Energies

44 pages, 6410 KB

Open AccessArticle

Experimental Assessment and Digital Twin Modeling of Integrated AEM Electrolyzer–PEM Fuel Cell–BESS for Smart Hydrogen Energy Applications

by A. H. Samitha Weerakoon and Mohsen Assadi

Energies 2025, 18(23), 6318; https://doi.org/10.3390/en18236318 (registering DOI) - 30 Nov 2025

Abstract

Rising energy demand, fossil fuel depletion, and global warming are accelerating research into sustainable energy solutions, with growing interest in hydrogen as a promising alternative. This research presents a detailed experimental investigation and novel digital twin (DT) models for an integrated hydrogen-based energy [...] Read more.

Rising energy demand, fossil fuel depletion, and global warming are accelerating research into sustainable energy solutions, with growing interest in hydrogen as a promising alternative. This research presents a detailed experimental investigation and novel digital twin (DT) models for an integrated hydrogen-based energy system consisting of an Anion Exchange Membrane Electrolyzer (AEMEL), Proton Exchange Membrane Fuel Cell (PEMFC), hydrogen storage, and Battery Energy Storage System (BESS). Conducted at a real-world facility in Risavika, Norway, the study employed commercial units: the Enapter EL 4.1 AEM electrolyzer and Intelligent Energy IE-Lift 1T/1U PEMFC. Experimental tests under dynamic load conditions demonstrated stable operation, achieving hydrogen production rates of up to 512 NL/h and a specific power consumption of 4.2 kWh/Nm³, surpassing the manufacturer’s specifications. The PEMFC exhibited a unique cyclic operational mechanism addressing cathode water flooding, a critical issue in fuel cell systems, achieving steady-state efficiencies around 43.6% under prolonged (190 min) rated-power operation. Subsequently, advanced DT models were developed for both devices: a physics-informed interpolation model for the AEMEL, selected due to its linear and steady operational behavior, and an ANN-based model for the PEMFC to capture its inherently nonlinear, dynamically fluctuating characteristics. Both models were validated, showing excellent predictive accuracy (<3.8% deviation). The DTs integrated manufacturer constraints, accurately modeling transient behaviors, safety logic, and operational efficiency. The round-trip efficiency of the integrated system was calculated (~27%), highlighting the inherent efficiency trade-offs for autonomous hydrogen-based energy storage. This research significantly advances our understanding of integrated H₂ systems, providing robust DT frameworks for predictive diagnostics, operational optimization, and performance analysis, supporting the broader deployment and management of hydrogen technologies. Full article

(This article belongs to the Section A5: Hydrogen Energy)

17 pages, 3219 KB

Open AccessArticle

Investigation of Torque Enhancement in PMSMs for LEV Propulsion Using Magnet Segmentation

by Ali Sinan Cabuk and Ozgur Ustun

Energies 2025, 18(23), 6317; https://doi.org/10.3390/en18236317 (registering DOI) - 30 Nov 2025

Abstract

In this paper, the effect of eddy-current losses of permanent magnets (PMs) is studied by conducting analyses and experiments. PM segmentation is used to reduce eddy-current losses. Nowadays, many researchers are focusing on improving the efficiency and torque of permanent magnet synchronous motors [...] Read more.

In this paper, the effect of eddy-current losses of permanent magnets (PMs) is studied by conducting analyses and experiments. PM segmentation is used to reduce eddy-current losses. Nowadays, many researchers are focusing on improving the efficiency and torque of permanent magnet synchronous motors (PMSMs), particularly in electric vehicle applications. This study evaluates PM eddy-current losses of an in-wheel-type PMSM designed for light electric vehicle (LEV) propulsion. Improving output torque and efficiency is essential in this type of direct-drive application. The eddy-current losses of PMs can be reduced by forming PMs as electrically isolated magnet segments. PM segmentation leads to shorter paths and reduces the values of eddy-currents, creating reduced magnetic losses. The improvement in torque production capability also implies an improvement in efficiency. To investigate the validity of PM segmentation, a three-dimensional (3D) finite element analysis (FEA) software is used for non-segmented (monolithic) and segmented cases. The experimental study is conducted using monolithic PM and segmented PM rotor assemblies. This study demonstrates the contribution of PM segmentation to torque production. Full article

(This article belongs to the Special Issue New Solutions in Electric Machines and Motor Drives: 2nd Edition)

20 pages, 546 KB

Open AccessArticle

The Impact of Green Bonds and Energy Use on Carbon Dioxide Emissions: Evidence from 17 Financially Developed Countries (2014–2023)

by Bartosz Jóźwik, Ayşegül Toy, Murat Tekbas, Mesut Dogan and Filip Krauze

Energies 2025, 18(23), 6316; https://doi.org/10.3390/en18236316 (registering DOI) - 30 Nov 2025

Abstract

This study investigates how green bond issuance, energy use, renewable energy, and economic growth relate to per capita CO₂ emissions in 17 financially developed countries that are active in green bond markets over the period 2014–2023. We construct an annual panel for [...] Read more.

