journal: International Journal of Emerging Electric Power Systems

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International Journal of Emerging Electric Power Systems

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Sprache: Englisch

Erstveröffentlichung: 1. Januar 2004

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Objective
International Journal of Emerging Electric Power Systems (IJEEPS) publishes significant research and scholarship related to latest and up-and-coming developments in power systems. The mandate of the journal is to assemble high quality papers from the recent research and development efforts in new technologies and techniques for generation, transmission, distribution and utilization of electric power.

Topics
The range of topics includes:

electric power generation sources
integration of unconventional sources into existing power systems
generation planning and control
new technologies and techniques for power transmission, distribution, protection, control and measurement
power system analysis, economics, operation and stability
deregulated power systems
power system communication
metering technologies
demand-side management
industrial electric power distribution and utilization systems

Article formats
Research articles, reviews

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Geschichte

Content available since 2004 (Volume 1, Issue 1)

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The impact of different electric vehicle penetration on distribution networks and investigation of mitigation strategies

13. Mai 2026

Ahmet Burak Kaba, Rasim Doğan, Emre Akarslan

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The rapid increase in electric vehicle (EV) adoption introduces significant operational challenges for low-voltage distribution networks. This study evaluates the impact of increasing EV penetration on a real residential distribution feeder in Afyonkarahisar, Türkiye, and investigates the effectiveness of different mitigation strategies. Simulations are conducted using the OpenDSS under multiple EV penetration scenarios, focusing on voltage deviations, thermal loading, and violation durations. The results reveal that thermal (ampacity) constraints become binding earlier and more severely than voltage limits as EV penetration increases. Uncoordinated time-of-use (TOU) charging is shown to increase load coincidence, leading to higher peak currents, whereas conservation voltage reduction (CVR) provides only limited mitigation under high loading conditions. In contrast, centralized charging coordination based on Open Charge Point Protocol effectively reduces peak demand by distributing charging sessions over time. Furthermore, battery storage systems (BSS) significantly mitigate thermal violations by providing localized peak shaving support. Quantitative results indicate that coordinated charging reduces the number of thermal violations substantially, while BSS deployment enables the network to accommodate higher EV penetration levels without exceeding operational limits. The findings highlight the critical role of coordinated charging and energy storage in enabling high EV integration and provide practical insights for distribution system operators in planning and managing future low-voltage networks.
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Distributed new energy distribution network structure optimization method based on X structure steiner minimum tree

7. Mai 2026

Fei Zheng, Ludong Chen, Ning Luo, Qingyu Zhao, Guang Liu

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The optimization of distribution network structure is a key technology for improving energy utilization efficiency and ensuring power supply reliability, especially in scenarios with large-scale integration of distributed renewable energy. Traditional distribution networks face challenges such as insufficient adaptability and high losses. In response to the large-scale and complex nature of distributed renewable energy distribution networks, this paper proposes a method for optimizing distribution network structure based on the X-structure Steiner minimum tree. This method obtains an optimal structural routing tree by introducing Steiner points, thereby shortening the total line length as much as possible, reducing load losses, and improving power supply quality. With the objective of minimizing total load loss and under constraints including line current and voltage limits, the X-structure Steiner minimum tree algorithm is used to introduce Steiner points into the distribution network, thereby achieving X-structure routing for the distribution network. The particle swarm optimization (PSO) algorithm is employed to solve for the optimal X-structure routing tree and realize distribution network structure optimization. The results show that after optimization using this method, the length of power supply paths in the distribution network is significantly shortened, and load losses at various load points are substantially reduced, effectively ensuring the power supply quality of distributed renewable energy distribution networks.
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Neural network-based power forecasting framework for solar PV plants under high soiling and degradation conditions

28. April 2026

Ankit Pal, Subhajit Ghosh, Aneesh Nath, G. Saravana Ilango

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Soiling and degradation are two major challenges that reduce the performance and forecasting accuracy of solar photovoltaic (PV) systems. While degradation effects have been studied, the combined influence of soiling and degradation on power forecasting remains largely unexplored. Soiling is particularly difficult to model because it has no direct correlation with irradiance or temperature and varies with cleaning schedules. As a result, power output can differ under identical environmental conditions depending on the soiling ratio (SR), leading to increasing forecasting errors. This study presents a transformer-based forecasting framework that explicitly corrects for both soiling and degradation. The proposed method first removes soiling effects from historical data, enabling the model to learn clean generation patterns. Forecasted power is then adjusted in real time using the SR. To handle degradation, the model employs periodic retraining (PR), maintaining accuracy as system capacity decreases. Tested on a 504 kWp rooftop PV plant, the framework achieved a mean relative error of 3.57 %, RMSE of 30 kW, and MAPE of 9.8 % over one year. Long-term analysis shows RMSE reduction of 32 % and MAPE reduction of 69 % over 20 years, confirming its robustness for reliable PV forecasting.
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Development of a reduced-switch nine-level inverter with low voltage stress for grid integration

