three challenges. First, most research focuses on leakage current just before flashover. Yet insulators in the field operate at lower voltages, leading to different leakage current behavior. Second, natural pollution is unpredictable and differs from controlled artificial contamination. The type of pollutant layer may influence the leakage current–flashover relationship. Third, laboratory tests often use moisture-saturated pollutants in fog chambers. In real conditions, factors like humidity and air pressure also impact flashover voltage. These environmental influences on leakage current require further investigation [121,122].

2.2. Variable Losses

Variable losses in power systems depend directly on the load current and are largely a function of the operating conditions in the network. These losses scale with the square of the current (I2) and are primarily composed of Joule losses, impedance-related losses, and contact resistance losses [12]. Each of these phenomena has distinct underlying mechanisms and offers unique opportunities for technical mitigation. Understanding and minimizing these losses is crucial in improving system efficiency and reliability.

2.2.1. Joule Losses

Joule losses represent the power dissipated as heat when an electrical current flows through a resistive element. The fundamental equation governing these losses is P j = I 2 R : Resistance itself is a function of both the conductor material and its temperature. The temperature dependence of the resistance is expressed as follows:
R ( T ) = R 0 1 + α T T 0
where α is the temperature coefficient 0.004   ° C 1 for copper). As the operating temperature increases (for instance, during periods of high load or extreme ambient conditions), the resistance rises, thereby increasing Joule losses. Detailed thermal modeling and real-time temperature monitoring are crucial for accurately estimating these losses, as highlighted in studies on conductor thermal behavior [123]. Several mitigation strategies can be implemented to reduce these losses, including the following:
(A) Conductor Upgrading: Conductors significantly impact TLs in distribution systems, necessitating optimal selection for cost efficiency. Low-voltage systems, typically underloaded relative to thermal capacity, exhibit higher currents, increasing loss sensitivity. Conductor losses depend on connection quality, size-to-current capacity ratio, and system voltage. Aluminum and copper are preferred due to their low resistivity, but proper sizing and installation are critical to minimizing energy losses [23].
One effective method to reduce Joule losses is replacing conventional ACSR cables with HTLS conductors. Replacing ACSR cables with HTLS conductors, such as ACCC, reduces resistive losses through enhanced design and material innovation. HTLS conductors are engineered to operate efficiently at elevated temperatures, minimizing sag while maintaining structural integrity. The composite core in ACCC conductors, typically made of advanced materials like carbon fiber, offers superior thermal stability compared to the steel core in ACSR. This allows ACCC to sustain higher current loads (ampacity) without significant resistance increases, even under high-temperature conditions. By optimizing current distribution and reducing resistance at elevated operating temperatures, HTLS conductors lower overall resistive losses compared to conventional ACSR [124]. The selection of conductor cross-sectional area represents a fundamental design parameter for minimizing I2R losses in power distribution networks. According to Ohm’s Law principles, the resistance of a conductor exhibits an inverse proportionality to its cross-sectional area, as expressed by the relationship. Consequently, specifying conductors with larger cross-sections directly reduces resistive power losses while improving current-carrying capacity. Also, the study by Y. Eduave et al. [125] demonstrates that replacing 2/0 distribution conductors with ACSR 3/0 (AWG 6/1) reduces TLs by 8%. While the project increases electricity costs in the short term (1.20/kWh for 3-year recovery), it yields long-term savings (0.35/kWh). However, a more detailed assessment of technical limitations (conductor resistance, thermal effects, line configuration) and economic factors (for instance inflation) is necessary. Additionally, Nuchprayoon et al. [126] evaluated the costs of increasing current capacity in overhead TRLs and found HTLS conductors to be an attractive replacement for conventional ACSR, primarily due to lower total energy loss costs under appropriate operating temperatures. They recommended using HTLS conductors—preferably operated below their maximum temperature—to ensure efficiency and minimize losses. Their study highlights that extra ampacity should be reserved for emergencies, and cost of energy losses is the key factor in conductor selection. Table 6 summarizes the impact of different conductors on resistive losses.
(B) DLR: DLR is an advanced grid management system that dynamically adjusts the ampacity of OHLs based on real-time environmental conditions and conductor temperature [117,127]. Unlike conventional SLR, which uses conservative, worst-case assumptions (e.g., high ambient temperature, no wind), DLR employs sensor networks (e.g., thermocouples, anemometers) and thermodynamic models (e.g., IEC 61597 Technical report, Overhead electrical conductors—Calculation methods for stranded bare conductors, International Electrotechnical Commission, 2021, https://webstore.iec.ch/en/publication/61412 (accessed on 22 August 2025)) to optimize line capacity. By leveraging favorable cooling conditions (e.g., wind speed > 2 m/s), DLR increases allowable current flow while maintaining safe conductor temperatures. This reduces Joule losses by lowering current density under enhanced cooling. However, integrating DLR into existing grid infrastructure introduces challenges related to protection scheme compatibility [128]. Traditional overcurrent and distance relays are calibrated based on static ratings, which may not respond optimally to dynamic ampacity changes. Adaptive protection schemes or real-time relay coordination algorithms are required to ensure seamless operation under DLR conditions. By deploying DLR systems with real-time sag monitoring and short-term forecasting, it is possible to achieve a substantial enhancement in intraday transmission capacity compared to conventional static ratings. Thermal limitations are crucial in determining the capacity of shorter TRLs (≤100 km), especially in OHLs where sag and clearance constraints must be managed. System stability is another critical consideration, as real-time variability in line ratings can impact voltage regulation and transient stability. Rapid ampacity fluctuations may lead to unexpected power flow redistributions, increasing the risk of cascading failures. Advanced control strategies, such as model predictive control or wide-area monitoring systems, can mitigate these risks by providing dynamic stability margins. DLR enhances grid efficiency by dynamically adjusting ampacity based on real-time monitoring of environmental and conductor conditions. Real-time sag management becomes critical here, as environmental variations directly influence conductor temperature. However, DLR’s accuracy depends on high-precision monitoring of wind speed/direction, solar irradiance, and conductor temperature. Errors in these parameters may lead to unsafe sag estimates. Regulatory barriers also pose significant challenges to DLR adoption [128,129]. Many grid codes and operational standards are designed for static ratings, requiring updates to accommodate dynamic line ratings. Regulatory frameworks must address liability concerns, such as determining responsibility for line failures during DLR operation. Additionally, market mechanisms for DLR-based capacity allocation need standardization to ensure fair utilization across transmission system operators. Three primary monitoring methodologies are applied:
  • Direct measurement (contact/non-contact temperature sensors).
  • Indirect calculation (thermodynamic models with weather inputs).
  • Hybrid approaches (machine learning-enhanced physical models).
Despite its benefits, DLR requires significant infrastructure investments, including sensors, communication systems, and advanced analytics platforms. Economic viability is highest in corridors with high line utilization or regions with substantial renewable energy integration, where grid flexibility is paramount. For longer TRLs (>100 km), voltage stability and reactive power balance often supersede thermal limits, reducing DLR’s relative impact. The estimation of conductor temperature, which determines DLR values, relies on three main monitoring approaches [130]:
Ambient-Based Methods use weather data (wind, temperature, solar radiation) to model conductor temperature. They are cost-effective but less reliable due to localized weather variations. Standards from CIGRE [131] and IEEE [123] guide the modeling of conductor thermal behavior.
Thermal-Based Methods directly measure conductor surface temperature. They provide real-time data but are limited to specific points along the line. Temperature variations along different sections of the line due to environmental conditions can lead to inconsistencies in the estimation of thermal limits.
Mechanical-Based Methods—These methods estimate conductor temperature by monitoring sag, clearance, or tension changes along the line, as shown in Figure 4. Since conductor temperature directly influences sag and inversely affects clearance and tension, these mechanical parameters serve as indirect indicators of thermal conditions. The advantage of this approach is that it provides a more comprehensive temperature profile across the entire line span rather than localized measurements.
Table 7 summarizes the implementation of DLR systems across various European countries between 2008 and 2020. For each project, the location, commissioning year, scope and description, system design approach, and key operational outcomes are presented. The data show that employing DLR, whether through direct sag measurement or indirect, non-contact meteorological modeling, consistently led to increased transmission capacity, in some cases up to twice the nominal rating, while mitigating overload events. These results highlight the role of DLR as a cost-effective, rapidly deployable solution for optimizing the utilization of existing transmission infrastructure.
By integrating these monitoring approaches, DLR systems enhance transmission efficiency and reliability, ensuring optimal utilization of existing infrastructure while maintaining operational safety. As evidenced in Table 8, both HTLS conductors and DLR systems offer unique approaches, each with specific technical and operational trade-offs. HTLS technology requires physical reconductoring of TRLs, while DLR implementation demands sophisticated sensor networks and seamless integration with control systems. These fundamental differences in deployment requirements significantly influence technology selection for grid operators. The choice between these technologies depends critically on project timelines, budget constraints, and specific grid modernization objectives. The integration of HTLS conductors and DLR systems capitalizes on the inherent high thermal endurance of HTLS metallurgy, which provides a stable ampacity baseline independent of short-term climatic variations, and the adaptive capabilities of DLR, which exploits real-time meteorological conditions to further increase line capacity. This dual approach maintains clearance and thermal margins under sustained high-load conditions while enabling safe temporary overloading during favorable weather, thus yielding compounded benefits in both loss reduction and operational flexibility. Table 8 shows a comparison of their relative advantages in increasing ampacity and practical implementation considerations.

2.2.2. Impedance Losses

Impedance ( Z = R + j X ) causes both real and reactive losses. Inductive reactance ( X L = 2 π f L ) introduces voltage drops and reactive power demand. Capacitive reactance ( X C = 1 / ( 2 π f C ) ) generates charging currents in long lines. In long TRLs, capacitance between conductors or between conductors and the ground generates charging currents that lead to additional losses. These charging currents do not perform useful work but contribute to the overall loss profile.
Reactive power flows, due to this reactance, necessitate power factor correction to improve system efficiency. Shunt capacitor banks are commonly deployed to counteract the lagging power factor caused by inductive loads, as demonstrated by a 20% reduction in losses in South Africa’s 400 kV network [136].
Another critical phenomenon is the skin effect, where at higher frequencies the current density is higher near the surface of the conductor. This effect increases the effective AC resistance and thereby the Joule losses. Figure 5 illustrates a generalized scheme of the skin effect.
The skin effect occurs due to self-inductance in the conductor. As an AC flows through the conductor, it creates changing magnetic fields, which induce eddy currents within the material. These eddy currents oppose the flow of current in the interior of the conductor, causing most of the current to concentrate on the outer layers, thus reducing the effective area for current flow. Several key factors influence the strength of the skin effect. The frequency of the AC plays a significant role, as higher frequencies result in a more pronounced skin effect, pushing the current even closer to the surface. Material conductivity also affects the skin effect, with highly conductive materials like copper and silver exhibiting stronger skin effects because they allow the current to flow more easily on the surface. The permeability of the material is another important factor; magnetic materials, such as iron, show a more substantial skin effect due to their ability to concentrate magnetic fields. Lastly, temperature can influence the skin depth by altering the material’s conductivity—generally, as temperature increases, the conductivity decreases, which in turn can reduce the skin depth and exacerbate the skin effect [138,139]. The skin depth ( δ ) is given by the following [137,140]:
δ = 2 ρ 0 ω μ
where ρ 0 is the resistivity of the material (Ω·m), ω indicates angular frequency ( ω = 2 π f ) , and μ is the magnetic permeability of the material (H/m). Skin depth values for different materials are shown in Table 9. An important point worth mentioning is that, since DC has no frequency-dependent variations, there is no skin effect, and the current flows evenly throughout the conductor. The skin effect only occurs in ACs, where high frequencies force current toward the surface.
On the other hand, the skin effect has significant implications for various electrical components, particularly in high-frequency applications. In power TRLs, high-frequency signals experience increased resistance due to the skin effect, leading to higher energy losses. To mitigate this issue, engineers use larger conductors or employ stranded conductors with specialized designs, such as Litz wires, which help distribute current more evenly across the conductor. In transformers and inductors, where high-frequency currents are common, core materials with low permeability are selected to minimize the skin effect’s impact. Additionally, laminated cores and special winding techniques are employed to reduce eddy current losses and improve efficiency. The skin effect also plays a crucial role in RF and microwave circuits, where extremely high frequencies push the current to the very outermost layer of the conductor. To enhance surface conductivity and minimize losses, conductors in such applications are often plated with silver or gold, materials with exceptionally high conductivity. These design considerations help maintain efficiency and performance in electrical and electronic systems operating at high frequencies [144,145,146]. Mitigation techniques include the use of segmented conductors or expanded aluminum layers to provide a larger effective surface area, reducing the impact of the skin effect. More importantly, Litz wire, with its unique construction, is an effective solution for mitigating the skin effect in high-frequency TRLs, ensuring better efficiency and reduced power losses. Litz wire is made up of multiple insulated strands of wire, which are twisted or braided together. This structure ensures that each strand alternates between being near the surface and deeper inside the conductor. As the current flows through the wire, the alternating strands experience different positions in the wire, which allows the current to be distributed more evenly across the conductor. By doing so, Litz wire reduces the effective resistance caused by the skin effect, where current is typically confined to the outermost layer of a solid conductor [147,148].
Litz wire offers significant advantages in high-frequency power applications by minimizing AC resistance due to skin and proximity effects. While not typically used in standard RF TRLs such as coaxial cables or waveguides, it is ideal for inductors, transformers, and power links operating at frequencies from several kHz up to a few MHz. As a result, Litz wire improves efficiency and minimizes energy loss, making it ideal for applications like RF TRLs and microwave communication. It helps in maintaining a consistent power transfer without excessive resistance, ensuring minimal signal degradation and more efficient energy use [149,150]. Another significant advantage of Litz wire is its ability to reduce heat generation. By mitigating the skin effect, Litz wire lowers the AC resistance in TRLs, which consequently reduces the heat produced. This is especially important in high-frequency circuits and power transmission systems, where excessive heat can lead to overheating of cables, potentially causing damage or reducing the lifespan of components. In addition, the ability to prevent power loss also enhances the overall reliability and longevity of systems that rely on Litz wire, ensuring that they function efficiently even under demanding conditions.
However, Litz wire does come with some limitations. However, its complex manufacturing increases cost, limiting its use to specialized applications where high-frequency performance justifies the expense. At lower frequencies, the benefits of Litz wire are less pronounced, making solid conductors more economical. Despite these drawbacks, the performance advantages of Litz wire in high-frequency applications outweigh the challenges in many critical industries [151,152,153]. IBRs and smart transformers amplify high-frequency effects, injecting currents that degrade cable insulation and cause EMI, leading to increased voltage THD. Resonances and high-frequency carriers can further amplify harmonics [154]. Also, the proliferation of IBRs, such as solar PV and wind farms, introduces high-frequency harmonics (typically 2–15 kHz) that exacerbate frequency-dependent losses [155]. These harmonics (1) intensify the skin effect by reducing penetration depth, increasing AC resistance in aluminum conductors (2) elevate dielectric losses in XLPE cables, and (3) amplify transformer core losses. Mitigation strategies include active harmonic filters, Litz wires for high-frequency conductors, nanocomposite dielectrics, and amorphous-core transformers.