This study investigates how green bond issuance, energy use, renewable energy, and economic growth relate to per capita CO₂ emissions in 17 financially developed countries that are active in green bond markets over the period 2014–2023. We construct an annual panel for Australia, Austria, Canada, Mainland China, Finland, France, Germany, Italy, Japan, Luxembourg, New Zealand, Norway, Spain, Sweden, the United Kingdom, and the United States, and apply panel-corrected standard errors (PCSEs) together with Method of Moments Quantile Regression (MMQR). Diagnostic tests based on Pesaran’s CIPS unit root and Westerlund’s cointegration procedures indicate that the variables are I(1) and cointegrated, while Pesaran-type dependence and slope heterogeneity tests justify the use of robust panel methods. The PCSE results show that total energy consumption is the strongest factor associated with higher emissions, renewable energy consumption is consistently associated with lower emissions, economic growth is positively linked to emissions, and green bond issuance is associated with lower emissions, although the magnitude of this relationship is modest. MMQR estimates reveal that these relationships are heterogeneous across the CO₂ distribution. Green bonds are associated with lower emissions only in low-emission country–years, while this association becomes statistically weak at higher quantiles. Renewable energy is linked to lower emissions across all quantiles, with stronger associations in the lower part of the distribution, and the growth–emissions relationship weakens at the top, consistent with an Environmental Kuznets Curve pattern. These findings suggest that expanding renewables and improving the carbon content of energy use remain central for decarbonization, while green bonds may support emission reductions, particularly in cleaner, institutionally advanced economies. Full article

(This article belongs to the Special Issue Energy Economics, Finance and Policy Towards Sustainable Energy: 2nd Edition)

16 pages, 2062 KB

Open AccessArticle

An Indicator for Assessing the Hosting Capacity of Low-Voltage Power Networks for Distributed Energy Resources

by Grzegorz Hołdyński, Zbigniew Skibko and Andrzej Firlit

Energies 2025, 18(23), 6315; https://doi.org/10.3390/en18236315 (registering DOI) - 30 Nov 2025

Abstract

The article analyses the hosting capacity of low-voltage (LV) power grids for connecting distributed energy sources (DER), mainly photovoltaic installations (PV), considering technical limitations imposed by power system operating conditions. The main objective of the research was to develop a simple equation that [...] Read more.

The article analyses the hosting capacity of low-voltage (LV) power grids for connecting distributed energy sources (DER), mainly photovoltaic installations (PV), considering technical limitations imposed by power system operating conditions. The main objective of the research was to develop a simple equation that enables the quick estimation of the maximum power of an energy source that can be safely connected at a given point in the network without causing excessive voltage rise or overloading the transformer and line cable. The analysis was performed on the basis of relevant calculation formulas and simulations carried out in DIgSILENT PowerFactory, where a representative low-voltage grid model was developed. The network model included four transformer power ratings (40, 63, 100, and 160 kVA) and four cable cross-sections (25, 35, 50, and 70 mm²), which made it possible to assess the impact of these parameters on grid hosting capacity as a function of the distance from the transformer station. Based on this, the P_HCI indicator was developed to determine the hosting capacity of a low-voltage network, using only the transformer rating and the length and cross-section of the line for the calculations. A comparison of the results obtained using the proposed equation with detailed calculations showed that the approximation error does not exceed 15%, which confirms the high accuracy and practical applicability of the proposed approach. Full article

(This article belongs to the Special Issue New Technologies and Materials in the Energy Transformation)

15 pages, 588 KB

Open AccessArticle

Closing the Loop on Solar: A Sustainability Assessment of Photovoltaic Recycling in Greece

by Kyriaki Kiskira, Angeliki Lalopoulou, Konstantinos Kalkanis and George Vokas

Energies 2025, 18(23), 6314; https://doi.org/10.3390/en18236314 (registering DOI) - 30 Nov 2025

Abstract

This paper examines the sustainability of photovoltaic (PV) panel recycling through a case study in Greece. It traces the evolution of PVs and outlines the main construction characteristics, emphasizing that although PV systems reduce greenhouse gas emissions, they also generate substantial end-of-life (EoL) [...] Read more.

