Search Results (8,166)

Power system models of electric systems are crucial in system planning for operations, economics, and expansion analyses. However, as these models contain critical infrastructure data, they are not publicly available. This poses challenges in future expansion scenarios and evaluating technological advancements in an electric grid. Synthetic models are realistic power system models, both topologically and operationally. However, since the electrical network is typically produced using statistical data and often uses machine learning, it does not contain propriety information. This allows researchers to evaluate system behavior under various operating conditions and as test cases for emerging technologies. These test cases are particularly important in highly evolving electric grids and areas of high renewable energy integration such as Alaska. Currently, no publicly available benchmark power system models of rural Alaskan island microgrids exist. This paper presents a rural Alaskan microgrid synthetic power system model and the methodology adopted to develop the model. The performance of the developed synthetic grid was assessed through steady state and positive-sequence dynamic simulations under various operating conditions. Full article

Network protector units (NPUs) are crucial parts of the protection of secondary networks to effectively isolate faults occurring on the primary feeders. When a fault occurs on the primary feeder, there is a path of the fault current going through the service transformers that causes a negative flow of current on the NPU connected to the faulted feeder. Conventionally, NPUs rely on the direction of current with respect to the voltage to detect faults and make a correct trip decision. However, the conventional NPU logic does not allow the reverse power flow caused by distributed energy resources installed on secondary networks. The communication-assisted direct transfer trip logic for NPUs can be used to address this challenge. However, the communication-assisted scheme is exposed to some vulnerabilities arising from the disruption or corruption of the communicated data that can endanger the reliable operation of NPUs. This paper evaluates the impact of the malfunction of the communication system on the operation of communication-assisted NPU logic. To this end, the impact of packet modification and denial-of-service cyberattacks on the communication-assisted scheme are evaluated. The evaluation was performed using a hardware-in-the-loop (HIL) co-simulation testbed that includes both real-time power system and communication network digital simulators. This paper evaluates the impact of the cyberattacks for different fault scenarios and provides a list of recommendations to improve the reliability of communication-assisted NPU protection. Full article

Underground electrical conductors, both medium-and high-voltage, play a crucial role in energy infrastructure. However, they present a maintenance challenge due to their difficult access. Unlike overhead installations, these cables remain hidden, making it harder to obtain key parameters, such as their temperature or structural condition, in a simple manner. Current temperature measurement methods, including fiber-optic-based systems (DTS and LTS), involve high costs that limit their feasibility in medium-voltage networks, where more economically accessible alternatives are required. This study introduces an alternative system for monitoring the temperature of underground cables using NTC thermistors. Its design allows for reducing the number of connection conductors for sensors to just four regardless of the number of measurement points. The implemented measurement technique is based on the sequential activation of sensors and the integration of the recorded current to achieve an accurate thermal assessment. The tests conducted validate that this proposal represents an efficient, cost-effective, and highly scalable solution for implementation in electrical distribution networks. Full article

Emerging power electronic devices like soft open points (SOPs) and electric springs (ESs) play a vital role in enhancing active distribution network (ADN) efficiency. SOPs enable flexible active/reactive power control, while ESs improve demand-side management and voltage regulation. This paper proposes a two-stage stochastic programming model to optimize ADN’s operation by coordinating these fast-response devices with legacy mechanical equipment. The first stage determines hourly setpoints for conventional devices, while the second stage adjusts SOPs and ESs for intra-hour control. To handle ES nonlinearities, a hybrid data–knowledge approach combines knowledge-based linear constraints with a data-driven multi-layer perceptron, later linearized for computational efficiency. The resulting mixed-integer second-order cone program is solved using commercial solvers. Simulation results show the proposed strategy effectively reduces power loss by 42.5%, avoids voltage unsafety with 22 time slots, and enhances 4.3% PV harvesting. The coordinated use of SOP and ESs significantly improves system efficiency, while the proposed solution methodology ensures both accuracy and over 60% computation time reduction. Full article