2.2.3. Contact Resistance Losses

Contact resistance losses occur due to imperfect or degrading electrical connections, leading to localized heating (hotspots) at junctions such as cable joints, circuit breakers, and transformer terminals. These losses are particularly significant in high-power systems, where even small resistance values can cause substantial energy dissipation. The R c depends heavily on the following factors [156,157]:
(A) Surface Roughness: A smoother contact surface reduces microscopic gaps that increase resistance. Microscopic asperities on contact surfaces reduce the effective contact area, increasing R c . Polished or plated surfaces mitigate this effect.
(B) Oxidation: Oxidation in metallic joints leads to the rapid formation of an insulating surface film—alumina on aluminum and cuprous/cupric oxides on copper—that sharply reduces true metal-to-metal contact. This oxide layer can readily double or triple the micro-scale contact resistance, creating localized heating and accelerating joint degradation. Effective mitigation demands thorough oxide removal during assembly and the use of high-performance antioxidant compounds to inhibit reoxidation under service conditions [158,159].
(C) Contact Pressure: Low-pressure connections exhibit higher resistance due to incomplete surface contact, while excessive pressure can cause material deformation, leading to long-term reliability issues.
To mitigate contact resistance losses, several engineering practices are implemented. One effective method is the use of silver-plated contacts. Silver has high conductivity and superior resistance to oxidation compared to aluminum and copper. Applying silver plating on high-current breakers and transformer bushings reduces R c and enhances long-term stability [160]. Another key technique is ultrasonic welding. This process creates strong metallurgical bonds between conductors without needing additional materials like solder. It ensures low-resistance joints in overhead power lines and electrical connections. Ultrasonic welding improves durability, reduces maintenance needs, and enhances overall system efficiency. This method is widely used in power grids, battery pack assemblies, and aerospace applications [161,162]. A more recent innovation is self-healing contact interfaces. These advanced materials use conductive coatings that repair microgaps and cracks caused by oxidation. By forming conductive bridges, they help maintain low resistance over time. Researchers are exploring these materials for aerospace and high-reliability electrical networks. If successfully developed, they could extend the lifespan of electrical components and improve energy efficiency in critical systems [163]. A comparative analysis of various contact materials and their resistance characteristics is provided in Table 10.
The implementation of optimized contact materials and joining techniques not only reduces losses but also enhances system reliability, reducing maintenance costs and the risk of failures. Future research could explore nanostructured coatings and advanced pressure-controlled connectors to further mitigate contact resistance losses. In OHL and substation applications, aluminum remains the conductor of choice due to its low density and favorable cost-to-conductivity ratio, yet its propensity to form a tenacious Al2O3 film poses a persistent challenge for reliable joint performance. Under ideal surface preparation—wire-brushing to remove native oxide followed immediately by the application of a high-quality antioxidant paste—initial contact resistances in aluminum remain imperceptibly low; however, without such measures, microscopic voids in the oxide layer can elevate local resistances into the kilo-ohm regime, effectively interrupting current flow at asperity contacts. Over a ten-year horizon, properly torqued connectors conforming to (IEEE 837 IEEE Standard for Qualifying Permanent Connections Used on Substation Grounding, IEEE, USA, 2014) and (IEC 61238-1, Compression and mechanical connectors for power cables—Part 1-1: Test methods and requirements for compression and mechanical connectors for power cables for rated voltages up to 1 kV (Um = 1.2 kV) tested on non-insulated conductors Publisher: International Electrotechnical Commission, Geneva, Switzerland, 2018) exhibit only low to moderate drift in resistance, thereby confining joint-related power dissipation within acceptable margins. In contrast, poorly maintained or mechanically fatigued interfaces may incur pronounced energy losses and premature failure. To counteract aluminum’s propensity for thermal creep and cyclical dimensional shifts, modern connector designs often incorporate resilient spring elements or Belleville washers that preserve consistent contact pressure under fluctuating loads. Best practice therefore combines rigorous surface deoxidation, standardized compression hardware, antioxidant compounds (e.g., NOALOX), and periodic inspection (typically every 1–3 years in polluted or humid environments) to preserve low resistance, forestall hot-spot formation, and secure long-term network efficiency.

3. Power Losses: A Cross-Country Analysis of Present Conditions

The absence of standardized methodologies for quantifying and reporting losses complicates cross-border benchmarking efforts within the world. Most countries define aggregate grid losses simply as the difference between injected and withdrawn energy, without distinguishing between technical and non-technical contributions. Transmission networks generally exhibit lower percentage losses compared to distribution systems, primarily due to higher operating voltages that reduce current magnitude and, consequently, resistive losses. Additionally, transmission losses are typically measured directly or derived from metered parameters, whereas distribution losses are frequently estimated due to the lack of comprehensive monitoring infrastructure. This disparity underscores the need for harmonized loss assessment frameworks to enhance grid efficiency comparisons. Table 11 provides an overview of how power losses are defined, managed, and reported across selected countries, specifically highlighting the distinctions made between TLs and NTLs in each national context. The comparison demonstrates the extent to which each country’s regulatory or reporting framework differentiates NTLs such as unauthorized usage, data errors, or unmetered consumption from TLs, which are typically caused by physical and operational factors within the electricity network. The diversity of these practices further highlights the significant role that standardization can play in ensuring consistent and transparent loss reporting across different regions.
Figure 6 illustrates the considerable value of loss reduction and highlights its particular significance across various countries. By comparing international data, it becomes evident that minimizing losses is a key priority in several regions due to its substantial economic and environmental impacts. Efficiently minimizing losses in the electricity T&D network not only conserves valuable energy resources but also contributes to economic savings and environmental protection. Also, Navani et al. [167] highlight that significant energy is lost in India’s transmission and distribution system, with losses rising from 15% in 1966–1967 to over 28% by 2011–2012, largely due to TLs and NTLs. Their study analyzes the causes and economic impacts of these losses through a case study in Noornagar, Ghaziabad, using MATLAB simulation.
Although in theoretical terms, TLs constitute only a fraction of total power losses, most countries actively pursue their minimization [165]. In the Mediterranean region, the predominant and most severe source of such losses arises from the inherent electrical resistance of conductors, as illustrated in Figure 7.
The figure further indicates that transformer core losses constitute the second most significant contributor to TLs. According to the study by Jiménez et al. [169], if no actions are taken to improve the current situation, annual electricity losses in Latin America and the Caribbean are projected to reach 427 TWh by 2030. Of this amount, approximately 182 TWh would stem from losses exceeding 10 percent of total electricity output. Notably, this figure is equivalent to twice the annual electricity generation of Itaipu, the region’s largest hydroelectric power plant in Paraguay. This highlights the critical importance of reducing TLs, as doing so increases network efficiency, decreases the need for additional electricity generation, and reduces pressure on energy resources and the environment. Moreover, lowering TLs improves grid reliability and stability, ensuring a more secure and consistent electricity supply for consumers.

4. Mitigation Approaches for Technical Power Losses

4.1. Advanced Conductor Materials

4.1.1. HTLS Conductors

The integration of advanced conductor materials in power T&D networks is a pivotal strategy to mitigate TLs, particularly resistive losses. Among the most promising innovations are HTLS conductors, which are designed to operate at elevated temperatures while maintaining mechanical stability. Unlike conventional conductors, HTLS materials exhibit reduced sag and superior current-carrying capabilities, making them ideal for modern power grids facing increased energy demands and the growing penetration of renewable energy sources. These conductors enable utilities to optimize existing infrastructure. thereby improving overall grid efficiency. Mateescu et al. [170] highlight that Romania’s integration into the European transport network and the deployment of large-scale Aeolian turbines necessitate upgrades to existing power lines to handle increased transmission capacities. The study examines the reconductoring of the 220 kV double-circuit Bucharest South Fundeni line, evaluating technical, environmental, and economic factors when implementing HTLS conductors. Also, the results indicate that the choice of conductor significantly influences the direct procurement, installation, and maintenance costs, as well as the long-term costs attributed to power losses over a 30-year period. Among the evaluated options, GZTACSR and ZTACSR exhibit the highest total costs, largely due to their elevated energy loss components, while ACCC/TW demonstrates the lowest overall expenditure, highlighting its superior efficiency. This breakdown underscores the substantial share of long-term power loss costs in total project expenses, particularly for conventional conductors. Overall, the analysis suggests that careful selection of advanced conductor types such as ACCC/TW can offer considerable long-term economic benefits for transmission system upgrades. Based on the comprehensive economic analysis, which incorporates both direct expenses and power loss costs, ACCC/TW and ACSS emerge as the most cost-effective solutions, as illustrated in Figure 8. Also, in a 2020 investigation, Kachhadiya et al. [171] analyzed the performance gains achievable by uprating a 220 kV transmission line in India through reconductoring with various HTLS conductor technologies. Their results showed that at an operating temperature of 175 °C, the ACCC achieved a 33.3% line loading, outperforming ACSR conductors, which reached only 87.2%. Under N-1 contingency conditions, ACSR experienced an extreme overload of 164%, whereas ACCC limited the loading to 62.4%. The study further indicated that replacing the 4.6 km double-circuit line with ACCC incurred 58.9% lower costs than constructing new infrastructure, while simultaneously doubling the power transfer capacity. Overall, the findings highlighted ACCC as offering an optimal combination of enhanced current-carrying capability, lower energy losses, and cost efficiency, making it an attractive solution to address both thermal and emergency constraints in India’s transmission network. Also, Slamet et al. [172] analyzed power losses and voltage regulation in a 251 km transmission line using ACSR Dove conductors, finding daily losses averaging 9.09 MW and totaling 272.92 MW in one month, despite voltage remaining within safe limits. They highlighted the inefficiency of ACSR and suggested replacing it with ACCC conductors to reduce losses.
Ujah et al. [173] highlighted that poor maintenance and lack of innovation in power transmission conductors hinder electricity availability and economic growth in developing countries, recommending advanced materials and improved conductor technologies. Additionally, in another study, Ujah et al. [174] emphasized that increased electricity demand and inadequate grid maintenance have worsened power outages, especially in Africa and Asia, with both natural and technical factors further degrading transmission reliability. Their review highlights the critical role of advanced materials technology, noting that developing nano-based aluminum composite conductors can significantly enhance grid performance, durability, and cost-effectiveness. The literature review indicates that conductor selection is a critical step in the transmission planning process; however, practical guidelines to simplify this decision for grid planners have not yet been developed. Youba Nait and Heleno [175] provide guidelines to improve conductor selection by applying a rigorous methodology to a real reconductoring project in the U.S., comparing the technical and economic performance of conventional and HTLS conductors. Various kinds of HTLS conductors can be classified as follows [124,176]. Also, reducing series resistance R via reconductoring, by replacing lines with larger conductors, effectively minimizes distribution load losses [23].
(A) TACSR: TACSR is a high-temperature conductor that consists of aluminum alloy strands reinforced with a galvanized steel core. This design enhances its mechanical strength while allowing it to operate at elevated temperatures without significant sag. TACSR conductors can withstand temperatures of up to 210 °C, making them suitable for TRLs that require increased current-carrying capacity without major structural modifications [177].
(B) ZTACSR: This innovative conductor design utilizes an iron–nickel alloy core (36–38% Ni, Invar) with either galvanized or aluminum-clad protection for enhanced durability and minimal thermal expansion. The core is surrounded by specialized aluminum-zirconium alloy outer strands that provide exceptional thermal stability. This unique combination of materials enables stable operation at temperatures reaching 200 °C while maintaining structural integrity. The conductor’s superior thermal performance and increased current-carrying capacity make it particularly valuable for power grid upgrades and efficiency enhancement projects in high-demand electrical networks [177].
(C) ACCC: The ACCC conductor features a core made of carbon fiber or composite material instead of traditional steel. This composite core significantly reduces the conductor’s weight while providing superior tensile strength. As a result, ACCC conductors exhibit lower sag, higher efficiency, and increased power transmission capacity. They can operate at temperatures up to 200 °C, making them ideal for long-span applications and environmentally sensitive areas where minimizing line losses is crucial [176,177].
(D) ACSS: This conductor consists of fully annealed aluminum (O-temper) wires with either circular or trapezoidal cross-sections. The steel core is either aluminum-clad or coated with a zinc and 5% aluminum–mischmetal alloy to improve corrosion resistance and thermal stability. The inclusion of mischmetal further enhances the conductor’s durability under high-temperature conditions. A key advantage of this conductor is its ability to sustain continuous operation at temperatures up to 250 °C without degradation of its mechanical properties. Its high-temperature tolerance makes it suitable for reconductoring projects where increased capacity is required without changing the existing infrastructure [177].
(E) GZTACSR: This conductor features a high-strength galvanized steel core with heat-resistant aluminum alloy outer strands, separated by a grease-filled gap. The grease inhibits galvanic corrosion and moisture penetration. Compared to similar-sized ACSR conductors, it achieves a 1.6–2 higher current capacity while maintaining thermal stability. The controlled sag characteristic of GZTACSR makes it advantageous for HV-TRLs where maintaining ground clearance is critical [177].
(F) INVAR: INVAR conductors are a specialized type of ACSS conductor that utilize a core made from INVAR steel, which is a nickel–iron alloy known for its minimal thermal expansion properties. This design enables the conductor to maintain consistent sag levels even at high operating temperatures. INVAR conductors can function efficiently at temperatures up to 210 °C, making them an excellent choice for transmission systems requiring stability under varying thermal conditions [177]. Table 12 summarizes the different characteristics of HTLS conductors.
Asorza et al. [179] conducted a detailed analysis on the feasibility of adopting HTLS conductors for future single-circuit overhead TRLs, comparing ACCC and ZTACIR with conventional AAAC conductors. Their study included electromechanical evaluations and ampacity calculations, finding that ACCC and ZTACIR significantly reduce mechanical loads and tower weight, with ACCC showing the lowest mechanical stress. The study recommends ACCC conductors for future projects due to their superior mechanical performance and comparable electrical characteristics, pending further economic assessment. HTLS conductors, such as ACCC and ACSS, enhance grid performance through minimized power losses and increased current-carrying capacity. These conductors employ advanced aluminum alloys and composite cores that reduce electrical resistance, thereby decreasing heat dissipation and improving transmission efficiency. Their ability to operate at elevated temperatures without significant sag further enables increased current-carrying capacity, maximizing power transfer while minimizing losses [124]. Another major advantage of HTLS conductors is their ability to maintain lower sag and improved clearance, even under high thermal loads. Sag in TRLs increases resistance and poses safety risks due to reduced ground clearance, potentially leading to power outages or faults. Conductors like GZTACSR and ACCC mitigate this issue by maintaining optimal line geometry, thus reducing resistive losses. Furthermore, HTLS conductors help reduce corona and dielectric losses, which occur when HV lines ionize the surrounding air, causing energy dissipation. Their optimized surface characteristics and reduced sag minimize corona discharge, particularly in extra HV and ultra-high-voltage networks, enhancing overall transmission efficiency [173,180]. Beyond efficiency improvements, HTLS conductors contribute to greater grid stability and reduced infrastructure costs. By operating at higher temperatures without losing mechanical integrity, they prevent thermal overload issues that can cause increased resistance and power losses. This ensures stable voltage profiles and reliable power delivery, even in heavily loaded grids. Additionally, their superior performance in terms of current capacity and thermal resistance allows utilities to upgrade existing TRLs without costly tower replacements or right-of-way expansions. This not only reduces capital investment but also minimizes energy losses associated with line reconstruction, making HTLS conductors a cost-effective and efficient solution for modernizing power transmission systems.
As the energy sector evolves, HTLS conductors will play a bigger role. They boost transmission capacity, increase efficiency, and help integrate renewable energy. This makes them essential for modernizing power grids. However, some challenges exist. HTLS conductors cost more upfront than conventional options. This can slow adoption. Utilities must also assess whether these conductors fit with existing infrastructure. Proper installation and maintenance are crucial to maximizing their benefits [126,181]. While the actual performance of these conductors is highly dependent on proper material selection, precise installation, and continuous maintenance, utilities should implement the following measures to achieve optimal loss reduction: (1) prioritize ACCC conductors with hybrid carbon–fiber cores for long spans requiring minimal sag, (2) implement real-time thermal monitoring (±0.5 °C accuracy), and (3) conduct annual ultrasonic inspections of composite cores and splices.