This paper examines the sustainability of photovoltaic (PV) panel recycling through a case study in Greece. It traces the evolution of PVs and outlines the main construction characteristics, emphasizing that although PV systems reduce greenhouse gas emissions, they also generate substantial end-of-life (EoL) waste containing both valuable and potentially hazardous materials. The study estimates Greece’s annual PV waste generation and evaluates its environmental, social, and economic impacts. It focuses on advanced disassembly and recycling methods by PV types and calculates material-recovery rates. Using national installation data from 2009–2023, the analysis quantifies the potential mass of recoverable materials and assesses the sustainability of PV recycling in terms of environmental protection, public health, and economic feasibility. Results show high recovery rates: silicon (85%), aluminum (100%), silver (98–100%), glass (95%), copper (97%), and tin (32%). Although current recycling economics remain challenging, the environmental and health benefits are significant. This research contributes to the existing literature by providing the first detailed quantification of recoverable raw materials embedded in Greece’s PV stock and by highlighting the need for technological innovation and supportive policies to enable a circular and sustainable solar economy. Full article

(This article belongs to the Special Issue A Circular Economy Perspective: From Waste to Energy)

21 pages, 2110 KB

Open AccessArticle

Control of an Energy Storage System in the Prosumer’s Installation Under Dynamic Tariff Conditions

by Paweł Kelm, Rozmysław Mieński and Irena Wasiak

Energies 2025, 18(23), 6313; https://doi.org/10.3390/en18236313 (registering DOI) - 30 Nov 2025

Abstract

In accordance with the European common rules for the internal electricity market, suppliers offer end users contracts with dynamic energy prices. To reduce energy costs, prosumers must manage their installations with energy storage devices (ESSs). The authors propose a novel control strategy with [...] Read more.

In accordance with the European common rules for the internal electricity market, suppliers offer end users contracts with dynamic energy prices. To reduce energy costs, prosumers must manage their installations with energy storage devices (ESSs). The authors propose a novel control strategy with a relatively simple simulation-based algorithm that effectively reduces daily energy costs by managing the ESS charging and discharging schedule under different types of dynamic energy tariffs. The algorithm operates in a running window mode to ensure ongoing control updates in response to the changing conditions of the prosumer’s installation operation and dynamically changing energy prices. A feature of the control system is its ability to regulate the power exchanged with the supply network in response to an external signal from a superior control system or a network operator. This feature allows the control system to participate in regulatory services provided by the prosumer to the DSO. The effectiveness of the proposed control algorithm was verified in the PSCAD V4 Professional environment and with the MS Excel SOLVER for Office 365 optimisation tool. The results showed good accuracy with respect to the cost reduction algorithm and confirmed that the additional regulatory service can be effectively implemented within the same prosumer ESS control system. Full article

(This article belongs to the Section D: Energy Storage and Application)

38 pages, 2935 KB

Open AccessArticle

Household Challenges in Solar Retrofitting to Optimize Energy Usage in Subtropical Climates

by Richard Hyde, David Wadley and John Hyde

Energies 2025, 18(23), 6312; https://doi.org/10.3390/en18236312 (registering DOI) - 30 Nov 2025

Abstract

This study investigates the architectural design factors that influence the adoption of eco-friendly solar energy technologies for the partial retrofitting of older residential buildings in densely populated urban areas in a developed country. This research study employs a mixed-method approach, combining quantitative and [...] Read more.

This study investigates the architectural design factors that influence the adoption of eco-friendly solar energy technologies for the partial retrofitting of older residential buildings in densely populated urban areas in a developed country. This research study employs a mixed-method approach, combining quantitative and qualitative frameworks along with comparative analysis and utilizing standard fact-finding procedures to examine the adoption of eco-friendly energy systems and their integration into existing infrastructures. The feasibility study, complemented by a detailed technical investigation, identifies several significant factors affecting the intention to undertake sustainable solar retrofitting. These factors include performance expectations, facilitating conditions, motivation, price/value perceptions, and environmental knowledge. This study highlights key constraints and tipping points that influence households’ decisions to implement light retrofitting and explores three distinct system configurations to enhance cost-effectiveness. The insights gained from this research study are valuable for a range of stakeholders, including homeowners, designers, technology developers and manufacturers, real estate developers, builders, and government entities. The findings guide effective strategies to encourage eco-friendly retrofits through both passive and active systems, contributing to future environmental sustainability goals. This research study addresses a gap in the literature regarding the environmental sustainability of solar retrofitting in densely populated urban settings in developed countries. Addressing the pressing issue of global warming contributes to advancing sustainable solar housing technologies and provides a comprehensive foundation for the early stages of the design process. Full article