This paper investigates the complex dynamics and fractal attractors that arise in a 60-dimensional ring lattice system of electrically coupled nonchaotic Rulkov neurons. While networks of chaotic Rulkov neurons have been widely studied, systems of nonchaotic Rulkov neurons have not been extensively explored due to the piecewise complexity of the nonchaotic Rulkov map. Here, we find that rich dynamics emerge from the electrical coupling of regular-spiking Rulkov neurons, including chaotic spiking, synchronized chaotic bursting, and synchronized hyperchaos. By systematically varying the electrical coupling strength between neurons, we also uncover general trends in the maximal Lyapunov exponent across the system’s dynamical regimes. By means of the Kaplan–Yorke conjecture, we examine the fractal geometry of the ring system’s high-dimensional chaotic attractors and find that these attractors can occupy as many as 45 of the 60 dimensions of state space. We further explore how variations in chaotic behavior—quantified by the full Lyapunov spectra—correspond to changes in the attractors’ fractal dimensions. This analysis advances our understanding of how complex collective behavior can emerge from the interaction of multiple simple neuron models and highlights the deep interplay between dynamics and geometry in high-dimensional systems. Full article

The increase in the popularity of digital terrestrial television broadcasting and the expansion of Greece’s network infrastructure have raised concerns about the possible harmful effects of exposure to long-term radio frequency electromagnetic fields (RF-EMFs) on sensitive groups. This study presents measurements of RF-EMFs generated in three locations of digital terrestrial television broadcast stations of the national public broadcasting company of Greece. The measurements and calculations of the radio frequency (RF) electric-field strength and RF electromagnetic field (EMF) power density were carried out in the near-field and far-field regions of the antenna of a digital television broadcasting station. In these three locations, the results of real measurements were compared to reports by the Greek Atomic Energy Commission (EEAE) and the limit levels of International Commission on Non-Ionizing Radiation Protection (ICNIRP). Full article

This research evaluates the vulnerability of public infrastructure in San Luis parish, Riobamba canton, Ecuador, to the flood risk posed by the Chibunga River under return period scenarios of 10, 50, 100, and 500 years. The main objective was to identify the most exposed systems—such as drinking water, sewerage, power grid, and utility poles—in order to prioritize mitigation measures. The methodology combined hydrometeorological analysis, hydraulic modeling using HEC-HMS and Iber, and the estimation of economic losses through the DaLA methodology. The results reveal that the low vulnerability of the drinking water system, as less than 0.08% of the network’s length, is at risk in the high-to-very-high range, even in a scenario with a 500-year return period. On the other hand, there is evidence of high exposure of the sewerage network in extreme scenarios, considering that 49.15% is at high-to-very-high risk in the worst-case scenario. Furthermore, as the return period increases, there is a growing impact on the electrical network, where the proportion of assets at high-to-very-high risk increases from 0.60% to 6.88% for high voltage, 0.00% to 18.03% for low voltage, and 0.00% to 1.18% for streetlights for a return period of 10 to 500 years. It should be noted that the estimated direct economic losses amount to USD 84,162.86 when taking into account the worst-case scenario. In this regard, the novelty of this study lies in the integration of technical, hydraulic, and economic analyses for a scarcely studied rural Andean area, providing crucial data for preventive risk management. It concludes that investment in prevention is more cost-effective than post-disaster reconstruction, recommending the strengthening of the sewerage system’s hydraulic capacity and the optimization of electrical infrastructure protection. Full article

To enhance the accuracy and robustness of lithium-ion battery state-of-health (SOH) prediction, this study proposes a dual-mode intelligent optimization BP neural network model (AO–AVOA–BP) which integrates the Aquila Optimizer (AO) and the African Vulture Optimization Algorithm (AVOA). The model leverages the global search capabilities of AO and the local exploitation strengths of AVOA to achieve efficient and collaborative optimization of network parameters. In terms of feature construction, eight key health indicators are extracted from voltage, current, and temperature signals during the charging phase, and the optimal input set is selected using gray relational analysis. Experimental results demonstrate that the AO–AVOA–BP model significantly outperforms traditional BP and other improved models on both the NASA and CALCE datasets, with MAE, RMSE, and MAPE maintained within 0.0087, 0.0115, and 1.095%, respectively, indicating outstanding prediction accuracy and strong generalization performance. The proposed method demonstrates strong generalization capability and engineering adaptability, providing reliable support for lifetime prediction and safety warning in battery management systems (BMS). Moreover, it shows great potential for wide application in the health management of electric vehicles and energy storage systems. Full article