27. April 2026

Jami Rajesh, Suresh Katta, Usha Bala Varanasi, Naga Venkata Vamshi Kumar Vanapalli, Pulavarthi Satya Venkata Kishore, Nakka Jayaram

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Multilevel inverters have gained significant attention in medium-voltage and grid-connected applications due to their ability to generate high-quality output voltage with reduced harmonic distortion. However, conventional nine-level inverter topologies generally require a large number of power switches, capacitors, and voltage-balancing circuits, which increase system complexity and cost. This manuscript proposes a reduced-switch nine-level inverter topology based on the switched-capacitor technique to minimize component count while maintaining high-quality multilevel output. The proposed topology employs a modular structure and operates in both symmetrical and asymmetrical configurations, while inherent capacitor voltage balancing is achieved using a level-shifted pulse-width modulation scheme without requiring additional sensors or balancing circuits. Furthermore, 50 % of the power switches experience only 50 % of the total DC-link voltage stress, which improves device reliability and enables the use of lower-rated switches. The proposed inverter produces a high-quality nine-level output voltage with reduced component count and lower voltage stress compared with existing topologies. The feasibility and effectiveness of the proposed inverter are validated through MATLAB/Simulink simulations and experimental verification using a prototype hardware setup.
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Mitigation of the effects of grid voltage disturbances on DFIG wind farm power conversion efficiency based on on-site measurements analysis

23. April 2026

Taghi Mehdi, Hocine Labar, Mounia Samira Kelaiaia, Ahmed Yarba

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The control and power production of a Doubly Fed Induction Generator (DFIG) wind turbine are highly dependent on grid parameters. To reach the maximum power point (MPPT) and hence to maximize the power output from the wind energy system, the MPPT algorithms used are generally dependent on the grid voltage measurements. Therefore, any deviation of the grid voltage from its rated value can reduce both the power production efficiency and the reactive power performance of the wind turbine. The main sources of these deviations are voltage unbalance and grid disturbances. Deep investigations of a year of data from the Nouadhibou wind farm located in Mauritania, have shown that DFIG wind turbines are very sensitive to the operating conditions defined by the grid code. This grid code specifies two operation modes: unlimited temporal operation and limited operation. In many situations, the wind farm exceeds the allowed time for limited operation, leading to grid disconnection. This paper proposes a new reactive power control strategy to reduce DFIG’s sensitivity to grid voltage variations. The proposed control compares the measured Phase-Locked Loop (PLL) signal with the reference voltage. Based on this comparison, the controller chooses the suitable combination of capacitors to generate or absorb the required reactive power for voltage regulation. This method allows the wind turbine to remain in unlimited operation mode, preventing unwanted disconnections. Furthermore, it reduces reactive power exchange between the DFIG and the grid while keeping the Point of Common Coupling (PCC) voltage within optimal limits.
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Experimental performance and analysis of standalone self-excited induction generators considering different fault variations and power quality

21. April 2026

Jotirmoy Samanta, Unmesh Chandra Naik, Yatindra Gopal, Ralli Sangno, Rajen Pudur

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Self-excited induction generators (SEIGs) are suitable for renewable energy applications due to their simple construction, low cost, and minimal maintenance requirements. SEIGs are superior to traditional synchronous generators in edge-of-grid pico-hydro systems because they offer inherent self-excitation and do not require external excitation. This research studies the power quality performance of SEIGs by analyzing voltage regulation, frequency variation, total harmonic distortion (THD), and power factor (PF) under varied rotor speeds and excitation capacitance. The behavior of SEIGs under abnormal operating conditions is also examined through extensive fault analysis, including open circuit faults and short circuit faults such as single line-to-ground (LG), line-to-line (LL), double line-to-ground (LLG), three-line (LLL), and three-line-to-ground (LLLG) faults. These source parameters variation and fault condition are performed in hardware setup and the results are executed. Experimental results reveal that terminal voltage and current THD increase with increasing speed and excitation capacitance. Depending on the load and capacitor configuration, the SEIG can tolerate both single- and double-conductor open circuit faults. The generator can withstand LG faults up to 40 % load with delta connected excitation capacitors, but other short-circuit faults result in stalling. These findings support SEIGs applicability for pico-hydro power production.
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Solving dynamic economic dispatch of generating units using grey wolf optimizer algorithm