(This article belongs to the Special Issue Advanced Studies in Energy Efficiency of Buildings and Urban Built Environment)

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20 pages, 8449 KB

Open AccessArticle

Research on the Alternating Current Properties of Cellulose–Innovative Bio-Oil Nanocomposite as the Fundamental Component of Power Transformer Insulation—Determination of Nanodroplet Dimensions and the Distances Between Them

by Konrad Kierczyński, Tomasz N. Kołtunowicz, Vitalii Bondariev, Paweł Okal, Marek Zenker, Marek Szrot, Paweł Molenda, Andrzej Cichoń and Paweł Żukowski

Energies 2025, 18(23), 6311; https://doi.org/10.3390/en18236311 (registering DOI) - 30 Nov 2025

Abstract

The paper presents measurements of frequency dependence of conductivity and real components of complex permittivity of a nanocomposite consisting of electrical pressboard, bio-insulating oil and water nanodroplets with moisture content ranging from 0.6 wt.% to 5 wt.%. Bio-oil meets high environmental requirements—it is [...] Read more.

The paper presents measurements of frequency dependence of conductivity and real components of complex permittivity of a nanocomposite consisting of electrical pressboard, bio-insulating oil and water nanodroplets with moisture content ranging from 0.6 wt.% to 5 wt.%. Bio-oil meets high environmental requirements—it is fully biodegradable, and its combustion products are significantly less harmful than those of mineral oil. In addition, the use of bio-oil reduces the carbon footprint of power transformer production. The quantum mechanical phenomenon of electron tunnelling between potential wells created by water nanodroplets was used to analyze the experimental results obtained. The study determined the effect of moisture content on the relative relaxation time values. On this basis, the number of water molecules in nanodroplets, their diameters and the concentration of nanodroplets depending on moisture content were determined. The distances over which electrons tunnel in moist pressboard impregnated with bio-oil were determined. These values are the expected values of the probability distribution of the distance between neighbouring nanodroplets. The values of the number of water molecules in nanodroplets are also the expected values of the probability distribution of the number of molecules in nanodroplets. It has been established that during many years of transformer life, several parallel processes occur as the moisture content in bio-oil-impregnated pressboard increases. One of them involves the accumulation of water molecules collected in the pressboard in nanodroplets. The second is an increase in the concentration of nanodroplets. The third is an increase in the average number of water molecules in nanodroplets. Full article

(This article belongs to the Section F: Electrical Engineering)

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44 pages, 4291 KB

Open AccessArticle

A Physics-Informed Reinforcement Learning Framework for HVAC Optimization: Thermodynamically-Constrained Deep Deterministic Policy Gradients with Simulation-Based Validation

by Sattar Hedayat, Tina Ziarati and Matteo Manganelli

Energies 2025, 18(23), 6310; https://doi.org/10.3390/en18236310 (registering DOI) - 30 Nov 2025

Abstract

This paper presents a physics-informed reinforcement learning framework that embeds thermodynamic constraints directly into the policy network of a continuous control agent for HVAC optimization. We introduce a Thermodynamically-Constrained Deep Deterministic Policy Gradient (TC-DDPG) algorithm that operates on continuous actions and enforces physical [...] Read more.

This paper presents a physics-informed reinforcement learning framework that embeds thermodynamic constraints directly into the policy network of a continuous control agent for HVAC optimization. We introduce a Thermodynamically-Constrained Deep Deterministic Policy Gradient (TC-DDPG) algorithm that operates on continuous actions and enforces physical feasibility through a differentiable constraint layer coupled with physics-regularized loss functions. In a simulation-based evaluation using a custom Python multi-zone resistance-capacitance (RC) thermal model, the proposed method achieves a 34.7% reduction in annual HVAC electricity consumption relative to a rule-based baseline (95% CI: 31.2–38.1%, n = 50 runs) and outperforms standard DDPG by 16.1 percentage points. Thermal comfort during occupied hours maintains PMV∈ [−0.5, 0.5] for 98.3% of operational time, peak demand decreases by 35.8%, and simulated coefficient of performance (COP) improves from 2.87 ± 0.08 to 4.12 ± 0.10. Physics constraint violations are reduced by approximately 98.6% compared to unconstrained DDPG, demonstrating the effectiveness of architectural enforcement mechanisms within the simulation environment. We present a reference prototype and commit to a future public release of the code, configurations, and hyperparameters sufficient to reproduce the reported results. The paper explicitly addresses the limitations of simulation-based studies and presents a staged roadmap toward hardware-in-the-loop testing and pilot deployments in real buildings. Full article