Distribution System Operators (DSOs) increasingly need planning tools that coordinate utility-influenced assets—such as electric-vehicle charging stations (EVCS) and voltage-support resources—with customer-sited distributed generation (DG). We present a Nash-equilibrium-based Iterative Best Response Algorithm (IBRA-NE) for joint planning of DG and EVCS in radial distribution networks. The framework supports two applicability modes: (i) a DSO-plannable mode that co-optimizes EVCS siting/sizing and utility-controlled reactive support (DG operated as VAR resources or functionally equivalent devices), and (ii) a customer-sited mode that treats DG locations as fixed while optimizing DG reactive set-points/sizes and EVCS siting. The objective minimizes network losses and voltage deviation while incorporating deployment costs and EV charging service penalties, subject to standard operating limits. A backward/forward sweep (BFS) load flow with Monte Carlo simulation (MCS) captures load and generation uncertainty; a Bus Voltage Deviation Index (BVDI) helps identify weak buses. On the EEU 114-bus system, the method reduces base-case losses by up to 57.9% and improves minimum bus voltage from 0.757 p.u. to 0.931 p.u.; performance remains robust under a 20% load increase. The framework explicitly accommodates regulatory contexts where DG siting is customer-driven by treating DG locations as fixed in such cases while optimizing EVCS siting and sizing under DSO planning authority. A mixed scenario with 5 DGs and 3 EVCS demonstrates coordinated benefits and convergence properties relative to PSO, GWO, RFO, and ARFO. Additionally, the proposed algorithm is also tested on the IEEE 69-bus system and results in acceptable performance. The results indicate that game-theoretic coordination, applied in a manner consistent with regulatory roles, provides a practical pathway for DSOs to plan EV infrastructure and reactive support in networks with uncertain DER behavior. Full article

This paper presents a detailed, measurement-based assessment of interharmonic, harmonic, and supraharmonic emissions from a Battery Energy Storage System (BESS) supporting electric vehicle (EV) fast charging. In contrast to prior literature, which is largely simulation-based and often neglects interharmonic and even harmonic components, this study provides real-world data under dynamic operating conditions. Emission limits are established in accordance with relevant international standards, with the observed deviations from standard practices highlighted in existing studies. The operation of the BESS-assisted fast-charging system is classified into five distinct operating stages, and the variations in spectral emissions across these stages are analyzed. A comparative evaluation with a grid-fed fast charger reveals the influence of BESS integration on power quality. Notably, the analysis shows a significant increase in even harmonics during EV charging events. This component is identified as the limiting factor in the network’s harmonic hosting capacity, underscoring the need to account for even harmonics in future grid compatibility assessments. These findings provide valuable insights for grid operators, EV infrastructure planners, and standardization bodies aiming to ensure compliance with power quality standards in evolving charging scenarios. Full article

To address the issue of insufficient coordination of local contextual information in lithium-ion battery state-of-charge (SOC) estimation, this paper proposes a two-branch contextual temporal attention model based on a modified recurrent neural network (TRNN-CTA). This model combines a bidirectional recurrent neural network (BIRNN) branch structure with a contextual temporal attention (CTA) mechanism, effectively addressing the limited generalization capabilities of traditional models in conditions such as operating-condition switching, temperature variations, and capacity differences. Experiments on the CALCE dataset demonstrate that the TRNN-CTA model significantly outperforms traditional models in SOC estimation under the US06 operating condition, with R², RMSE, and MAE values of 0.99987, 0.263%, and 0.199%, respectively. Further feature dimension expansion, model simplification, and model generalization experiments verify that the TRNN-CTA model can stably and accurately estimate battery SOC across various operating conditions, temperatures, and capacities. Specifically, when the feature dimension is expanded from 2 to 6, the accuracy improves by approximately 30%, while the TRNN-CTA model achieves a 70% reduction in error compared to the baseline model. In summary, the TRNN-CTA model proposed in this paper provides a new solution for predicting the SOC of lithium-ion batteries in hybrid electric vehicles. This research result will provide certain technical support in this field. Full article

Accurate and reliable characterization of current transformer (CT) performance is essential for maintaining grid stability and power quality in modern electrical networks. CT measurements are key to effective monitoring of harmonic distortions, supporting regulatory compliance and ensuring the safe operation of the grid. This paper addresses a method for the characterization of CTs across an extended frequency range from 50 Hz up to 150 kHz, driven by increasing power quality issues introduced by renewable energy installations and non-linear loads. Traditional CT calibration approaches involve measurement setups that offer ppm-level uncertainty but are complex to operate and limited in practical frequency range. To simplify and expand calibration capabilities, a calibration system employing a sampling ammeter (power analyzer) was developed, enabling the direct measurement of CT secondary currents of an unknown CT and a reference CT without any further auxiliary equipment. The resulting expanded magnitude ratio uncertainties for the wideband CT calibration system are 10 ppm ($k=2$) up to 10 kHz and less than 120 ppm from 10 kHz to 150 kHz; these uncertainties do not include the uncertainty of the reference CT. Additionally, the operational conditions and setup design choices, such as instrument warm-up duration, grounding methods, measurement shunt selection, and cable type, were evaluated for their impact on measurement uncertainty and repeatability. The results highlight the significance of minimizing parasitic impedances at higher frequencies and maintaining consistent testing conditions. The developed calibration setup provides a robust foundation for future standardization efforts and practical guidance to characterize CT performance in the increasingly important supraharmonic frequency range. Full article