4.1.2. HTS Conductors

Superconductors have unique properties. They show zero electrical resistance and expel magnetic fields below a critical temperature (Tc). Many materials exhibit superconductivity [182]. Elements like mercury (Tc = 4.2 K), lead (7 K), aluminum (1.2 K), and niobium (9 K) are superconductors. Alloys such as NbTi (10 K) and Nb3Sn (18 K) are widely used. Nb3Ge (23 K) holds the highest Tc among LTSs. Organic superconductors include RbC60 (33 K), the highest in this group. Several compounds also exhibit superconductivity. Examples include MgB2 (40 K), FeSe (8 K), and doped LaO—FeAs oxypnictides (52 K). Some materials surpass 77 K, allowing for cooling with liquid nitrogen. These are cuprates, a special class of superconductors. Notable cuprates include YBa2Cu3O7 (“YBCO,” 93 K) and Bi2Sr2Ca2Cu3O10 (“BSCCO-2223,” 110 K). The highest Tc at ambient pressure belongs to HgBa2Ca2Cu3O8 (133 K). These are HTSs. Some also classify iron pnictides and MgB2 as HTSs [183].
Zero resistance in HTSs is crucial for improving power grid efficiency. It removes I 2 R losses, a major drawback of conventional systems. This breakthrough enhances energy transmission. However, superconductors are not entirely loss-free. ACs still cause some energy dissipation, though careful design can reduce these losses. Another factor is flux creep, which introduces a tiny voltage, even in DC operation. Fortunately, at liquid nitrogen temperatures, this effect is minimal. Despite these small losses, HTS still offers significant advantages, making it a game-changer for power applications [184].
HTS AC cables are the most advanced superconducting grid technology. Many successful tests have been conducted worldwide. The first fully commercial projects, without government funding, are expected soon. These cables resemble conventional underground cables but with key differences. They contain multiple HTS wires, an HV dielectric layer, an HTS screening layer, a flexible cryostat, and an outer jacket. Their structure is long and flexible, similar to a massive snake. They range from 6 to 10 inches in diameter and can extend up to a kilometer without joints [185,186].
Liquid nitrogen cools them through a closed-cycle refrigeration system at one or both ends. Special HV terminals connect the superconductor wires to copper leads and transition from cryogenic to room temperature. Designed for underground use, these cables link substations in cities and suburbs. Underground placement offers major benefits—protection from storms and attacks, less land disruption, and better aesthetics. Compared to standard cables, superconducting versions bring additional advantages in efficiency, capacity, and reliability [187]. In addition, superconductor cables have many advantages over conventional cables, which are listed in Table 13.
DC cables provide significant benefits beyond AC applications, particularly for transmitting large amounts of power over long distances. These cables are crucial for delivering renewable energy from remote sources to urban centers. A large-scale version of this concept, known as a supergrid, enhances grid reliability by allowing power to be shared across regions when local supply is disrupted.
The key advantage of HTS DC cables is their zero resistive loss, ensuring efficient power transmission. However, maintaining strong thermal insulation is essential to minimize heat losses. Like other underground cables, HTS DC cables require less right-of-way space, lowering land acquisition costs and avoiding visual pollution. Burying these cables also reduces public health concerns and makes them more resilient to extreme weather [192,193]. Despite these benefits, overhead AC and DC lines remain cost-effective due to their well-established technology. However, increasing public resistance to new overhead power lines, due to environmental and legal concerns, makes underground HTS DC cables an attractive alternative. A major challenge, however, is the massive wire requirement for long-distance projects, such as a 1000 km link. Expanding HTS wire production is necessary before such large-scale applications become practical.
HTS cables have evolved through three generations, each bringing advancements in material composition, performance, and cost-effectiveness. The 1st-Generation HTS cables utilize Bi-based (Bi-2223) superconductors and are fabricated using the PIT method, forming silver matrix tapes. While they offer a high critical temperature (~110 K), they suffer from limited critical current, high silver costs, mechanical fragility, and lower engineering current density. The 2nd-Generation HTS cables, made from YBCO (YBa2Cu3O7-δ), employ thin-film coated conductor technology with a metallic substrate, such as Hastelloy, and a superconducting YBCO layer. These cables demonstrate improved critical current density, enhanced mechanical strength, and reduced silver dependency, though their complex manufacturing processes still result in relatively high production costs. The emerging 3rd-Generation HTS cables, currently under development, focus on FeSC or MgB2, aiming for more cost-effective and simplified processing methods. They feature novel material compositions that eliminate expensive buffer layers, potentially offering lower costs, greater flexibility, and improved current capacity. However, 3G HTS cables are still under research and development, with commercial viability yet to be fully realized [194,195,196]. The cost of 3G HTS cables remains a critical barrier to their widespread commercialization, with commercial YBCO-coated conductors still priced at more than 60 USD per meter. This high cost is attributed to several interconnected factors including the intrinsic price of the superconducting material, the complexity and multi-step nature of coated conductor fabrication, the requirement for cryogenic cooling systems such as liquid nitrogen, and the persistent challenge of achieving high and consistent critical current density [189]. In addition, the overall conductor length required for a given application directly increases the cost burden [197]. Although significant progress has been achieved compared to earlier generations of HTS cables, further improvements in manufacturing efficiency and material performance remain essential to reduce costs and to enable broader deployment of HTS technologies in industrial-scale applications. Table 14 compares these three generations.
Until recently, only two research facilities were able to produce and test 2G HTS cables at full scale [198,199]. In a 2018 study, Yuan et al. [200] conducted the UK’s first feasibility investigation on HTS cables, comparing them with conventional solutions for electricity distribution capacity reinforcement. They found that HTS cables provide higher power density and require less land but are currently about 75 percent more expensive. Cost parity with conventional cables could be achieved in 5–10 years if superconducting material prices drop by 10 percent annually. HTS solutions are most advantageous in areas with severe space constraints despite present cost barriers. New strategies for HTS conductors are being developed to minimize AC losses efficiently. The helically wound CORT technique, originally designed for DC applications, is now being explored for AC use in MV underground cables [201]. Through three-dimensional simulations using the H-formulation of Maxwell’s equations, researchers have confirmed the complex current profiles in these conductors. The study highlights how parameters such as current, pitch angle, and frequency influence AC losses, revealing an optimal pitch angle and strong frequency-dependent current behavior [202].
One other effective approach is the division of the superconducting layer into parallel filaments, which significantly reduces hysteresis loss. Recent studies on round HTS cables made from coated conductor tapes have demonstrated that using filamentized REBCO layers, produced through an industrial process with a specially designed 3D patterned metal substrate, leads to substantial reductions in magnetization loss. Further research is needed to enhance the critical current and optimize metallic layers to facilitate current migration between filaments while minimizing coupling losses [203]. In addition, the preliminary design of Rfc using HTS Q-ISs has been evaluated through numerical simulations, demonstrating lower transport AC losses compared to directly stacked conductors. Additionally, the magnetization loss of Rfc made from Q-ISs is reduced within specific external field orientations. This approach, analyzed using the T-A formulation at 77 K, presents a promising solution for superconducting feeder lines and bus applications with a high current capacity. Further optimization of this design could lead to significant advancements in AC loss reduction [204]. One promising approach is gap optimization in non-twisted stacked HTS conductors, which helps reduce the anisotropic effects of magnetic fields that weaken critical current and increase AC losses. Finite element modeling has demonstrated that optimized gap arrangements significantly lower AC losses compared to directly stacked conductors. This method offers a simpler, more cost-effective, and robust design, making it a viable solution for high-current, large-scale HTS applications. Further exploration of this technique could enhance the efficiency and practicality of superconducting cable systems [205]. Generally, balancing cost and efficiency in HTS cables is crucial for optimizing modern power systems. By strategically designing HTS cables to reduce AC losses while considering material and manufacturing expenses, power grids can achieve high power transfer with minimal energy dissipation.

4.2. Voltage Optimization

Voltage optimization is a crucial technique for reducing TLs in power systems by regulating voltage levels. By maintaining optimal voltage levels, the efficiency of power T&D can be significantly enhanced. Several methods are employed for voltage optimization, including transformer tap changers, bus bar capacitors, and voltage regulators. These techniques not only minimize energy losses but also improve system stability and reliability [136]. Also, elevating the primary line voltage, through voltage upgrading or conversion, leads to a reduction in distribution system losses. Imran et al. [206] proposed replacing large three-phase transformers with multiple small single-phase units in rural networks, demonstrating 29% voltage improvement and 78% loss reduction in Iraq’s Nineveh network via ETAP simulations. While cost-effective (20-month payback), challenges include increased maintenance complexity, land acquisition for additional units, and potential phase imbalance risks in unbalanced loads.
One of the primary methods for voltage optimization is the use of transformer tap changers. These devices adjust the voltage ratio of transformers, enabling the optimization of voltage levels throughout the power system. By selecting the appropriate tap setting, the voltage supplied to various sections of the grid can be optimized, leading to a reduction in both fixed and variable losses [207,208]. Furthermore, tap changers can improve the voltage profile across the network, ensuring efficient power delivery with minimized losses. Recent advancements in tap changer technology, particularly on-load tap changers with enhanced control systems, have facilitated more precise and responsive voltage optimization. These innovations allow for real-time adjustments to tap settings, which can be fine-tuned based on dynamic system conditions. Studies have shown that improper tap settings can contribute to increased power dissipation and voltage imbalances, affecting overall system stability and efficiency. By optimizing tap-changing mechanisms, voltage regulation can be improved, leading to reduced losses and enhanced reliability.
Numerical simulations have proven effective in analyzing the impact of tap settings on power loss reduction. Numerical tools have been employed to model real-time load profiles, allowing for automated high-frequency simulations. These simulations enable the capture of dynamic system behavior and facilitate a comprehensive evaluation of optimal tap positions. Comparative analyses of fixed tap settings (e.g., 1.0 p.u.) versus optimized configurations highlight the potential for significant reductions in transmission losses through strategic tap adjustments [209,210].
Another critical challenge in voltage regulation arises in MV networks, especially those with radial topologies and increasing integration of DG units. The efficient coordination of these DG units is essential to minimizing both active power losses and reactive power consumption. In this context, nearly decentralized voltage regulation algorithms have emerged as a promising solution. These algorithms require minimal communication infrastructure and enable each DG unit to make independent decisions based on local and remote measurements. The integration of cooperative on-load tap changer control has been found to enhance this coordination, leading to a more stable voltage profile and further reducing network losses [211,212]. Numerous studies, including time-domain simulations, have validated the effectiveness of decentralized control schemes, demonstrating superior performance in terms of response time, robustness, and overall system efficiency compared to conventional methods [213].
Optimal control strategies traditionally focused on the optimization of shunt capacitor banks and under-load tap changers at HV and MV substations [214]. However, recent research has expanded these strategies to include the optimization of additional components such as tie-switches and capacitor banks located on the feeders of large, radially operated meshed distribution systems. Multi-objective heuristic optimization techniques, including fuzzy set theory, have been employed to address the complexities of these optimization problems. These methods have shown promise in minimizing power losses while flattening the voltage profile across the grid. The solution algorithm is presented in Figure 9. The optimization of grid components, as demonstrated in recent studies, provides a feasible solution for improving the overall performance of distribution networks [215].
Another method employed for voltage optimization is the use of bus bar capacitors, which are strategically placed to compensate for reactive power within the system. Capacitors reduce the overall current flowing through TRLs, thereby minimizing resistive losses. Since power losses are proportional to the square of the current, reducing the current flow significantly reduces power losses. In addition to minimizing losses, capacitors also improve voltage stability, enhance the power factor, and reduce the burden on other reactive power compensation devices. The use of dynamic capacitor banks, which can adjust their reactive power output in real-time, has gained attention as an innovative solution for more efficient voltage optimization. Also, distribution networks incur significant TLs, with reactive power contributing substantially to overall system inefficiencies. Strategic capacitor deployment addresses this through three key benefits: (1) reactive current compensation reduces I2R losses, (2) freed system capacity improves load handling, and (3) enhanced voltage profiles boost service quality.
Additionally, the allocation of capacitor banks has proven effective in minimizing losses in distribution networks, especially in HV systems. Reddy and Manoj [216] proposed a hybrid optimization method combining Fuzzy Logic for capacitor placement and the Bat Algorithm for sizing, achieving 78% loss reduction (from 14.73% to 3.21%) in 15/34-bus test systems. While effective, limitations include computational complexity of dual-stage optimization and sensitivity to input parameters in practical deployments. Reference [217] highlights the key benefits of capacitor bank utilization, including power flow control, loss minimization, voltage stability improvement, and power factor correction. Capacitors help reduce inductive reactance, leading to a decrease in reactive power losses. Early implementations saw capacitors installed at substations, but more recent trends favor placement near loads on primary feeders for more localized impact. The challenges of capacitor allocation, including selecting the optimal type, size, and placement of capacitors, are explored in [217]. That study also presents a loss minimization process, using a uniformly loaded primary feeder as an example, as shown in Figure 10.
Overall, voltage optimization plays a vital role in minimizing losses within power systems. While analytical models offer theoretical insights, real-world applications emphasize the importance of practical implementations. Future research should focus on integrating advanced AI techniques for predictive voltage control, which could further enhance the efficiency of voltage optimization strategies. Optimal implementation requires careful sizing and placement to avoid overcompensation. Table 15 provides a clearer comparison of the methods discussed in the article, highlighting their strengths, limitations, and references for further study.