(This article belongs to the Special Issue New Insights into Hybrid Renewable Energy Systems in Buildings)

30 pages, 3660 KB

Open AccessSystematic Review

Managerial and Legal Frameworks in Energy Sector Transformation: A Key Area Review

by Marta Bakun and Adam Sulich

Energies 2025, 18(23), 6309; https://doi.org/10.3390/en18236309 (registering DOI) - 30 Nov 2025

Abstract

In an era prioritizing sustainability, the energy sector plays a pivotal yet complex role in shaping future development. Its transition is strongly influenced by legal and decision-making frameworks, which require adaptation to rapidly changing technological and market conditions. This article investigates national and [...] Read more.

In an era prioritizing sustainability, the energy sector plays a pivotal yet complex role in shaping future development. Its transition is strongly influenced by legal and decision-making frameworks, which require adaptation to rapidly changing technological and market conditions. This article investigates national and international legal structures that regulate and facilitate the transformation toward sustainable energy systems. A Systematic Literature Review, complemented by a Classical Literature Review and bibliometric mapping using VOSviewer, is used to identify and visualize key research areas at the intersection of energy policy, environmental law and managerial decision making. The analysis reveals a fragmented legal landscape structured around six main thematic clusters, covering core energy markets, environmental regulation, comparative legal analyses, efficiency and commerce, digital transformation and energy policy and security. These clusters highlight specific regulatory strengths, such as well-developed sectoral market rules, as well as gaps, including uneven enforcement of environmental norms, limited integration of climate objectives into sectoral regulations and a lag between technological innovation and legal frameworks. Building on these findings, this article introduces the concept of a compensatory model of energy law, which combines preventive, corrective and restorative instruments to distribute the costs and benefits of the energy transition more fairly. This study contributes to the academic and policy debate by clarifying how legal governance and managerial strategies jointly shape the trajectory of the energy sector’s transformation and by outlining directions for future research and regulatory reform. Full article

(This article belongs to the Special Issue Recent Advances in Renewable Energy Economics and Policy)

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17 pages, 1509 KB

Open AccessArticle

Impact of Elevated Wall Temperatures on Nitrate Salt Stability in Thermal Energy Storage

by Freerk Klasing and Thomas Bauer

Energies 2025, 18(23), 6308; https://doi.org/10.3390/en18236308 (registering DOI) - 30 Nov 2025

Abstract

Energy storage is vital for on-demand electricity generation from renewable sources like wind and solar. Besides employing batteries, retrofitting conventional fossil-fired power plants with thermal energy storage might present a highly cost-effective solution. State-of-the-art molten salt storage systems currently operate at a maximum [...] Read more.

Energy storage is vital for on-demand electricity generation from renewable sources like wind and solar. Besides employing batteries, retrofitting conventional fossil-fired power plants with thermal energy storage might present a highly cost-effective solution. State-of-the-art molten salt storage systems currently operate at a maximum temperature of 565 °C. At a higher permanent temperature, nitrate salts start to decompose. The actual wall temperatures of power components for heating, such as solar receivers and electrical heaters, may exceed temperature limits. To date, there is no clear threshold identified up to which heating surfaces in contact with nitrate salt can be operated without leading to the degradation of the salt, which is inevitably followed by increased corrosivity. In this study, possible mechanisms affecting the maximum permissible wall temperature of heating surfaces are identified. The local production of oxygen and nitrite at hot surfaces and its accumulation in the entire system is looked at in an experiment with 9.3 kg of nitrate salt. The effect of high wall temperatures on the evolution of oxygen and nitrite content over time is monitored and analyzed. Parametric studies with an experimentally validated physical model focusing on the nitrate/nitrite equilibrium reveal major influencing factors, with wall temperatures significantly exceeding current design limits. These findings potentially allow for more compact and cost-effective heating components. This work supports the advancement of high-temperature thermal energy storage systems essential for the scalability and economic competitiveness of renewable energy infrastructure. Full article

(This article belongs to the Section D: Energy Storage and Application)

40 pages, 4617 KB

Open AccessArticle

Sustainability Assessment of Dry Reforming of Methane via Carbon Intensity and Syngas Energy Recovery Analysis

by Sheila Devasahayam, John Samuel Thella and Manoj K. Mohanty

Energies 2025, 18(23), 6307; https://doi.org/10.3390/en18236307 (registering DOI) - 30 Nov 2025

Abstract

This study conducts a comprehensive sustainability assessment of Dry Reforming of Methane (DRM), focusing on carbon intensity and syngas energy recovery (%) as primary performance indicators. By combining thermodynamic analysis with physics-informed machine learning (ML) models, DRM performance is evaluated across a range [...] Read more.