21. April 2026

Gheath Y. Bader, Muwaffaq I. Alomoush

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The dynamic economic dispatch problems can be either single-objective or multi-objective depending on the concerns of the operator, and it is used in order to minimize the total generation cost and transmission losses. In this research, the day-ahead dynamic economic dispatch is investigated that involves diesel generators to find a solution with minimum transmission losses, a smaller number of iterations, and a smaller computational time. The aim of this study is to find the optimal schedule for the generation that minimizes the generation cost and transmission losses of generating units for a 24 h period. Grey wolf optimizer algorithm (GWO) is used in the study to deal with the dynamic economic dispatch problem, whose results are compared with results of many other powerful algorithms. The proposed approach is tested on two benchmark systems with 5 and 10 generating units over a 24 h scheduling horizon. The simulation results are achieved by grey wolf optimizer algorithm then compared with different algorithms and techniques in order to prove the high-quality effectiveness of grey wolf optimizer algorithm in handling the dynamic economic dispatch problem especially in minimizing transmission losses including all the supply-demands equality constraints, valve point effects, ramp rate constraints, upper and lower generation limits for each generating unit. The results show that the GWO attains competitive generation cost minimization while effectively reducing transmission losses, with rapid convergence and modest computational requirements. Comparisons with several state-of-the-art optimization methods further demonstrate the robustness and effectiveness of the proposed framework.
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Non-linear adaptive fuzzy control for microgrid-integrated UPQC under severe disturbances

8. April 2026

Chittaranjan Biswal, Rakhee Panigrahi, Rajesh Kumar Patjoshi

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This work suggests the functionality of the grid integrated microgrid-based unified power quality conditioner (UPQC) system employing proposed reference generation scheme and proposed feedback compensator based current and voltage controller approach underneath extreme power system perturbations generated at the microgrid source owing to the fault originated during interfacing of renewable energy resources. The proposed methodology follows a three-stage approach. First, Takagi-Sugeno fuzzy (TSF) logic and adjustable proportional-integral-derivative (APID) control are coupled to make an adjustable non-linear gain fuzzy (ANGF) controller. In order to achieve minimal steady-state error, this controller controls the capacitor voltage variances within the UPQC during load and source variations. Second, an improved fuzzy phase-locked loop (IFPLL) based on Mamdani fuzzy principles improves the UPQC’s performance even under grid disruptions. Third, a modified synchronous reference frame (MSRF) system generates accurate current and voltage references for UPQC operation. In addition, the proposed feedback compensator benefits the UPQC system by improving tracking error deterioration, gain stability, and lessening amplitude deformation as well as sensitivity to exterior disorders. The effectiveness of the suggested control approach for UPQC is considered through evaluation with a conventional enhanced phase-locked loop (EPLL) and TSF- synchronous reference frame (SRF) controller and then justified via simulation and real-time HIL system under extreme power system environments such as voltage swell/sag along with distorted voltage, random fluctuation of load, voltage interruption, voltage unbalance, and under-voltage.
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Autonomous hybrid power system control integrating wind, solar PV, biomass, and battery storage

20. März 2026

Sekhar Nindra, Ajaykumar Devarapalli, Kumaresan Natarajan

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Recent advancements in decentralised renewable energy offer solutions for reliable grid-based power in remote Indian regions. This study introduces an AHDES (autonomous hybrid distributed energy system) for rural electrification, integrating solar, wind, biomass, and battery storage. A DFIG converts wind energy, with PV panels as the primary source, supported by a biomass generator and battery bank. An SPWM inverter ensures constant voltage and frequency at the PCC, replacing the conventional back-to-back converter for rotor power supply. Converter output current-based maximum power point tracking (COCB-MPPT) is anticipated. This process exploits the relationship between the converter output current and duty ratio to routinely fine-tune step fluctuations, thus maximising power output from the PV panel. In this study, a VFCL (voltage and frequency closed loop) controller combined with a harmonic filter is employed as a voltage controller to reduce the THD percentage. The AHDES topology is simulated in MATLAB and experimentally validated under various operating conditions. Test results presented indicate that the VFCL control strategy effectively maintains the stator voltage at 415 V and the frequency at 50 Hz under all conditions. Further, measured THD values remain below 3 % for voltage and below 6.5 % for current. This demonstrates that the hybrid Solar PV-wind-biomass AHDES maintains stability. Furthermore, the results confirm that the VFCL controller with a harmonic filter is an effective approach for mitigating voltage instability.
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Influence of international design code differences on thunderstorm wind loads and safety margins of transmission tower–line systems