4.3. Reactive Power Compensation

Load losses in distribution systems are proportional to the square of the line current, necessitating a reduction in the reactive component to improve the power factor and minimize TLs. Reactive power compensation, utilizing devices such as shunt compensators (SVCs and STATCOMs), synchronous condensers, and series compensators [23,222], is essential for enhancing voltage stability and reducing energy losses. Effective management of reactive power through these techniques can significantly decrease power losses and provide economic benefits for utility companies. Figure 11 illustrates the devices employed in reactive power compensation.

4.3.1. SVCs

SVCs are essential power electronic devices used for reactive power compensation, voltage stabilization, and power loss reduction in electrical grids. They consist of thyristor-controlled reactors and TSCs, which dynamically regulate the system’s reactive power demand. By reducing the reactive power demand from the source, SVCs help in minimizing the total current flowing through the TRLs. Since line losses are proportional to the square of the current ( R I 2 ), a reduction in reactive power leads to lower transmission losses. SVCs help in maintaining a stable voltage profile across the network by injecting or absorbing reactive power as required. This prevents over-voltage and under-voltage conditions, which can lead to increased power losses and reduced efficiency of electrical equipment. A poor power factor leads to higher apparent power (S = P + jQ), increasing losses in generators, transformers, and TRLs. SVCs improve the power factor by dynamically adjusting the reactive power, thereby reducing the overall burden on the system and minimizing losses [223,224,225]. Optimal SVC operation requires precise thyristor firing angle control to maintain voltage profiles within permissible limits while minimizing switching losses. Advanced designs incorporating integrated harmonic filters significantly mitigate resistive losses associated with harmonic distortion. Dynamic coordination with other voltage regulation devices via phasor measurement-based control algorithms optimizes circulating reactive currents. To maximize system-wide benefits, SVCs should implement adaptive impedance matching to maintain network resonance stability during transient conditions.
The study by Saleh et al. [226] investigates the integration of an SVC and DG within an IEEE 33-bus distribution network using PSS/E 34 software, aiming to enhance voltage stability and reduce power losses. By evaluating scenarios both with and without a DG and determining the optimal locations for the SVC and DG using voltage stability margin and voltage stability index methods, the authors demonstrated that the combined application of an SVC and DG provides the most significant improvements in voltage profile and power loss reduction. A comparative analysis of the system’s key performance metrics is presented in Table 16, demonstrating the reduction in power losses.
Reference [227] examines the use of SVCs in improving the power distribution network of Ado-Ekiti, Nigeria. It found that without SVCs, some distribution lines were overloaded, and voltage levels were outside the acceptable range. By incorporating SVCs, active power loss was reduced by 9.73%, and the network’s voltage stability improved, increasing its capacity from 150% to 263% of the active load. The study highlighted the benefits of using SVCs to enhance network efficiency and reduce losses [227]. This comprehensive modeling and simulation of the 11 kV distribution network in Ado-Ekiti was conducted by inputting the collected data into an advanced computer-aided analysis tool, NEPLAN software. The research process is illustrated in the systematic flowchart presented in Figure 12.

4.3.2. STATCOM

STATCOMs belong to the family of FACTS devices, designed primarily to deliver rapid, precise, and controllable reactive power support to the AC power network they are connected to. They achieve this by adjusting both the magnitude and phase angle of the reactive current exchanged with the grid. Through this mechanism, STATCOMs effectively regulate the volume and direction of reactive power flow within the system [228]. FACTS devices significantly reduce TLs in power systems by dynamically optimizing reactive power flow and voltage stability. STATCOMs and SVCs inject/absorb reactive power at strategic nodes to minimize I2R losses caused by reactive current flow, particularly in long transmission corridors. TCSCs modulate line impedance to relieve congestion and redirect power from overloaded paths to underutilized lines with lower resistance. By maintaining voltages within ±1% of nominal values, FACTS devices reduce current magnitude for constant active power transfer, directly lowering Joule losses. Unlike conventional switches, FACTS enables real-time adaptive control—critical for loss minimization under variable loading without compromising transient stability. A common application of STATCOMs is dynamic power factor correction, particularly in industrial setups where equipment demands fluctuating levels of reactive power. By enhancing the power factor, stabilizing input voltage fluctuations, and safeguarding machinery from potential damage, STATCOMs help optimize plant operations and reduce operational expenses. Additionally, they serve as voltage support devices at the receiving end of AC TRLs [229]. Figure 13 illustrates a single-machine infinite bus system incorporating a STATCOM positioned at the midpoint of a TRL.

4.3.3. Synchronous Condensers

A synchronous condenser is a machine resembling a synchronous motor but without mechanical load. It is used to regulate voltage and improve power factor in electrical grids by supplying or absorbing reactive power. Historically essential before power electronics-based solutions, these devices have been utilized since the 1920s to enhance grid stability at both T&D levels. However, their use has declined due to high costs, large infrastructure requirements, and inefficiencies compared to modern static compensators. Despite these drawbacks, synchronous condensers remain valuable for their overload capacity and ability to support voltage stability, particularly in industrial applications and hybrid renewable energy systems. They continue to be deployed worldwide to optimize energy resource utilization and ensure a reliable, sustainable power supply [230]. Synchronous condensers can absorb or generate reactive power based on system requirements. This reduces the reactive power burden on TRLs and transformers, lowering resistive losses in the system. By injecting reactive power when voltage drops and absorbing reactive power when voltage rises, synchronous condensers help maintain a stable voltage profile, preventing excessive current flow and associated losses. Since synchronous condensers have a rotating mass, they contribute to system inertia, improving transient stability and reducing frequency deviations in the network. This is particularly beneficial in grids with high renewable energy penetration, where fluctuations in power generation can cause losses due to frequency instability [231]. Advanced implementations now feature hybrid configurations combining synchronous condensers with fast static compensators to mitigate the condenser’s no-load losses while preserving grid-forming capabilities. Cutting-edge adaptive control systems utilizing phasor measurements enable precise voltage regulation during transients, significantly reducing associated resistive losses. Emerging solutions incorporate superconducting rotating elements to dramatically decrease rotational losses while maintaining critical inertia properties. The condenser’s ability to provide sustained reactive power during prolonged undervoltage conditions proves invaluable for maintaining system efficiency. Figure 14 illustrates a single-phase configuration incorporating a synchronous condenser.

4.3.4. Series Compensators

Series compensators, such as the SSSC, TCSC, and TSSC, play a critical role in reducing power losses and enhancing the efficiency of power transmission networks. These devices improve voltage stability, mitigate TRL congestion, and optimize power flow by injecting a controllable series voltage into the system. The SSSC, as a voltage source converter-based device, provides dynamic series compensation by generating both capacitive and inductive voltage compensation, thus improving power transfer capability and minimizing losses. In contrast, TCSC and TSSC employ thyristor-controlled and switched capacitor arrangements, respectively, to adjust the effective impedance of the TRL. By dynamically modulating the line reactance, these compensators alleviate power oscillations, enhance transient stability, and improve voltage regulation. The deployment of these series compensators not only reduces transmission losses but also enhances the reliability and flexibility of modern power systems, making them indispensable for efficient power delivery in large-scale networks [232]. The placement of the SSSC is a critical factor in maximizing its ability to enhance power system performance. Ideally, the SSSC should be installed in series with either the weakest bus or the TRL exhibiting the highest underutilization. To identify these locations, a continuous power flow analysis is conducted, assessing system performance without the SSSC. The weakest bus is determined based on voltage profile analysis, where the bus experiencing the most significant voltage collapse is selected. Similarly, the TRL with the lowest power utilization, relative to its total capacity, is identified as the optimal candidate for series compensation [233]. Functionally, the SSSC is connected in series with a TRL, consisting of key components such as a coupling transformer, voltage source converters, a DC capacitor, and a magnetic interface. The coupling transformer introduces a voltage in quadrature with the line current, enabling the SSSC to function as a synchronous voltage source. By injecting a controllable series voltage, the device effectively modifies TRL impedance, operating in either capacitive or inductive mode based on the phase relationship between the injected voltage and the line current. This capability allows the SSSC to dynamically regulate reactive power, enhance voltage stability, and optimize power flow. Additionally, an SSSC equipped with an energy storage system can facilitate active power exchange with the grid.

4.3.5. Comparison with Other Compensation Techniques

OYIOGU et al. [234] highlighted that power system stability requires maintaining equilibrium during disturbances, with voltage instability often caused by reactive power imbalance. They analyzed the impact of FACTS devices on voltage stability and power loss reduction. Simulations using NEPLAN Engineering indicated that FACTS controllers effectively enhance voltage stability and reduce losses in power networks. Also, Saha et al. [235] investigated voltage stability enhancement and power transfer improvement using fixed capacitors, SVCs, and STATCOMs in a simulated transmission system. Their results showed that while all devices improved power flow and voltage profiles, STATCOMs provide the most effective compensation and voltage regulation when properly rated. While FACTS devices offer notable technical benefits for power grids, high initial installation and lifetime operation costs (along with spatial and time constraints) can limit their adoption. Cost structure typically includes equipment, engineering, civil works, installation, and maintenance, with annual costs around 5–10% of initial investment. Exact costs vary widely due to factors like device type, rating, voltage, and system requirements, making precise estimation challenging. Figure 15 shows a comparison of active and reactive power loss reduction achieved by different FACTS controllers. Figure 16 shows the cost breakdown for capacitor banks versus FACTS devices, underlining the financial impact of adopting advanced grid technologies.
Table 17 highlights the key characteristics of various reactive power compensation methods, categorized into shunt compensators, series compensators, and shunt reactors. Shunt compensators, including SVCs, STATCOMs and synchronous condensers, are primarily used for voltage regulation and dynamic reactive power compensation. While SVCs and STATCOMs offer fast response times, STATCOMs have superior low-voltage performance due to their voltage source converter-based design. Synchronous condensers, on the other hand, provide additional inertia support but suffer from high operational costs. Series compensators, such as the SSSC, TCSC, and TSSC, enhance transmission efficiency by adjusting line reactance and controlling power flow. These devices are particularly effective in improving system stability and reducing transmission losses, though they are more complex and costly than shunt compensators. Finally, shunt reactors provide a passive means of reactive power absorption, preventing over-voltage issues in long TRLs under light load conditions. However, they do not supply reactive power, making them suitable only for specific scenarios. Overall, selecting the appropriate compensation method depends on system requirements, cost considerations, and the level of control needed for reactive power management.

4.4. Smart Grid Technologies

Smart grid technologies, such as advanced sensors, real-time monitoring, and automated control systems, can significantly reduce TLs in power systems. These technologies enable the optimization of power flow, load balancing, and fault detection, leading to more efficient and reliable power distribution [241]. Table 18 provides an unusual categorization of sensors based on their impact on voltage stability rather than their conventional functions.
As seen in Table 17, some sensors have an unexpectedly high impact on voltage stability, although their primary function may not necessarily be related to it.
Sensors play a crucial role in mitigating losses in power systems by addressing both technical and non-technical challenges. They help detect energy loss caused by resistance, aging infrastructure, and equipment inefficiencies, thereby reducing TLs. Additionally, they minimize NTLs by preventing energy theft and unauthorized connections. By optimizing energy distribution based on real-time consumption data, sensors improve demand response and enhance overall grid efficiency. Their ability to identify potential failures before they occur supports predictive maintenance, reducing repair costs and preventing unexpected breakdowns. Moreover, sensors enable faster fault restoration by quickly locating and isolating faults, minimizing downtime, and ensuring a more reliable power supply. Table 19 maps automated control systems to unrelated attributes, such as their potential for reducing administrative workload. Automated control systems in smart grids improve efficiency, reliability, and security while reducing energy losses. These systems use advanced sensors, real-time data processing, and AI-driven decision-making to optimize energy distribution [242,243].
Interestingly, Table 19 suggests that demand response systems reduce administrative workload the most, which may or may not align with expectations. Automated control systems are essential for minimizing energy losses by optimizing power distribution and reducing waste in transmission networks. They contribute to grid stability by mitigating voltage fluctuations and preventing blackouts, ensuring a more dependable electricity supply. Moreover, these systems enhance fault detection and recovery by rapidly isolating faults, allowing for quicker power restoration. By continuously adjusting the balance between supply and demand, they improve energy consumption efficiency and reduce unnecessary losses. Additionally, automating grid management processes boosts overall system performance by minimizing human errors and enhancing operational reliability. Finally, Table 20 illustrates fault detection systems in a way that compares their speed.
Fault detection systems mitigate losses by preventing energy wastage through the rapid identification of faulty components, thereby reducing TLs. In conclusion, while these tables may not align with conventional classifications, they highlight the interconnected nature of smart grid technologies in unexpected ways.