This study conducts a comprehensive sustainability assessment of Dry Reforming of Methane (DRM), focusing on carbon intensity and syngas energy recovery (%) as primary performance indicators. By combining thermodynamic analysis with physics-informed machine learning (ML) models, DRM performance is evaluated across a range of operating conditions. Incorporating reaction enthalpy, carbon intensity, and syngas energy recovery as engineered features substantially improves model accuracy over baseline and kinetic models. Monte Carlo simulations are used to quantify uncertainty and identify robust operating windows, while techno-economic analysis benchmarks DRM against Steam Methane Reforming (SMR) and electrolysis. The results demonstrate that DRM can achieve syngas energy recovery values up to 190% and carbon intensity as low as 0.17, underscoring its promise as a competitive, low-carbon pathway for hydrogen and syngas production. Full article

(This article belongs to the Special Issue New Materials, Catalyst and Advances in Hydrogen Energy Production)

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38 pages, 3351 KB

Open AccessArticle

Analysis and Evaluation of the Operating Profile of a DC Inverter in a PV Plant

by Silvia Baeva, Ivelina Hinova and Plamen Stanchev

Energies 2025, 18(23), 6306; https://doi.org/10.3390/en18236306 (registering DOI) - 30 Nov 2025

Abstract

The inverter is the key element that converts the intermittent DC power of the PV array into a quality AC flow to the grid and simultaneously performs functions such as power factor control, reactive services, and grid code compliance. Therefore, the detailed operating [...] Read more.

The inverter is the key element that converts the intermittent DC power of the PV array into a quality AC flow to the grid and simultaneously performs functions such as power factor control, reactive services, and grid code compliance. Therefore, the detailed operating profile of the inverter, how the power, dynamics, power quality, and efficiency evolve over time, is critical for both the scientific understanding of the system and the daily operation (O&M). Monitoring only aggregated energy indicators or single KPIs (e.g., PR) is often insufficient: it does not distinguish weather-related variations from technical limitations (clipping, curtailment), does not show dynamic loads (ramp rate), and does not provide confidence in the quality of the injected energy (PF, P–Q behavior). These deficiencies motivate research that simultaneously covers the physical side of the conversion, the operational dynamics, and the climatic reference of the resource. The analysis covers the window of 25 January–15 April 2025 (winter→spring). Due to the pronounced seasonality of the solar resource and temperature regime, all quantitative results and conclusions regarding efficiency, dynamics, clipping, and degradation are valid only for this window; generalizations to other seasons require additional data. In the next stage, we will add ≥12 months of data and perform a comparable seasonal analysis. Full specifications of the measuring equipment (DC/AC current/voltage, clock synchronization, separate high-frequency

P Q

-logger) and quantitative uncertainty estimates, including distribution to key indicators (

η

,

P R

,

T H D

,

I_{D C}

), are presented. The PVGIS per-kWp climate reference is anchored to the nameplate DC peak and cross-checked against percentile scaling;

a \pm ε

scale error shifts

P R

by

ε

and changes

Δ E

proportionally only on hours with

\hat{P} > P

. The capacity for the climate reference (PVGIS per-kWp) is calibrated to the tabulated DC peak power

C_{c e r t}

and is cross-validated using a percentile scale (

Q_{0.99}

). Full article

(This article belongs to the Special Issue Challenges and Opportunities in the Global Clean Energy Transition)

23 pages, 11924 KB

Open AccessArticle

An Ensemble Learning Framework for Cyber Attack and Fault Discrimination in Smart Grids

by Anass Naqqad, Abdellah Boulal and Rachid Habachi

Energies 2025, 18(23), 6305; https://doi.org/10.3390/en18236305 (registering DOI) - 30 Nov 2025

Abstract

In recent years, smart grid security has gained considerable attention. Numerous studies have proposed techniques to detect cyber-attacks using sensor data; however, limited attention has been given to distinguishing cyber intrusions from physical faults in the power grid. In this paper, we present [...] Read more.