10. März 2026

Xiangli Liu, Bin Zhang, Daokun Qi, Minggui Tang, Lulu Wang, Quan Liu

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Recent failures of transmission towers during thunderstorm events underline the need for a clearer understanding of how different design codes characterize non-synoptic wind loads. This study compares the thunderstorm-related wind parameters specified in four major standards – DL/T 5551-2018, ASCE 74-2020, IEC 60826-2017, and BS EN 50341-2012 – and evaluates their influence on wind-load predictions and the wind-induced behavior of transmission tower–line systems. Results show that ASCE 74 produces the largest wind loads, whereas DL/T 5551 yields the smallest, with the maximum difference in tower-body wind forces reaching 12.8 %. Wind direction significantly affects the vertical distribution of wind pressure, and a 45° incidence angle is identified as a critical loading condition due to geometric shielding effects. Parametric analyses further indicate that wind speed overwhelmingly governs the system’s structural response, while span length introduces comparatively minor variations. Conductor displacements consistently exhibit much larger horizontal than vertical components as a result of dominant lateral aerodynamic actions. These findings demonstrate that the choice of design code can markedly alter the assessed wind effects on transmission tower–line systems. The study provides a scientific basis for determining thunderstorm wind loads and underscores the necessity of adopting provisions tailored to convective storm environments to ensure adequate safety margins in transmission-line design.
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Single-phase off-grid solar microinverter with common ground and voltage boost operation

27. Februar 2026

Ajay Kumar Sahu, Lalit Kumar Sahu, Ramnarayan Patel

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The voltage produced by solar panels can fluctuate because of factors such as irradiance, temperature, and shading. This makes it challenging to obtain a stable voltage suitable for powering devices that use regular household electricity. This article presents a novel solar microinverter that operates in off-grid mode and provide a stable output voltage of 230 V from a low and variable input voltage ranging from 24 V to 46 V. A modified Z-source converter with an active switch achieves the requisite gain. The duty ratio of this switch adapts dynamically in response to fluctuations in the input voltage or load. The operation of the microinverter is controlled by Proportional-Integral (PI) controller, ensuring optimal control and performance. The proposed microinverter provides a common grounding feature between the solar panel and load; this suppresses the Photovoltaic (PV) leakage current. A detailed explanation of the circuit operations, component design and a comparison of the proposed microinverter with existing microinverters are provided. The performance analysis of the proposed topology is validated in real time with a 500VA microinverter.
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Efficiency enhancement and cost analysis of a low-frequency induction motor using Metglas stator core: a comparative study with traditional designs

27. Februar 2026

Roby Mohajon, Md. Anawar Ibrahim, Abu Talha Haque Miah, Nur Mohammad

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The efficiency of conventional induction motors is constrained by the substantial core losses associated with silicon steel, prompting the investigation of alternative magnetic materials for their fabrication. This study aims to enhance the performance of a low-frequency (50 Hz) induction motor by substituting the traditional M19 stator core with Metglas 2605SA1, an amorphous alloy known for its minimal hysteresis and eddy current losses. The study was conducted using ANSYS Motor-CAD simulations under identical geometric and electrical conditions to ensure fair comparison. The key performance indicators, namely efficiency, losses, and thermal stability, were analysed alongside the lifecycle cost and environmental impact. The results indicate that the Metglas-based motor achieved a system efficiency of 85.46 %, compared to 80.71 % for M19, with a total loss reduction of 21.15 % and a core-loss reduction of 62 % (110.3 W → 41.89 W). The peak stator temperature decreased by 17 °C, which enhanced the insulation life and reduced the cooling requirements. Despite the higher initial material cost, the Metglas motor offers long-term economic and environmental benefits, including lower operating costs and reduced CO 2 emissions. These findings underscore the industrial significance of amorphous alloys in realising next-generation, high-efficiency, and sustainable motors.
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Performance analysis of robust SRF controller based on bat optimization for PV based hybrid DSTATCOM for power quality improvement