Impact of DERs and Role of Load Forecasting

DERs reduce losses by generating power near demand centers. Optimal DER placement and sizing enhance voltage stability and minimize losses. Forecasting of load and distributed generation has been shown in many simulation studies to facilitate TL reduction [14]. Agüero [23] highlights the importance of optimizing DG sizing and placement to maximize their effectiveness in reducing TLs.
Traditional modeling approaches include empirical formulas (e.g., I2R), analytical methods (e.g., load flow analysis), and statistical regression [244]. However, advanced techniques such as machine learning (support vector machines, decision trees) and optimization algorithms have improved loss prediction accuracy by capturing non-linear relationships and optimizing grid parameters [245,246]. More generally, deep learning models have been proposed to predict losses directly from forecasted conditions. For instance, Blinov et al. [42] applied deep neural networks to predict nodal loads and compute losses; by recalculating line flows on forecasted loads, their scheme could reflect topology changes and proactively steer power flows, thereby reducing operational losses. Forecasting renewable outputs and co-scheduling storage yields similar loss-saving benefits. Loss allocation methods vary in complexity, from simple pro rata approaches to more refined techniques like distance-adjusted pro rata, which incorporates line length but ignores power flow non-linearity [247,248]. The incremental loss method evaluates losses from new grid additions using Newton–Raphson linearization, though high X/R ratio networks complicate its application [249,250]. Kebir and Maaroufi [251] developed an algorithm for an MV feeder with a PV and battery, where day-ahead forecasts of load and PV generation are inputs to the control. Network analysis methods (Z-bus, Y-bus) and power tracing algorithms provide systematic loss quantification but may require normalization for accuracy [252,253,254].
Auchoa et al. [255] demonstrated that phase imbalance in distribution systems elevates TLs and causes voltage deviations, potentially damaging equipment. While mitigation requires load balancing, the associated costs remain low, primarily involving metering and manual phase adjustments. Accurate forecasting of both electrical load and renewable generation has become indispensable for modern power system planning and operation. Forecasts of demand and intermittent supply allow grid operators to schedule generation, reserves, and flexibility ahead of time so that supply matches demand with minimum waste. In particular, high-resolution load and DER forecasts enable system operators to anticipate fluctuations and proactively adjust dispatch or control devices. Recent reviews emphasize that precise renewable forecasts are critical for optimizing grid operations and managing energy flows [256]. In practice, accurate forecasts help avoid unnecessary generator commitments or reserves (which would create extra power flows and losses) and prevent under-generation (which can force high-loss emergency dispatch).
Additionality, smart grid control modules such as DERMS and DR platforms actively minimize inherent TLs (conductor and transformer I2R losses) in T&D networks. By coordinating distributed generation and flexible loads, these systems flatten load–generation profiles and optimize power flows. In practice, integrating DER dispatch with demand-side management has been shown to overcome distribution network losses by better balancing supply and demand; in other words, DERMSs adjust local generation and reactive support while DR programs shape the load curve to minimize high-current conditions [14]. Within a smart grid framework, these modules jointly regulate voltage, feeder loading, and network topology to reduce losses. For instance, advanced DERMSs (often embedded in an ADMS) implement adaptive Volt/VAR control and dynamic reconfiguration to keep voltages within limits while shaving resistive losses [257]. Simultaneously, DR mechanisms shift or curtail loads from congested feeders or peak hours, lowering line currents and transformer stress. Case studies confirm the effectiveness of this coordination: one analysis found that enabling flexible demand at ~30% of the load reduced network losses by roughly 14.5% and significantly tightened voltage deviation indices [258]. Crucially, DEMS and DR modules operate in real time, using high-speed measurements and controls to continuously balance the grid. Modern ADMS platforms provide full visibility of the distribution network for accurate loss detection and voltage optimization and coordinate DER inverters, tap changers, and DR signals as needed [257]. For example, under-voltage conditions detected by a DERMS might trigger either reactive injection from local inverters or automated demand curtailment to rebalance flows. Studies of such closed-loop schemes highlight their impact: one recent optimization reported a ~42.6% reduction in distribution losses through strategic DR deployment, echoing the conclusion that DR is pivotal in reducing power losses and mitigating voltage deviations. In summary, the tight integration of distributed resource management and demand response creates a feedback control system that continuously balances load and generation, optimizes voltage profiles, and relieves line and transformer loading, all of which systematically reduce TLs across transmission and distribution networks [259].
TLs—the unavoidable I2R losses in T&D lines and transformers—depend directly on the magnitude and pattern of power flows. Because flows are driven by the net difference between generation and demand at each node, forecast errors can indirectly inflate losses. For example, if a load surge or drop is not anticipated (due to forecasting error), operators may run extra generators or rapidly ramp others, leading to suboptimal power flows and higher I2R losses. Likewise, in a distribution feeder with high PV penetration, poor solar forecasts can cause unplanned reverse flows or voltage swings, raising losses. To address this, some studies explicitly incorporate forecasts into loss management. Reference [251] proposed adjusting demand forecasts and ensuring reliable PV output prediction as part of an optimal control strategy—this allows us to underpin the forecast accuracy results in grid-connected distributed generation systems. Similarly, predictive analytics can use short-term forecasts to identify high-loss network segments: forecasting transmission losses helps dispatchers plan load flows for longer-term design improvements [260]. In short, by incorporating accurate load/PV/wind forecasts into operational planning (e.g., Volt-Var control, storage dispatch, network reconfiguration), system operators can reduce unnecessary flows and thus trim TLs. Overall, the literature concurs that better forecasting, especially for variable renewables, allows the system to operate closer to optimal power flows (lower currents and voltages) and thus reduce I2R losses.

4.5. Regular Maintenance and Inspection

Regular maintenance and inspection of T&D infrastructure—including conductors, insulators, transformers, and associated components—are essential for minimizing TLs and ensuring grid reliability. Proactive maintenance enhances energy efficiency by reducing resistive losses, leakage currents, and core losses while preventing premature equipment failure.

4.5.1. Conductor Maintenance for Resistive Loss Reduction

Conductors are critical components whose degradation directly impacts resistive losses. Overloaded conductors experience increased resistance due to heating, making thermal monitoring through infrared thermography and real-time current sensors crucial for detecting hotspots and enabling timely load adjustments. Exposure to moisture, chemicals, and pollution accelerates oxidation, particularly in aluminum and steel-reinforced conductors, necessitating regular inspections and anti-corrosive coatings such as grease or polymer-based solutions. Mechanical integrity checks, including tension measurements and visual inspections, help identify issues like sagging, fraying, or broken strands, which can increase resistance and failure risks [177].

4.5.2. Insulator Maintenance to Minimize Leakage Currents

Pollution and humidity significantly impact all electrical distribution network equipment, making them critical factors in selecting the appropriate insulators. This issue is particularly pronounced in coastal and desert regions, where fine dust, high humidity, and industrial pollutants are prevalent [261]. The accumulation of these contaminants on electrical equipment, combined with high humidity, can lead to electrical arcing in insulation components, such as insulators and overhead distribution substations, causing power outages [262,263]. In addition, the adoption of composite insulators featuring hydrophobic polymeric housings has proven effective in mitigating pollution-related flashovers, as their surface properties limit contaminant adhesion and facilitate self-cleaning under wet conditions [264]. Scheduled cleaning using high-pressure water jets or specialized chemical agents maintains surface resistivity and prevents flashovers. Studies, such as one conducted in India, demonstrate that systematic insulator cleaning reduces leakage current losses by 30–50% [265]. Without proper maintenance, contaminated insulators can lead to partial discharges, accelerating equipment failure and increasing system losses. Hence, timely network cleaning, adhering to established cleaning protocols, and rectifying identified defects are vital steps that enhance network reliability and ensure high operational stability. Furthermore, these proactive measures directly contribute to the reduction in TLs within the grid. By maintaining the integrity of insulators and other critical components, the likelihood of current leakage and the ensuing energy losses are markedly minimized. This optimized performance leads to a more efficient distribution of power, thereby realizing a demonstrable reduction in TLs.

4.5.3. Impact of Loose Joints, Maintenance, and Self-Supporting Cables

Loose electrical connections in power distribution systems are a significant source of TLs. Increased contact resistance at these points leads to localized heating and energy dissipation, contributing to elevated I2R losses. This phenomenon can also accelerate the thermal degradation of conductors and connectors, further reducing system efficiency and lifespan. Furthermore, loose connections often result in arcing and intermittent faults, introducing harmonic distortions and transient losses that degrade power quality [266]. One potential mitigation strategy involves the use of self-supporting cables, such as ABC. These cables reduce the number of required mechanical joints and provide enhanced insulation against environmental factors. By minimizing contact resistance and reducing the likelihood of faults, ABC cables can contribute to a significant reduction in TLs. Given the strong influence of the network’s physical condition on TLs, proper installation techniques, regular maintenance schedules, and the strategic adoption of self-supporting cables are crucial. These measures can substantially reduce losses, improve the overall reliability, and enhance the economic performance of power distribution systems.

4.5.4. Replacing Old Transformer and Maintenance for Core and Resistive Loss Mitigation

Transformer losses contribute significantly to overall utility losses, with studies showing that they can account for a substantial portion of distribution system losses; replacing old, inefficient transformers and optimizing transformer loading through AMIs systems can yield significant energy savings [23]. Regular inspection and maintenance of connections to transformer bushings, fuses, isolators, and LT switches are crucial to ensure proper contact pressure. Effective maintenance practices include monitoring oil levels to prevent insulation breakdown and overheating, as well as ensuring proper cooling system function through oil circulation and radiator maintenance. Insulation integrity testing, such as dissolved gas analysis and infrared thermography, helps detect early signs of winding degradation. A case study in a 400 kV South African transmission network demonstrated that implementing a structured transformer maintenance program reduced TLs by 20%, highlighting the importance of systematic upkeep for efficiency and longevity [136]. Kundu et al. [267] introduced a technique for reducing TLs, referred to as active repair. This method focuses exclusively on compensating the winding without altering the core structure. The loss reduction from a single distribution transformer may appear minimal, but cumulative savings from a large group of transformers over a 20-year lifespan are substantial.

5. Environmental Impacts of TLs and Real-World Efforts to Reduce TLs for Sustainability

TLs in power systems represent a substantial economic challenge, with global estimates indicating annual losses amounting to billions of dollars in wasted revenue. For utilities, reducing these losses directly enhances profitability by decreasing the need for additional generation capacity and lowering operational costs [268]. In developing nations, where infrastructure inefficiencies often result in TLs exceeding 15% of total generation, effective loss reduction strategies can significantly enhance energy affordability at the macroeconomic level. This improvement fosters industrial competitiveness and stimulates economic growth while alleviating the financial burden on end consumers. A notable example is found in pre-reform Central America (pre-2000), where governments implemented substantial power sector subsidies to offset distribution losses that consistently exceeded 30% of generated electricity [269]. From an environmental perspective, TLs exacerbate carbon emissions by necessitating surplus fossil fuel-based generation to compensate for wasted energy. The need to generate more electricity to compensate for losses leads to increased consumption of natural resources. Unfortunately, the reserves of these fuels are depleting, and they are expected to become prohibitively expensive soon. Additionally, the process of generating power from fossil fuels releases harmful gases and particulates, leading to substantial and long-lasting environmental damage [270]. Specifically, the study identified power TRL losses as a notable source of these substantial greenhouse gas emissions within the electricity generation domain [271]. The study examined the ecological performance of the Norwegian transmission grid, Sentralnett, and found that the transmission of 1 kWh through this network results in emissions ranging from 1.3 to 1.5 g CO2 eq. [272]. In regions heavily reliant on coal-fired power plants, such as parts of Asia and Africa, loss reduction initiatives can significantly curb PM2.5 and SO2 emissions, improving air quality and public health.
Furthermore, minimizing losses aligns with global climate targets, as it reduces the need for incremental generation capacity and supports the integration of variable renewable energy sources by optimizing existing grid infrastructure. The economic benefits of loss reduction extend beyond direct cost savings. Considering current pricing trends, the economic burden of TLs often outweighs the capital expenditure needed to minimize them to their economically optimal level, particularly in systems with substantial fossil fuel-based generation [269]. For policymakers, investing in loss mitigation offers a dual advantage: it delays costly grid expansions while creating green jobs in the manufacturing, installation, and maintenance of advanced power technologies. With growing electricity demand and increasing renewable energy integration, modern grid technologies and strategic interventions are being implemented across different regions to enhance efficiency. These initiatives employ advanced solutions such as smart grid technologies, HVDC transmission, real-time monitoring systems, and DG to minimize losses. However, barriers persist—high upfront costs for HTLS conductors, a lack of standardized loss assessment tools, and uneven regional adoption. Across the Mediterranean region, a combination of technical and operational interventions has been implemented to mitigate TLs in transmission and distribution networks. Predominant measures include network reconfiguration, replacement and upgrading of transformer fleets, and upsizing or replacement of aged conductors and cables to reduce resistive losses. For example, Bosnia and Herzegovina prioritized network reconfiguration and transformer modernization, while Egypt pursued cable and transformer capacity upgrades, shortened feeder lengths through new connection points, increased MV ratings, and efforts to mitigate load imbalance. In several jurisdictions (notably Italy and Portugal), performance-linked incentive schemes that reward or penalize distribution system operators based on deviation from target loss levels have been adopted; other countries (for instance Cyprus and France) have emphasized improvements in loss calculation accuracy and enhanced operational tools (SCADA/DMS) to optimize network operation [165].
Digitalization and process improvements have further supported loss reduction efforts. Albania’s targeted investments in smart and electronic metering, CRM/billing systems, field workforce management, and energy inflow monitoring have measurably improved network performance indicators and reduced TLs. Parallel initiatives such as France’s Linky rollout, which produced ancillary technical loss benefits despite its primary focus on NTLs, illustrate the cross-cutting effects of advanced metering and data-driven asset management. Countries facing structural challenges, such as Lebanon, are pursuing comprehensive strategies that combine voltage-level standardization, transformer efficiency upgrades, reactive power management, and increased penetration of distributed renewables to reduce long-distance power transfers. Overall, the regional experience indicates that an integrated approach combining infrastructure renewal, regulatory incentive mechanisms, grid reconfiguration, and digital-enabled monitoring and control is most effective for sustainably reducing TLs [165].
Table 21 summarizes key projects from various countries, demonstrating measurable success in loss reduction while improving grid reliability and sustainability. Ultimately, the fight against TLs is a linchpin for achieving SDG 7 (Affordable and Clean Energy) and SDG 13 (Climate Action). Future research must prioritize scalable, context-specific solutions—such as decentralized renewable microgrids in rural areas and superconducting urban networks—to maximize these dual benefits while ensuring equitable energy access worldwide.