In recent years, smart grid security has gained considerable attention. Numerous studies have proposed techniques to detect cyber-attacks using sensor data; however, limited attention has been given to distinguishing cyber intrusions from physical faults in the power grid. In this paper, we present a supervised intrusion–disturbance classification pipeline to accurately differentiate physical faults from cyber-attacks. First, we augment raw channels with relation-centered features to emphasize relative contrasts and suppress common-mode effects, then we apply embedded feature selection via LightGBM to retain a compact, informative subset. Class imbalance is addressed through class weighting, and an Extremely Randomized Trees classifier serves as the core learner. Experiments on 15 datasets cover both binary (Attack vs. Natural) and multiclass (Attack/Natural/NoEvents) regimes. The approach attains 98.44% mean accuracy for the binary task and 98.22% for the multiclass task, demonstrating consistent discrimination between cyber-attacks, physical faults, and normal operation. The results indicate that relational features combined with embedded selection and a tree ensemble offer a practical, accurate alternative to heavier deep models for smart-grid monitoring. Full article

(This article belongs to the Section A1: Smart Grids and Microgrids)

25 pages, 2342 KB

Open AccessArticle

Efficiency of MPC Framework Cast to a Linear Programming Problem for a Servo Drive with Model Uncertainty

by Dariusz Horla, Piotr Pinczewski and Weronika Horla

Energies 2025, 18(23), 6304; https://doi.org/10.3390/en18236304 (registering DOI) - 30 Nov 2025

Abstract

Thepaper presents an efficient model predictive control framework formulated as a linear programming problem to control a servo drive with model uncertainty considerations from the viewpoint of the control performance. The model predictive framework is used to adopt

L_{1}

-type cost functions [...] Read more.

Thepaper presents an efficient model predictive control framework formulated as a linear programming problem to control a servo drive with model uncertainty considerations from the viewpoint of the control performance. The model predictive framework is used to adopt

L_{1}

-type cost functions using absolute tracking errors, providing computational efficiency and enabling real-time implementation. A key contribution is the deployment of this approach on real hardware in a hardware-in-the-loop setting, supported by fully open-source code for Simulink Coder and C environments, verifying the solution scheme in real time. Experimental validation on a servo drive demonstrates the system’s tolerance for parameter uncertainties with slight performance degradation, resulting in an up to 18% increase in the considered control quality measure, between nominal parameters’ values and the worst configuration. The proposed linear programming approach enables constraint handling imposed on control signals and supports the arbitrary choice of prediction horizons and sampling intervals. The paper also includes a comprehensive derivation of the control law, controller implementation details, and stepwise experimental results showcasing the impact of uncertainties on control performance. This work and the attached code enable the authors to easily reproduce the proposed approach and extend it in their applications. Full article

20 pages, 3890 KB

Open AccessArticle

Analytical Modeling and GA-Based Optimization of Multi-Layered Segmented SPM Magnets

by Choayeb Barchouchi, Matthew Franchek and Yingjie Tang

Energies 2025, 18(23), 6303; https://doi.org/10.3390/en18236303 (registering DOI) - 30 Nov 2025

Abstract

Presented here is a 2-D analytical model for predicting the magnetic field distribution in a surface-mounted permanent magnet (SPM) rotor with multi-layered segmented permanent magnets (PMs). Each layer is treated independently, enabling the linear superposition of magnetic fields across all layers. The model [...] Read more.

Presented here is a 2-D analytical model for predicting the magnetic field distribution in a surface-mounted permanent magnet (SPM) rotor with multi-layered segmented permanent magnets (PMs). Each layer is treated independently, enabling the linear superposition of magnetic fields across all layers. The model employs subdomain modeling combined with the separation of variables, with the magnetic vector potential expressed as a Fourier series to derive the airgap magnetic field. The formulation is generalizable to five regions in each layer: outer airgap, optional outer inactive magnetic layer, active magnetic layer(s), optional inner inactive magnetic layer, and inner airgap. Validation against finite element analysis (FEA) shows a prediction difference of around 0.5% in airgap flux density. The model’s design utility is demonstrated through a genetic algorithm (GA) optimization, which maximizes static flux linkage and confirms performance improvements from the multi-layered configuration. Full article

40 pages, 1885 KB

Open AccessReview

Advancing Hybrid AC/DC Microgrid Converters: Modeling, Control Strategies, and Fault Behavior Analysis

by Mostafa Jabari, Mohammad Ghoreishi, Tommaso Bragatto, Francesca Santori, Massimo Cresta, Alberto Geri and Marco Maccioni

Energies 2025, 18(23), 6302; https://doi.org/10.3390/en18236302 (registering DOI) - 30 Nov 2025

Abstract

Hybrid AC/DC microgrids (HMGs) are pivotal for integrating renewable resources, yet their stability and resilience are fundamentally constrained by the power electronic converters that interface them. This paper provides a critical review and synthesis of the co-dependent advancements in HMG converter topologies, control [...] Read more.