With the rapid rise in electric vehicle (EV) adoption, the deployment of EV charging infrastructure—particularly fast-charging stations—has expanded significantly to meet growing energy demands. While fast charging offers the advantage of reduced charging time and improved user convenience, it imposes considerable stress on existing power distribution systems due to its high power and current requirements. This study investigated the impact of EV fast charging on power quality within Thailand’s distribution network, emphasizing compliance with accepted standards such as IEEE Std 519-2014. We developed a control-oriented EV-charging station model in power systems computer-aided design and electromagnetic transients, including DC (PSCAD/EMTDC), which integrates grid-side vector control with DC fast-charging (CC/CV) behavior. Active/reactive power setpoints were mapped onto $dq$ current references via Park’s transformation and regulated by proportional integral (PI) controllers with sinusoidal pulse-width modulation (SPWM) to command the voltage source converter (VSC) switches. The model enabled dynamic studies across battery state-of-charge and staggered charging schedules while monitoring voltage, current, and total harmonic distortion (THD) at both transformer sides, charger AC terminals, and DC adapters. Across all scenarios, the developed control achieved grid-current THDi of <5% and voltage THD of <1.5%, thereby meeting IEEE 519-2014 limits. These quantitative results show that the proposed, implementation-ready approach maintains acceptable power quality under diverse fast-charging patterns and provides actionable guidance for planning and scaling EV fast-charging infrastructure in Thailand’s urban networks. Full article

This research focused on determining the technical and economic feasibility of the design of a solar-powered electric vehicle charging station (EVCS) in Cairo, Egypt. Using HOMER Grid, hybrid system configurations are assessed technically and economically to reduce costs and ensure reliability. These systems incorporate photovoltaic (PV) systems, lithium-ion battery energy storage systems (ESS), and diesel generators. A comprehensive analysis was conducted in Cairo, Egypt, focusing on small vehicle charging needs in both grid-connected and generator-supported scenarios. In this study, a 468 kW PV array integrated with 29 units of 1 kWh lithium-ion batteries and supported by time-of-use (TOU) tariffs, were used to optimize energy utilization. This study demonstrated the feasibility of the system in a case of eight chargers of 150 kW each and forty chargers of 48 kW. Conclusions suggest that the PV + ESS has the lowest pure power costs and reduced carbon emissions compared to traditional network-dependent solutions. The optimal configuration of USD 10.23 million over 25 years, with lifelong savings, results in annual savings of tool billing of around USD 409,326. This study concludes that a solar-powered EVC in Egypt is both technically and economically attractive, especially in the light of increasing energy costs. Full article

With the development of dynamic wireless power transfer (DWPT) technology, the introduction of wireless charging lanes (WCLs) in traffic systems is seen as a promising trend for electrified transportation. Though there has been extensive discussion about the planning and allocation of WCLs in different situations, studies on traffic control models for WCLs are relatively lacking. Thus, this paper aims to design a coordinated optimization strategy for managing electric vehicle (EV) traffic on an expressway network, which integrates a corridor traffic flow model with a wireless power transmission model. Two components are considered in the control objective: the total energy increased for the EVs and the total number of EVs served by the expressway, over the problem horizon. By setting the trade-off coefficients for these two objectives, our model can be used to achieve mixed optimization of WCL traffic management. The decisions include metering of different on-ramps as well as routing plans for different groups of EVs defined by origin/destination pairs and initial SOC levels. The control problem is formulated as a novel linear programming model, rendering an efficient solution. Numerical examples are used to verify the effectiveness of the proposed traffic control model. The results show that with the properly designed traffic management strategy, a notable increase in charging performance can be achieved by compromising slightly the traffic performance while maintaining overall smooth operation throughout the expressway system. Full article