6. Future Research Directions and Discussion

Despite advancements in TL mitigation, critical gaps persist. The future of power systems, as envisioned by current research, necessitates a significant reduction in TLs to meet sustainability goals and accommodate rising electricity demands. Advancements in materials science will play a crucial role, with a focus on developing conductors with ultra-low resistance, potentially leveraging nanomaterials and HTSs for T&D networks. Hydrophobic conductor coatings and self-healing insulation further minimize corona and leakage currents. Despite their potential, scalability and cost barriers persist, particularly for HTS and nanocrystalline materials, necessitating further research into room-temperature superconductors and durable nanocomposites. Future work should prioritize quantitative benchmarking of these materials’ performance under real-world grid conditions, including long-term durability studies and standardized testing protocols. With increasing energy challenges, especially during hot summer days, thermal metamaterials have emerged as a promising solution for advanced energy management. Developed through nanotechnology and artificial intelligence, these materials can direct heat flow in unique ways and serve as efficient thermal insulators, potentially reducing energy consumption by up to 30%. Artificial intelligence significantly accelerates the design and optimization process, while IoT technology allows for real-time, adaptive control of thermal behavior. Although current production costs are relatively high (200–500 USD/m2), prices are expected to decrease substantially as commercialization and mass production progress, enabling broader adoption within the next seven years. Also, future work must address scalability across diverse grid topologies [280] and dynamic loss optimization in modernized grids [26]. Furthermore, the integration of smart grid technologies, enhanced by AI, will enable real-time monitoring, predictive maintenance, and optimized power flow, leading to significant reductions in fixed and variable losses. The convergence of these technologies will allow for adaptive grid management that responds dynamically to environmental factors and operational conditions. Looking ahead, the transition towards hybrid AC/DC grids and the widespread adoption of DERs, including microgrids, will further reshape the landscape. Research will concentrate on the cost-effective integration of these elements while also focusing on robust cybersecurity measures to protect these increasingly complex systems from cyber–physical attacks. Incentives for utilities, standardization of best practices, and global collaboration are essential to accelerate the adoption of loss mitigation strategies. Regulatory policies play a pivotal role in mitigating TLs by creating economic incentives for utilities to enhance network efficiency and imposing penalties for excessive losses. These policies typically combine the establishment of explicit performance targets, the implementation of incentive mechanisms, and the promotion of advanced technology deployment [166]. Key approaches include PBR, which links predetermined TL reduction targets to financial rewards or sanctions, thereby aligning network efficiency with utility profitability; incentives linked to performance indicators such as loss levels, voltage regulation, or reliability indices; and technology-enabling regulations that foster the adoption of innovations such as smart grids, energy storage systems, and high-efficiency equipment. Regulatory frameworks may also leverage tariff structure reforms—including time-of-use pricing and demand-side management programs—to promote efficient consumption patterns, while mandatory transparency and reporting requirements hold utilities publicly accountable for loss performance data, root cause analyses, and corrective measures. Notable examples include MedReg’s [166] recommendations for benchmarking and loss reduction, CEER’s [152] survey-based findings on regulatory practices, and UK Power Networks’ [281] successful application of larger conductor sizing and advanced technological solutions, all demonstrating measurable efficiency gains.
However, despite their documented benefits, existing regulatory frameworks for TL reduction present several shortcomings. In many jurisdictions, PBR mechanisms are either absent or only partially implemented, often due to limited metering infrastructure, inconsistent data quality, or weak monitoring systems. Technology adoption remains constrained in developing economies due to high upfront capital costs, unclear legal provisions, or insufficient cost recovery mechanisms. Additionally, the short-term profitability goals of some distribution companies can conflict with long-term network efficiency objectives, reducing incentive alignment. Looking ahead, emerging challenges such as the large-scale integration of distributed renewable energy resources, the proliferation of electric vehicle charging infrastructure, cybersecurity risks in smart grids, and economic pressures from the clean energy transition will test the resilience and adaptability of current regulatory models. Addressing these issues will require more dynamic, data-driven regulatory mechanisms, coordinate investment planning, and strengthened enforcement to ensure sustained progress in TL reduction. Additionally, many mitigation strategies have been validated primarily through simulations, small-scale pilots, or geographically specific case studies, which restrict their applicability to broader and more diverse grid conditions. Furthermore, inconsistencies in TL quantification methodologies, variations in load flow modeling approaches, and incomplete operational datasets reported in the literature hinder reliable cross-technology comparisons. Economic assessments also tend to overlook lifecycle cost analyses, long-term performance degradation, and the challenges of integrating new measures with existing infrastructure. Addressing these issues will require coordinated efforts toward large-scale and longitudinal field validation across a wide range of operational contexts, the establishment of standardized methodologies for loss quantification and modeling, the development of comprehensive and high-resolution datasets, and the incorporation of holistic economic models that account for lifecycle and interoperability considerations. Future research could build upon these foundations by conducting cross-regional empirical studies, integrating physics-based and data-driven modeling to enhance predictive accuracy, formalizing global benchmarking protocols, examining the interface of mitigation measures with smart grids and renewable integration, and extending cost assessments to include environmental and sustainability impacts over the entire asset lifecycle. As illustrated in Table 22, a substantial variation exists in the maturity level and commercialization status among the available TL mitigation strategies. Technologies such as HTLS conductors, voltage optimization, and reactive power compensation exhibit high Technology Readiness Levels and have already achieved widespread deployment in many countries. In contrast, emerging solutions such as third-generation HTSs or hybrid AC/DC grids remain at pre-commercial or demonstration stages and still face challenges related to cost, operational stability, and infrastructure compatibility. This classification enables network operators and policymakers to identify readily deployable solutions while strategically planning the development trajectory of emerging technologies. Also, to provide a structured comparison of various TL mitigation approaches, Table 23 summarizes key technologies, their working principles, advantages, limitations, cost implications, and typical applications. This comprehensive overview facilitates informed decision-making for grid operators, planners, and researchers seeking to optimize T&D efficiency.

7. Conclusions

TLs in power systems represent a significant challenge to global energy efficiency, economic viability, and environmental sustainability. This review has systematically examined the mechanisms of TLs—categorized into fixed and variable losses—and evaluated cutting-edge mitigation strategies, including advanced conductor (e.g., HTLS and HTS), voltage optimization, reactive power compensation, and smart grid technologies. While these innovations demonstrate substantial potential for loss reduction, their widespread adoption faces barriers such as high upfront costs, infrastructural limitations, and cybersecurity risks in smart grids. From an engineering standpoint, the adoption of TL mitigation techniques must be evaluated not only in terms of loss reduction potential but also in terms of commercial readiness and implementation feasibility. Mature and widely deployed technologies include transformer core loss reduction using amorphous metal alloys, reactive power compensation through shunt capacitor banks, SVCs, STATCOMs, and DLR systems for optimizing conductor utilization. These solutions are already integrated into commercial services such as high-efficiency power transformers, DSM programs, and advanced distribution network operation platforms. In contrast, several promising solutions remain at the research or pilot stage, including HTS cables, hybrid AC/DC grid topologies, and AI-driven predictive maintenance for early fault detection. Clarifying this distinction enables utility operators, policymakers, and technology providers to align investment and R&D priorities, ensuring that loss reduction strategies deliver both immediate operational benefits and long-term innovation pathways.
To provide a clear implementation strategy for TL reduction across power systems, Table 24 presents a phased roadmap categorizing solutions for T&D networks across short-term, medium-term, and long-term horizons. This structured approach enables utilities and system operators to prioritize interventions based on implementation complexity, cost considerations, and expected impact.
Key Recommendations for Policymakers and Stakeholders:
  • Prioritize infrastructure modernization:
    Focus on replacing aging transformers and conductors in developing grids with high-efficiency alternatives (e.g., amorphous metal core transformers, ACCC conductors) to achieve loss reductions.
    Implement regulatory incentives (e.g., subsidies, tax breaks) for utilities to adopt HTLS and HTS technologies.
  • Enforce standardized loss assessment protocols:
    Develop unified methodologies for TL quantification to address inconsistencies in load flow techniques and high-frequency loss contributions.
    Mandate real-time monitoring systems to enable data-driven decision-making.
  • Integrate smart grids with cybersecurity safeguards:
    Accelerate deployment of AI-driven predictive maintenance and DLR systems while investing in robust cybersecurity frameworks to protect grid integrity.
  • Promote hybrid AC/DC grids for renewable integration:
    Support pilot projects for HVDC transmission and decentralized microgrids to minimize losses in long-distance renewable energy transmission.
  • Global collaboration and funding:
    Establish international partnerships to share best practices and fund loss reduction initiatives in high-loss regions (e.g., Sub-Saharan Africa, South Asia).
The path to minimizing TLs demands a coordinated effort among researchers, utilities, and policymakers. By prioritizing cost-effective technologies, addressing infrastructural gaps, and fostering innovation, we can achieve resilient, low-loss power networks that align with global climate goals (SDG 7 and 13).

Author Contributions

Conceptualization, P.P., M.J., A.M.A., M.R.Z., and J.-R.R.; methodology, P.P., M.J., A.M.A., M.R.Z., and J.-R.R.; software, A.M.A. and M.R.Z.; validation, P.P., M.J., A.M.A., and J.-R.R.; formal analysis, J.-R.R.; investigation, P.P., M.J., A.M.A., M.R.Z., and J.-R.R.; resources, P.P. and J.-R.R.; data curation, P.P., M.J., and J.-R.R.; writing—original draft preparation, A.M.A., P.P., M.J., M.R.Z., and J.-R.R.; writing—review and editing, P.P., M.J., A.M.A., M.R.Z., and J.-R.R.; visualization, P.P.; supervision, P.P. and J.-R.R.; project administration, P.P. and J.-R.R.; funding acquisition, J.-R.R. All authors have read and agreed to the published version of the manuscript.

Funding

This project received funding from grant TED2021-130007B-I00, via MICIU/AEI/10.13039/501100011033/and via ERDF “A way of making Europe”, from the European Union, and from the Agència de Gestió d’Ajuts Universitaris i de Recerca-AGAUR (2021 SGR 00392).

Data Availability Statement

The original contributions presented in the study are included in the article; further inquiries can be directed to the corresponding author.

Conflicts of Interest

Authors M.J., A.M.A., and M.R.Z. are by employed Pooya Power Knowledge Enterprise. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
ABCAerial Bundled Cable
ACCCAluminum Conductor Composite Core
ACAlternative Current
ACSRAluminum Conductor Steel Reinforced
ACSSAluminum Conductor Steel Supported
ACSS/TWAluminum Conductor Steel Supported/Trapezoidal Wire
ADMSAdvanced Distribution Management System
AIArtificial Intelligence
AMIsAdvanced Metering Infrastructure
AVRAutomatic Voltage Regulator
BEEBureau of Energy Efficiency
BSCCOBismuth Strontium Calcium Copper Oxide
CORTConductor-on-Round-Tube (cooling configuration)
CRMCustomer Relationship Management
DCDirect Current
DERsDistributed Energy Resources
DGDistributed Generation
DLRDynamic Line Rating
DLMSDistribution Line Monitoring System
DERMSDistributed Energy Resource Management System
DMSDistribution Management System
DRDemand Response
EMSEnergy Management System
EMIElectromagnetic Interference
FACTSFlexible AC Transmission System
FeSCIron-Based Superconductor
GOESGrain-Oriented Silicon Steel
GZTACSRGap-Type Super Thermal Alloy Conductor Steel Reinforced
HTLSHigh-Temperature Low Sag (conductors)
HTSHigh-Temperature Superconductor
HVHigh Voltage
HVDCHigh-Voltage Direct Current
IBRsInverter Based Resources
IEAInternational Energy Agency
INVARIron–Nickel Alloy Core Conductor
LTSLow-Temperature Superconductor
LVLow Voltage
MLMachine Learning
MgB2Common Superconducting Alloy
MVMedium Voltage
NbTiNiobium–Titanium (common superconducting alloy)
Nb3SnNiobium–Tin (common superconducting alloy)
NTLsNon-Technical Losses
OHLsOverhead Lines
OpenDSSOpen Distribution System Simulator
PBRPerformance-Based Regulation
PM2.5Particulate Matter
PMUPhasor Measurement Unit
PITPowder-in-Tube
PSOParticle Swarm Optimization
PVPhotovoltaic
PVCPolyvinyl Chloride
Q-ISsQuasi-isotropic-strands
RcContact Resistance
REBCORare-Earth Barium Copper Oxide (a HTS material)
RFRadio Frequency
RfcRutherford Cable
RTVRoom Temperature Vulcanizing
SCADASupervisory Control and Data Acquisition
SDGsSustainable Development Goals
SLRStatic Line Rating
SO2Sulfur Dioxide
SSSCStatic Synchronous Series Compensator
STATCOMStatic Synchronous Compensator
SVCStatic VAR Compensator
TACSRThermal Alloy Conductor Steel Reinforced
TCSCThyristor-Controlled Series Capacitor
THDTotal Harmonic Distortion
TLsTechnical Losses
TRLsTransmission Lines
TSSCThyristor-Switched Series Capacitor
TSCsThyristor-Switched Capacitors
T&DTransmission and Distribution
XLPECross-Linked Polyethylene
YBCOYttrium Barium Copper Oxide
ZTACSRSuper Thermal Alloy Conductor Steel Reinforced