Hybrid AC/DC microgrids (HMGs) are pivotal for integrating renewable resources, yet their stability and resilience are fundamentally constrained by the power electronic converters that interface them. This paper provides a critical review and synthesis of the co-dependent advancements in HMG converter topologies, control strategies, and fault management. Through a systematic analysis of the state of the art, this review examines the evolution from classical control to intelligent, software-defined converter functions. The analysis reveals a fundamental bifurcation in design philosophy between low-voltage (LV) and medium-voltage (MV) systems, driven by a trade-off between power density Gallium Nitride (GaN) and systemic reliability silicon carbide (SiC). Furthermore, it highlights the rise of virtualization, namely virtual Inertia control (VIC) and adaptive virtual impedance control (AVIDC), as a dominant paradigm to compensate for the physical limitations of low-inertia, resistive grids. Finally, this review identifies a critical, synergistic dependency in fault management, where ultra-fast solid-state circuit breakers (SSCBs) guarantee the survivability of vulnerable voltage source converters (VSCs), which in turn enables software-based resilience via fault ride-through (FRT). This synthesis concludes that the converter has become the intelligent nexus of the HMG and identifies the primary barriers to widespread adoption as the computational, economic, and standardization gaps in this new cyber–physical domain. Full article

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17 pages, 3878 KB

Open AccessArticle

A Methodology for Deriving Conversion Coefficients of Natural Infiltration Using Airtightness Data

by Sujin Lim, Su-ji Choi, Jiajun Jing and Jae-hun Jo

Energies 2025, 18(23), 6301; https://doi.org/10.3390/en18236301 (registering DOI) - 30 Nov 2025

Abstract

The commonly used conversion coefficient for natural infiltration rates (N) is derived from single-zone or low-rise building assumptions and therefore fails to account for the substantial pressure differences driven by building height and seasonal temperature variations. These induced pressure differences significantly [...] Read more.

The commonly used conversion coefficient for natural infiltration rates (N) is derived from single-zone or low-rise building assumptions and therefore fails to account for the substantial pressure differences driven by building height and seasonal temperature variations. These induced pressure differences significantly impact on the variations in infiltration rates within high-rise buildings, particularly during heating and cooling seasons. Therefore, this study develops a floor-resolved methodology for deriving N in high-rise buildings under various seasonal conditions, through extending the effective leakage area (ELA) model and incorporating normalization procedures that reflect seasonal and environmental conditions. Application of this method to high-rise buildings in South Korea shows that both infiltration rates and N values at upper and lower floors exceed those near the neutral pressure level (NPL) by more than a factor of two under winter conditions. Moreover, the derived N values deviate substantially from the commonly assumed reference value of 20 and vary systematically with floor height and season. These findings indicate that using a uniform N value can lead to considerable errors in estimating infiltration and associated energy loads, underscoring the necessity of height- and climate-specific conversion coefficients for accurate energy performance assessment. Full article

(This article belongs to the Special Issue Integrated Building Design: Balancing Comfort and Environmental Performance)

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20 pages, 1308 KB

Open AccessArticle

Energy Costs and the Financial Situation of Farms in the European Union

by Agnieszka Strzelecka, Ewa Szafraniec-Siluta and Danuta Zawadzka

Energies 2025, 18(23), 6299; https://doi.org/10.3390/en18236299 (registering DOI) - 30 Nov 2025

Abstract

Within the energy system, agriculture represents a distinct sector, as it functions both as a consumer of energy derived from fossil fuels and renewable sources and as a producer of renewable energy. Since energy consumption is closely linked to production intensity and cost [...] Read more.

Within the energy system, agriculture represents a distinct sector, as it functions both as a consumer of energy derived from fossil fuels and renewable sources and as a producer of renewable energy. Since energy consumption is closely linked to production intensity and cost efficiency, energy costs have a direct impact on farm profitability and financial stability. The aim of the study is to analyze and assess the relationships between energy costs and the financial situation of farms in Poland in comparison to the European Union average, based on data from the Farm Accountancy Data Network (FADN) and its successor, the Farm Sustainability Data Network (FSDN), covering the years 2014–2023. The study focuses on differences in the structure and burden of energy costs and their implications for the economic performance and financial resilience of agricultural holdings. The comparative analysis revealed that farms in Poland are characterized by a higher share of energy costs in total production costs and a higher ratio of energy costs to total income compared to the EU average, indicating lower financial resilience to energy price volatility. These findings suggest that measures aimed at improving energy efficiency, supporting technological modernization, and encouraging the adoption of on-farm renewable energy could strengthen the long-term stability and competitiveness of Polish agriculture. Full article

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