16. Februar 2026

Mir Manjur Elahi, Pratap Sekhar Puhan, Prakash Kumar Ray

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The present research motivates the enhancement of power quality in a PV fed DSTATCOM employed in a local distribution network. As per the power quality demand from the consumer, regulation of power has become major focus in presence of renewable systems in the distribution network. The distribution network majorly shows resistance towards the severe uncertainties of the grid and load variations. Therefore, the present research proposes hybrid DSTATCOM for the distribution system with various uncertain load conditions. To enhance the performance of proposed system, a robust SRF controller has been implemented for the generation of reference signal for VSI of the DSTATCOM along with DC offset error compensation (DOEC) based phase-locked loops. In the Hybrid DSTATCOM, regulation of dc-link voltage also plays significant position for the performance of the system. Therefore, in this research paper, bat optimization based MPPT has been implemented for the regulation of dc link voltage at the desired level. The system has been developed in the Matlab/Simulink and results have been analyzed. The system has been also validated under experimental conditions in the laboratory, which shows the systems efficiency.
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A position error reduced sensorless control method for PMSM based on an improved sliding mode observer and PLL

5. Februar 2026

Fei Teng, Leilei Guo, Chen Jiang, Kun Huang, Haoyi Huang, Junjun Wu

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The conventional sliding mode observer (SMO)-based sensorless control method for permanent magnet synchronous motor (PMSM) usually requires a sigmoid function, and a low-pass filter (LPF) to reduce the sliding mode noise. However, the influences of the sigmoid function on the rotor position estimation are not clear, and the conventional rotor position compensation method has large errors. To solve these drawbacks, a position error reduced sensorless control method for PMSM based on an improved SMO and phase-locked loop (PLL) is proposed in this paper. First, the influences of the sigmoid function on the rotor position estimation are analyzed in detail. Then, to remove these influences, an improved SMO is proposed by introducing a cross-compensation term in the observer. Next, the drawbacks of the conventional rotor position compensation method are explained, and an improved PLL is further proposed, which not only can compensate the rotor position error generated by the LPF without using the estimated speed, but also can reduce the sliding mode chattering better. As a result, better sensorless control performance is achieved. Finally, experimental studies are carried out, which show that the rotor position estimation error is reduced from 0.2 rad to 0.0025 rad at 200 r/min, and it is reduced from 0.022 rad to 0.0025 rad at 1,000 r/min, indicating the effectiveness of the proposed method in this paper.
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Fault tolerant hybrid cascaded nine level multi-level inverters for grid connected applications

20. Januar 2026

Jami Rajesh, Suresh Katta, Satya Venkata Kishore Pulavarthi, Jayaram Nakka, Naga Venkata Vamshi Kumar Vanapalli, Anil Kumar Chappa

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A novel hybrid cascaded H-bridge (CHB) inverter topology is proposed for renewable energy applications, featuring enhanced fault tolerance. By integrating a nine-level boost switched-capacitor module with H-bridge modules, the design ensures reliable operation under faults affecting semiconductor switches or DC power supplies. The topology offers additional benefits, including voltage boosting of four and self-balancing of switched capacitors. Simulation and experimental results validate the proposed inverter’s performance under various operating conditions, demonstrating its potential for robust and efficient renewable energy systems.
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False Data Injection attacks against non-linear state estimation using the Cartesian formulation of power system equations

20. Januar 2026

Harag Margossian, Zahi Nakad, Dani Tannir, Wissam Fawaz

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State estimation (SE) uses available measurements to extract and analyze information about the power system and support its operation and control. However, its reliability may be compromised through carefully designed False Data Injection (FDI) attacks that target its input measurements. Most existing literature on FDI attacks mounted against SE focus on its approximate, linearized model. Conversely, practical applications often require the use of non-linear SE. This paper proposes a novel approach for the design of FDI attacks against non-linear SE. The proposed approach utilizes the Cartesian formulation of power flow equations to linearize the attack problem, without compromising its accuracy. Two motivating examples using widely adopted test networks are used to demonstrate the effectiveness of the approach. The approach is flexible and can be applied to any network topology and incorporated to different attack design and mitigation studies. It also requires less resources to perform a successful attack as compared to the other relevant approaches proposed in the open literature. This may have important implications on studies that assess the vulnerability of the power system to FDI attacks or propose defense strategies against them, as more resources may be required to implement mitigation techniques than currently assumed in the literature.
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Reliability assessment of All-DC electrical collection system for offshore wind farms: a hierarchical framework from component to system level