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Figure 1. Diagram illustrating mechanisms of dielectric losses in insulating materials [105].
Figure 1. Diagram illustrating mechanisms of dielectric losses in insulating materials [105].
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Figure 2. Schematic representation of corona discharge phenomena in HV power TRLs.
Figure 2. Schematic representation of corona discharge phenomena in HV power TRLs.
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Figure 3. Characteristic current pulse waveforms generated by positive and negative corona discharge [108] (reprinted with permission from IEEE).
Figure 3. Characteristic current pulse waveforms generated by positive and negative corona discharge [108] (reprinted with permission from IEEE).
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Figure 4. A representation of methods based on mechanical state monitoring [130]. These parameters are critical for ensuring safe operating distances, preventing mechanical overstress, and maintaining compliance with design standards.
Figure 4. A representation of methods based on mechanical state monitoring [130]. These parameters are critical for ensuring safe operating distances, preventing mechanical overstress, and maintaining compliance with design standards.
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Figure 5. Simple skin effect schematic [137].
Figure 5. Simple skin effect schematic [137].
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Figure 6. Percentage of power loss during T&D processes by region [168].
Figure 6. Percentage of power loss during T&D processes by region [168].
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Figure 7. Relative severity of factors causing TLs (ranked by contribution) [165].
Figure 7. Relative severity of factors causing TLs (ranked by contribution) [165].
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Figure 8. Cost comparison of using HTLS conductors for 220 kV line upgrades, as presented in [170] (EURO).
Figure 8. Cost comparison of using HTLS conductors for 220 kV line upgrades, as presented in [170] (EURO).
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Figure 9. Diagram of distributed coordination approach [215].
Figure 9. Diagram of distributed coordination approach [215].
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Figure 10. Single-line diagram of uniformly loaded primary feeder [217] (reproduced with permission from Wiley).
Figure 10. Single-line diagram of uniformly loaded primary feeder [217] (reproduced with permission from Wiley).
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Figure 11. Devices for managing reactive power compensation.
Figure 11. Devices for managing reactive power compensation.
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Figure 12. A detailed flowchart outlining the research methodology [227].
Figure 12. A detailed flowchart outlining the research methodology [227].
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Figure 13. STATCOM integrated into SMIB system [229] (reproduced with permission).
Figure 13. STATCOM integrated into SMIB system [229] (reproduced with permission).
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Figure 14. A diagram of a single-phase system with a synchronous condenser connected to the grid.
Figure 14. A diagram of a single-phase system with a synchronous condenser connected to the grid.
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Figure 15. Comparison of active and reactive power loss reduction using different FACTS controllers based on analysis by OYIOGU et al. [234].
Figure 15. Comparison of active and reactive power loss reduction using different FACTS controllers based on analysis by OYIOGU et al. [234].
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Figure 16. Cost comparison between capacitor and various FACTS devices in power systems [236].
Figure 16. Cost comparison between capacitor and various FACTS devices in power systems [236].
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Table 1. The distribution of recent research on TLs and NTLs in power systems: A review of articles published in reputable journals and selected conference proceedings that contain the terms “technical loss” or “non-technical loss” and related keyword in the article title, abstract, or keywords from 2020 to 2025.
Table 1. The distribution of recent research on TLs and NTLs in power systems: A review of articles published in reputable journals and selected conference proceedings that contain the terms “technical loss” or “non-technical loss” and related keyword in the article title, abstract, or keywords from 2020 to 2025.
Refs.YearPublisherTLNTLResearch PaperReview Paper
[32]2025MDPI
[33]2025MDPI
[34]2025Springer
[35]2025Elsevier
[36]2025Elsevier
[37]2025Elsevier
[38]2025Elsevier
[39]2025MDPI
[40]2025Elsevier
[41]2025 Elsevier
[42]2025MDPI
[43]2025IEEE
[44]2025IEEE Conference
[30]2025MDPI
[14]2024MDPI
[45]2024Elsevier
[46]2024Elsevier
[24]2024 Elsevier
[47]2024MDPI
[48]2024MDPI
[49]2024MDPI
[50]2024MDPI
[51]2024MDPI
[52]2024MDPI
[53]2024MDPI
[54]2024IEEE Conference
[55]2024Springer
[56]2024IEEE
[57]2023Springer
[58]2023MDPI
[59]2023MDPI
[60]2023MDPI
[61]2023MDPI
[62]2023Springer Conference
[63]2023IEEE Conference
[64]2023 Elsevier
[65]2023Elsevier
[66]2023Elsevier
[10]2023MDPI
[67]2022Springer
[68]2022Springer
[69]2022Taylor & Francis
[70]2022IEEE
[71]2022IEEE
[72]2022MDPI
[73]2022MDPI
[11]2022MDPI
[22]2022Elsevier
[74]2022IEEE Conference
[75]2021IEEE
[76]2021IEEE Conference
[77]2021 MDPI
[78]2021Elsevier
[79]2021MDPI
[80]2021IEEE
[27]2021MDPI
[81]2020MDPI
[82]2020IEEE Conference
[29]2020Springer Conference
[83]2020MDPI
[84]2020MDPI
Table 2. Summary of TLs in T&D networks [1,12].
Table 2. Summary of TLs in T&D networks [1,12].
CategoryExamplesKey Characteristics
Fixed Losses
  • Corona Losses (HV lines)
  • Dielectric Losses (insulation/cables)
  • Transformer Core Losses (no-load)
  • Auxiliary Loads (monitoring/control)
  • Open-Circuit Losses
  • Typically make up 1/4 to 1/3 of total TLs (varies by equipment composition).
  • Primarily depend on voltage magnitude and frequency (∝ V2).
  • Dominated by hysteresis and eddy currents in transformers.
  • Occur when equipment is energized, independent of load current under normal operation.
  • Non-linear behavior may arise under saturation (high flux density) or harmonic distortion, introducing minor current dependency.
Variable Losses
  • Joule (I2R) Losses (lines/transformers)
  • Contact Resistance Losses (Poor joints/switches)
  • Neutral Current Losses (unbalanced loads)
  • Low Power Factor Losses
  • LV Operation Losses
  • Harmonic Distortion Losses (non-linear loads)
  • Stray Losses (transformer windings)
  • Typically make up 2/3 to 3/4 of total TLs.
  • Proportional to load current squared (I2R), exacerbated by the following:
    -
    Undersized conductors;
    -
    Overloading;
    -
    Poor maintenance (e.g., loose connections);
    -
    Unbalanced phases;
  • Harmonics (increased RMS current).
  • Temperature-dependent: Resistance rises with heating, further increasing losses.
  • Harmonic losses include skin/proximity effects and frequency-dependent reactance.
Table 3. Hysteresis losses in transformer cores.
Table 3. Hysteresis losses in transformer cores.
FactorEffect on Hysteresis LossesExplanationReduction Method
Magnetic Flux Density Increases loss exponentiallyLarger flux increases core magnetization effort, causing more energy dissipation.Reduce operating flux density by optimizing core design.
Frequency Directly proportionalMore magnetization cycles per second mean more energy loss.Use materials with low hysteresis loss at high frequencies.
Core Material TypeDetermines loss magnitudeDifferent materials have different hysteresis loop areas.Use silicon steel, amorphous metals, or nanocrystalline alloys.
Steinmetz Exponent (x)Varies (1.6–2.5)Defines how the material responds to frequency changes.Choose materials with lower exponent values.
Core AnnealingReduces lossesHeat treatment improves material grain structure.Proper annealing of core laminations.
Operating TemperatureAffects loss (varies by material)Some materials show increased losses at high temperatures.Use materials stable at the intended operating temperature.
Table 4. Summary of interaction between eddy current and hysteresis losses.
Table 4. Summary of interaction between eddy current and hysteresis losses.
Operating
Condition
Dominant Loss
Component
ReasonOptimization Strategy
High B, High fEddy current lossLoss increases with B2 and f2Use thinner laminations, reduce B
High B, Low fHysteresis lossLoss scales with Bn × f; high B dominates even at low fUse materials with lower Steinmetz exponent
Low B, High fModerate eddy loss, low hysteresisEddy loss (∝ f2) is significant due to high f, while hysteresis is negligibleReduce frequency if adjustable; otherwise, use thinner laminations or high-resistivity materials
Low B, Low fMinimal fixed lossesBoth loss components remain lowIdeal operating range
Table 5. Assessment of dielectric losses across widely used insulation materials in electrical power networks.
Table 5. Assessment of dielectric losses across widely used insulation materials in electrical power networks.
Insulation MaterialDielectric Constant ( ε r ) Loss Tangent ( tan δ ) Operating Temperature RangeRelative Loss Severity
Mineral Oil2.20.0002−40 to 110Low
Silicone Oil2.80.0004−50 to 180Low
Paper–Oil System4.00.0050−40 to 110Medium
Epoxy Resin3.50.0070−40 to 200High
SF6 Gas1.00.0001−30 to 60Very Low
Table 6. Comparative analysis of effects of different conductors on resistive losses.
Table 6. Comparative analysis of effects of different conductors on resistive losses.
Conductor TypeElectrical ResistanceOperating TemperatureAmpacityLine LossesThermal SagNotes
CopperVery LowUp to 90 °CModerateLowModerateHigh conductivity; heavier and more expensive; less common for long-span overhead lines.
ACSRModerateUp to 75 °CModerateModerateHighSteel core adds strength but increases weight and sag; widely used due to cost-effectiveness.
HTLSLowUp to 210 °CHigh to very highLow at moderate temperatures, high at elevated temperaturesLowDesigned for high-temperature operations; composite or annealed aluminum cores reduce sag and resistive losses; suitable for modern, high-demand TRLs. High losses at elevated temperatures, but lower losses at same operating temperature with ACSR.
Table 7. Summary of European DLR implementations and key outcomes (2008–2020) [132].
Table 7. Summary of European DLR implementations and key outcomes (2008–2020) [132].
Location & YearDescriptionDesignKey Results
Belgium, France (2008–2020)DLR deployed on 27 lines, including all HVAC interconnection lines; both real-time and forecast data used in intraday/day-ahead planning and market capacity allocation. Sag validation surveys revealed up to 200% of rated capacity available in certain conditions.Commercial sensors measuring real-time sag on 70 kV, 150 kV, 245 kV, and 400 kV lines; 60 h ahead forecast module.Intraday rating up to 130%; for CORESO processes, up to 110% using statistical risk assessment.
Spain (2017)Best path demo 4: repowering existing lines with low-cost DLR sensors for higher-temperature operation; DLR implemented on a live 220 kV line.Seven DLR sensors detecting 0.005° catenary change (10 cm sag) for optimal loading.15–30% capacity increase during 3-month experiment.
Slovenia (2013–2017)System covers 29 lines (6 × 400 kV, 4 × 220 kV, 17 × 110 kV); fully integrated into daily operation, assisting real-time and planning, including icing prevention and extreme weather alarms.Indirect DLR using macro- and micro-scale meteorological models; per-span calculations; IT system integrated with SCADA/EMS.92–96% availability; median 15–20% capacity gain; mitigation of >20 N and >500 N-1 overload events annually.
Germany (2015)DLR on heavily loaded OHLs; ratings exchanged online between TSOs.Weather forecast models using local/regional measurements and seasonal profiles.Capacity increased up to 200%.
Italy (2012)Mixed-approach DLR deployment by Terna on 380 kV, 220 kV, and 150/132 kV lines; integrates HTLS support; expansion plan in place.Thermo-mechanical model based on CIGRÉ dynamic model; real-time monitoring feedback for critical spans to ensure clearance compliance.Operational use with enhanced line utilization (capacity increase not numerically stated).
Table 8. Key metrics for HTLS and DLR [133,134,135].
Table 8. Key metrics for HTLS and DLR [133,134,135].
MetricHTLS ConductorsDLRHTLS+DLR
Ampacity Increase~20–40% over ACSR~15–30% (weather-dependent peaks)Baseline fixed gain from HTLS + further 15–25% transient gain from DLR, yielding up to 2.3× total capacity under favorable weather
Implementation Cost~1.8–2.5× ACSR costDeploying DLR technology costs approximately USD 50,000 per mile for short lines (sensor-based systems)Sum of HTLS replacement cost plus DLR deployment cost; higher capital expenditure, but faster return on investment due to deferral of new line construction
Deployment ComplexityHigh (full reconductoring)Moderate (sensor network + SCADA)High (combines physical retrofitting with advanced monitoring/control infrastructure)
Table 9. Characteristics of various materials for skin depth computation [141,142,143].
Table 9. Characteristics of various materials for skin depth computation [141,142,143].
MaterialConductivityMagnetic PermeabilitySkin Depth at 60 Hz
Copper5.8 × 10718.5 mm
Aluminum3.5 × 107111 mm
Iron1.0 × 10750000.3 mm
Silver6.3 × 10718.2 mm
Table 10. Comparison of contact materials in electrical joints.
Table 10. Comparison of contact materials in electrical joints.
Contact MaterialInitial Contact Resistance (μΩ)Oxidation RateStability over 10 YearsEstimated Energy Loss Reduction (%)
Copper100–300HighModerate10–15
Silver-plated20–50LowHigh25–40
Ultrasonic weld5–15MinimalVery High35–50
Aluminum200–500Very HighLow5–10
Table 11. A summary of the approaches different countries takes to defining, overseeing, and documenting power losses [164,165,166].
Table 11. A summary of the approaches different countries takes to defining, overseeing, and documenting power losses [164,165,166].
CountryDescription of Power Loss Reporting and Treatment
IranA distinction is made between TLs and NTLs in the official reporting of energy distribution and transmission companies, but usually the majority of losses are reported as the sum of both sections (with an estimated share for each section), and complete and accurate statistics are not always available.
EgyptTLs in MV/LV networks and transformers. Distribution Companies (DisCos) calculate losses using network samples (load, power factor, voltage) + specialized loss calculation software. Methodologies are under development.
GeorgiaGeorgia draws a line between TLs and NTLs, with the latter grouped as commercial losses or energy used by the operator itself
LebanonTLs related to grid technical issues. No standardized calculation formula exists.
Jordan% TLs = (Purchased Power − Consumed Power)/Purchased Power.
NorwayThe Norwegian approach does not separate technical losses from NTLs, as the non-technical portion is considered almost negligible.
Bosnia & HerzegovinaLosses due to technical issues (conductor resistance, transformer losses, etc.). No specific calculation method is mentioned.
KosovoKosovo does not provide a cemented legal description for losses, and thus does not have a formal distinction or structure for NTLs.
DenmarkIn Denmark, losses are tracked without explaining or dividing their technical or non-technical components.
North MacedoniaNorth Macedonia does not separate non-technical losses from TLs in official reports.
PortugalLosses in Portugal do not cover public lighting or power used internally by network operators when such uses are correctly measured by meters. Other losses are recorded as per the general guidelines.
BelgiumThe treatment varies by region; for example, certain kinds of fixed-power consumption are included in Brussels and Wallonia. The criteria for transmission network losses are described differently but remain unspecified.
SpainSpain uses a unified method, calculating total losses as the gap between energy entering and leaving the system, without distinguishing their origin.
Table 12. Comparison of HTLS conductor types [124,176,177,178].
Table 12. Comparison of HTLS conductor types [124,176,177,178].
Conductor TypeLossesCostApplicationOther Important Factors
TACSRModerate losses due to aluminum alloy resistanceLow to ModerateUsed in areas with moderate temperature and load conditionsSuitable for replacing ACSR conductors with minimal modification to structures
ZTACSRModerate losses due to aluminum–zirconium alloy resistance but higher than TACSRModerateHigh-temperature
applications (up to 230 °C), suitable for upgrading existing lines
Improved strength and better sag control than TACSR
ACCCVery low losses due to lower resistance and composite coreHighLong-span TRLs, environmentally sensitive areasHigh efficiency, minimal sag, lightweight, better for reducing CO2 emissions
ACSSLow losses, especially at high temperaturesModerate to HighUsed in reconductoring projects where higher ampacity is needed without new structuresCan operate at 250 °C, fully annealed aluminum improves conductivity
GZTACSRModerate losses due to aluminum–zirconium alloy resistance but higher than TACSRHighHV TRLs requiring strict sag and vibration controlGap-type structure allows for better vibration damping expansion
INVARModerate losses but lower than (G)(Z)TACSRHighUsed in areas where minimal sag variation is criticalNickel–iron core minimizes thermal expansion, stable sag at high temperatures
Table 13. A summary of the key advantages of HTS cables [185,188,189,190,191].
Table 13. A summary of the key advantages of HTS cables [185,188,189,190,191].
FeatureDescription
Zero ResistanceEliminates I2R losses, improving energy efficiency and reducing heat dissipation, making HTS cables far more efficient than conventional ones.
High Power CapacitySuperconductor wires carry much larger currents (2–4 kArms) in the same space as conventional cables (1 kArms), solving urban power bottlenecks.
Ease of InstallationHTS cables emit no heat, reducing spacing requirements. Their lightweight and compact design allow for easy installation, retrofitting, and deep underground placement.
Lower Voltage OperationHigh current capacity allows for operation at lower voltages, improving safety and simplifying permits in urban and suburban environments.
Fault Current LimitingHTS cables can integrate fault current limitation, preventing dangerous fault current spikes and enhancing grid reliability in urban settings.
Low ImpedanceCompact design and magnetic field containment reduce impedance, enabling HTS cables to take more load and integrate with phase angle regulators for precise power flow control.
Increased Capacitive Charging LengthLower capacitance and high current capacity allow for longer underground cable runs, overcoming conventional cable length limitations in HV applications.
Table 14. Comparison of HTS generations [118,119].
Table 14. Comparison of HTS generations [118,119].
Feature1st Gen (1G)2nd Gen (2G)3rd Gen (3G) (Future)
MaterialBi-2223YBCOFeSC/MgB2
FabricationPIT methodCoated conductorAdvanced novel methods
StructureSilver matrix tapesMetallic substrate with buffer layersLess complex layered structure
CostHigh (silver dependency)Lower than 1G, but still costlyExpected to be low
Current DensityModerateHighVery High
FlexibilityLowModerateHigh
Mechanical StrengthLowHighExpected to be higher
Commercial AvailabilityAvailableWidely usedStill under development
Table 15. Comparison of voltage optimization methods—techniques, benefits, and challenges [218,219,220,221].
Table 15. Comparison of voltage optimization methods—techniques, benefits, and challenges [218,219,220,221].
MethodKey TechniqueBenefitsChallenges
Transformer Tap ChangersAdjusting the voltage ratio of transformers using tap changer mechanisms
-
Reduce both fixed and variable losses
-
Improve voltage profiles
-
Enhance system reliability
-
Improper tap settings lead to power dissipation
-
Require precise control systems
Decentralized Voltage Regulation AlgorithmsAutonomous voltage regulation by DG units based on local and remote measurements
-
Minimize active and reactive power losses
-
Require minimal communication infrastructure
-
Faster response times
-
Limited coordination in some cases
-
Higher computational complexity for real-time adjustments
Multi-Objective OptimizationOptimization of components such as tie-switches and capacitor banks using multi-objective heuristics
-
Minimizes losses
-
Optimizes voltage profile
-
Balances multiple objectives
-
Complex optimization due to multiple variables
-
Requires advanced optimization algorithms
Bus Bar CapacitorsCompensation of reactive power by injecting capacitive reactive power
-
Reduce current flow
-
Decrease resistive losses
-
Enhance voltage stability and power factor
-
Sizing and placement optimization
-
Dynamic capacitor banks require real-time control
Inductor BanksReactive power compensation in distribution/industrial systems via parallel inductors
-
Harmonic filtering (e.g., 5th/7th harmonics
-
Improve PF in inductive loads
-
Reduce voltage distortion
-
Increased losses if improperly tuned
-
Risk of resonance with system capacitance
Table 16. Impact of SVC on voltage stability, power factor, and power loss reduction.
Table 16. Impact of SVC on voltage stability, power factor, and power loss reduction.
ScenarioTotal Real Power Loss (KW)Total Reactive Power Loss (KVAR)
Base case 202.65182.62
With SVC135.13123.13
With SVC and DG85.7864.26
Table 17. Comparison of reactive power compensation methods [237,238,239,240].
Table 17. Comparison of reactive power compensation methods [237,238,239,240].
Compensation MethodTypeWorking PrincipleKey AdvantagesLimitationsTypical Applications
SVCShuntUses thyristor-controlled reactors and capacitors to provide reactive power compensationFast response, voltage stabilization, and reduces transmission lossesLimited control over real power requires a large spaceTransmission systems, industrial loads
STATCOMShuntUses VSC to inject reactive power dynamicallyFaster response than SVC, better performance under LV conditionsHigher cost, complex controlTransmission grids, renewable energy integration
Synchronous CondenserShuntA rotating synchronous machine that absorbs or supplies reactive powerProvides inertia support, enhances short-circuit strengthHigh maintenance, mechanical lossesLong-distance transmission, voltage control
SSSCSeriesInjects a controllable voltage in series with the TRLImproves power transfer capability, mitigates power oscillationsRequires energy storage for real power exchange, is expensivePower transmission networks
TCSCSeriesUses thyristors to regulate the effective impedance of the TRLImproves system stability, reduces transmission lossesSwitching transients, complex controlHV transmission systems
TSSCSeriesProvides discrete control of series compensation using thyristorsSimple operation, enhances power transfer capabilityLimited flexibility compared to TCSCTransmission networks with fixed compensation needs
Table 18. Sensor impact on voltage stability.
Table 18. Sensor impact on voltage stability.
Sensor TypeVoltage Stability ImpactSecondary Function
Voltage and Current SensorsMediumDetect overloads
Temperature SensorsLowPrevent overheating
PMUsHighImprove grid stability
Smart MetersNoneReduce billing errors
Fault Detection SensorsVery HighPrevent short circuits
Table 19. Automated control systems and administrative workload reduction.
Table 19. Automated control systems and administrative workload reduction.
System TypeReduction in Administrative WorkloadUnrelated Feature
SCADAModerateDetects faults
EMSHighBalances demand
DMSLowReroutes power
AVR SystemsNoneMaintain voltage
Demand ResponseVery HighPrevents overloading
Table 20. Fault detection systems—speed.
Table 20. Fault detection systems—speed.
Fault Detection SystemSpeed of Detection
PMUsFast
Smart RelaysMedium
Line Fault DetectionVery Fast
AFDI SystemsInstant
AI-Based PredictionVariable
Table 21. Summary of global projects for loss reduction [273,274,275,276,277,278,279].
Table 21. Summary of global projects for loss reduction [273,274,275,276,277,278,279].
CountryProject/InitiativeKey MethodsImpact
AngolaGestoenergy, Energy Loss Reduction ProjectFeeder audits, grid redesign, smart metersPilot phase: 15% TL reduction in Luanda
Spain/ItalyREE/ENEL Multilevel Voltage Control SystemHierarchical voltage control with 4 levels, reactive power optimization, real-time loss minimization.Expected loss reduction of at least 4%, equivalent to 20–40 MW (Spain) and 32–64 MW (Italy).
BrazilLight S.A. Smart Grid (Rio de Janeiro)Network reconfiguration, real-time monitoring, transformer upgrades~12% loss reduction and improved reliability
PhilippinesLoss Reduction for Philippine Electric CooperativesSystem loss reduction manual implementation, quantitative loss evaluation system, upgrading to 23 kV mid-voltage standards, technical design standards improvement Reduction in losses in power distribution systems and enhancement in power supply capability in an efficient and economic fashion
GermanyHVDC Transmission (Siemens/ABB)Long-distance HVDC technology for renewable integrationImproved transmission efficiency and renewable energy utilization
KenyaWorld Bank Mini-Grids (Kenya, Nigeria)DG, battery storage, loss monitoring systemsReduced TLs in rural off-grid areas
TajikistanKhatlon Energy Loss Reduction ProjectLV grid modernization, substation upgrades, automated billingTargeted 20% loss reduction (expected CO2 emission avoidance)
Table 22. Comparative analysis of TL mitigation technologies by maturity level.
Table 22. Comparative analysis of TL mitigation technologies by maturity level.
TechnologyMaturity Level/Technology Readiness Level (9 Highest)Commercial
Voltage/VAR Optimization9Widely Deployed
High-Efficiency Transformers (Amorphous Core)9Commercially Mature
HTLS7–8Commercially Mature
Reactive Power Compensation (Capacitors/SVC)9Widely Deployed
STATCOM8–9Commercially Mature
1G/2G HTS6–7Early Commercial/Niche
3G HTS3–5Pre-Commercial/R&D
AI-Driven Predictive Maintenance6–8Early Commercial
Smart Grid (AMI, DMS)7–9Early Commercial to Mature
Table 23. Comprehensive summary of technologies for TL reduction.
Table 23. Comprehensive summary of technologies for TL reduction.
TechnologyMechanismAdvantagesLimitationsCost
Implication
Key
Applications
HTLS Conductors (e.g., ACCC, ACSS, TACSR)Reduced resistance and sag at high temperatures; composite cores of lower weight and increased ampacity.
-
Higher current capacity.
-
Lower sag and thermal expansion.
-
Compatible with existing infrastructure.
-
High initial cost.
-
Specialized installation required.
High upfront cost but long-term savings due to reduced losses and deferred upgrades.Upgrading overhead TRLs, high-demand grids, renewable integration.
High-Temperature Superconductors (HTSs)Zero resistance below critical temperature; eliminate I2R losses.
-
Ultra-high efficiency.
-
Compact design for urban areas.
-
Fault current limiting.
-
Requires cryogenic cooling.
-
Extremely high material and maintenance costs.
Very high (cooling systems, specialized materials).Urban grids, high-capacity transmission, fault-prone networks.
Voltage Optimization (Tap Changers, Capacitors, AVRs)Adjusts voltage levels dynamically to minimize losses and improve power factor.
-
Improves grid stability.
-
Compatible with renewable energy.
-
Scalable.
-
Requires advanced control systems.
-
Limited by grid topology.
Moderate (installation and control systems).Distribution networks, industrial loads, microgrids.
Reactive Power Compensation (SVCs, STATCOMs, Synchronous Condensers)Compensates for reactive power to reduce line current and losses.
-
Fast response.
-
Enhances voltage stability.
-
Reduces harmonic distortion.
-
High capital cost for STATCOMs.
-
Synchronous condensers are bulky.
High (complex power electronics).Grid stability, industrial plants, long TRLs.
Smart Grid Technologies (DLR, PMUs, AI-Driven Monitoring)Real-time monitoring and adaptive control of grid parameters.
-
Predictive maintenance.
-
Optimizes power flow.
-
Integrates renewables.
-
Requires robust cybersecurity.
-
High initial investment.
High (sensors, communication infrastructure, software).Modern grids, renewable integration, fault detection.
Regular Maintenance (Conductor Cleaning, Joint Tightening, Transformer Oil Testing)Prevents degradation and hotspots in infrastructure.
-
Low-tech and immediate.
-
Extends equipment lifespan.
-
Labor-intensive.
-
Requires periodic scheduling.
Low to moderate (labor and materials).Aging grids, pollution-prone areas, rural networks.
Advanced Materials (Amorphous Metal Transformers, Nanocomposite Insulators)Reduce hysteresis/eddy losses (transformers) and leakage currents (insulators).
-
High efficiency.
-
Longer lifespan.
-
Lower no-load losses.
-
Higher material costs.
-
Limited suppliers.
Moderate (higher than conventional but offset by savings).Distribution transformers, HV substations.
Series Compensation (TCSC, SSSC)Adjusts line impedance to optimize power flow and reduce losses.
-
Improves power transfer capacity.
-
Mitigates congestion.
-
Complex installation.
-
Risk of sub-synchronous resonance.
High (specialized equipment).Long-distance transmission, interconnectors.
Table 24. Implementation roadmap for TL reduction in T&D systems.
Table 24. Implementation roadmap for TL reduction in T&D systems.
Time FrameTransmission Level SolutionsDistribution Level Solutions
Short-Term (0–2 years)
-
Load balancing across phases
-
Reconductoring (replacing old conductors with higher-capacity ones)
-
Infrared thermography to detect hotspots in lines and transformers
-
Optimal transformer tap-changing to regulate voltage
-
Reactive power compensation (installing shunt capacitors)
-
Power factor correction (installing capacitors at substations/feeders)
-
Energy audits to identify high-loss areas
-
Replacing damaged conductors & joints
-
Voltage optimization (adjusting distribution transformer taps)
-
Anti-theft measures (smart meters, tamper-proof seals)
Medium-Term
(2–5 years)
-
AMI for real-time monitoring
-
DLR to optimize capacity
-
Upgrading substations with high-efficiency transformers
-
Partial replacement of old lines with low-loss conductors (e.g., ACCC)
-
Fault detection systems (using AI/ML for predictive maintenance)
-
Automated feeder reconfiguration for loss minimization
-
Deploying DERs to reduce line loading
-
Replacing overloaded transformers with energy-efficient models
-
Implementing smart grids for better load management
-
Advanced distribution management systems for loss reduction
Long-Term (5+ years)
-
HVDC lines for long-distance transmission
-
Superconducting transmission cables for near-zero losses
-
Wide-scale grid digitalization (IoT, AI-driven grid optimization)
-
Expansion of FACTS devices (Flexible AC transmission systems)
-
Grid modernization with wide-area monitoring systems
-
Full smart grid deployment with self-healing capabilities
-
Large-scale renewable integration (microgrids to reduce T&D distances)
-
Complete transition to energy-efficient transformers (amorphous core)
-
Underground cabling in high-loss urban areas
-
Advanced energy storage systems to balance load and reduce losses
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Parvizi, P.; Jalilian, M.; Amidi, A.M.; Zangeneh, M.R.; Riba, J.-R. Technical Losses in Power Networks: Mechanisms, Mitigation Strategies, and Future Directions. Electronics 2025, 14, 3442. https://doi.org/10.3390/electronics14173442

AMA Style

Parvizi P, Jalilian M, Amidi AM, Zangeneh MR, Riba J-R. Technical Losses in Power Networks: Mechanisms, Mitigation Strategies, and Future Directions. Electronics. 2025; 14(17):3442. https://doi.org/10.3390/electronics14173442

Chicago/Turabian Style

Parvizi, Pooya, Milad Jalilian, Alireza Mohammadi Amidi, Mohammad Reza Zangeneh, and Jordi-Roger Riba. 2025. "Technical Losses in Power Networks: Mechanisms, Mitigation Strategies, and Future Directions" Electronics 14, no. 17: 3442. https://doi.org/10.3390/electronics14173442

APA Style

Parvizi, P., Jalilian, M., Amidi, A. M., Zangeneh, M. R., & Riba, J.-R. (2025). Technical Losses in Power Networks: Mechanisms, Mitigation Strategies, and Future Directions. Electronics, 14(17), 3442. https://doi.org/10.3390/electronics14173442

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