26. Dezember 2025

Nan Jiang, Yanbo Che, Hao Guo, Lei Wang

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The harsh operating conditions of deep offshore wind farm (OWF) significantly reduce the reliability of electrical collection system (ECS). Traditional assessment methods for conventional AC-ECS often rely on reliability parameters that are unsuitable for the challenging wind conditions encountered in deep offshore environments. Moreover, the lack of empirical data from operational DC-ECS introduces substantial uncertainty into the reliability evaluations. To address these issues, this paper proposes a hierarchical assessment framework, encompassing component, device and system levels. For the key components of DC-ECS that are impacted by harsh wind conditions, the framework begins with multi-time scale lifespan prediction of power modules at the component level. These predictions are then utilized in device-level reliability calculations for critical equipment. Finally, the sequential Markov Chain Monte Carlo (MCMC) method is employed to assess the reliability of ECS under different topologies. A 300 MW wind farm is used as a case study to validate the feasibility of the proposed method, and the influence of individual equipment reliability and other factors on the overall system reliability is analyzed.
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Enhancing PV-EV hosting capacities in residential distribution systems considering thermal limits of substation and feeders

22. Dezember 2025

Ahmad Eid

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This paper presents a methodology for enhancing the hosting capacity (HC) of photovoltaic (PV) generation and electric vehicle (EV) demand in residential unbalanced distribution systems using the Jellyfish search (JS) algorithm. The primary role of the JS algorithm is to determine the maximum number of PVs and EVs that can be hosted in the distribution systems while satisfying operational and system constraints. The constraints include the voltage profile, the utility transformer’s thermal limit, and the system feeders’ thermal limit. Four case studies on the hosting capacity of PVs and EVs, with and without reactive power support from their inverters. The first and second case studies simulate the EV-HC without and with reactive power support from the EV inverters. The third and fourth cases are dedicated to EV-PV-HC without and with reactive power support. The JS algorithm optimizes the HC of 207 and 225 EVs for the first and second case studies, respectively. The EV-HC has risen to 3,201 and 3,540 EVs with PV generation in the third and fourth case studies, respectively. In addition, the PV-HC reaches 2,988 and 3,084 PVs in the last two cases, respectively. Moreover, the results show that the PV-HC with EV demand reduces power loss by 47.39 % compared to hosting EVs alone. Furthermore, the power loss is reduced by 66.64 % through reactive power assistance from the regulation of PV and EV inverters. Equally, reactive power loss decreases by 57.38 % when using PV-HC compared to EV-HC alone. Furthermore, reactive power loss is reduced by 70.39 % with inverter reactive power support. The increased hosting capacity for PV and EV into distribution systems indicates a more robust and sustainable energy management approach, marked by reduced energy losses and potentially improved efficiency.
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Detection of cyber attacks in smart grids using deep learning

12. Dezember 2025

Mukilan Karuppasamy, Vikash Sunkara, Maddikara Jaya Bharata Reddy

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This paper explores the detection of False Data Injection (FDI) cyberattacks on smart grids using deep learning techniques. Cyberattacks can lead to undesirable outcomes, such as damage to electrical equipment, unnecessary relay tripping, or system-wide blackouts. The utilization of a Feature Tokenizer Transformer (FT-Transformer) model is proposed for robust detection accuracy compared to traditional tree-based classifiers. An FDI attack is mimicked on an IEEE 14 bus system to detect it using various machine learning algorithms. The proposed solution has also been validated against cyberattacks on a three-bus system. The results obtained demonstrate the superior performance of the FT-Transformer model in identifying FDI cyberattacks in smart grids. This research contributes to the advancement of modern cybersecurity power systems, ensuring their reliability against malicious cyber threats.
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Wavelet-based fault detection and classification in MV grids using neural models: case study of Moroccan distribution system

8. Dezember 2025

Saad Sarih, Samira Chabaa, Zakaria Boulghasoul, Abdelouahed Tajer, El Bacha Abdelhadi

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The increasing complexity of modern power distribution systems, driven by renewable integration, evolving load patterns, and aging infrastructure, has accentuated the need for advanced fault detection and classification mechanisms, particularly in emerging medium-voltage (MV) networks such as Moroccan distribution grid. However, traditional protection schemes, often based on centralized logic and fixed thresholds, tend to underperform in complex or high-impedance fault conditions. Furthermore, global signal features such as RMS or frequency components are insufficient to capture the localized and phase-dependent behavior of faults. These limitations have prompted a growing interest in intelligent, data-driven approaches combining signal processing and machine learning to achieve high-resolution fault diagnosis and improved system reliability. The present study proposes and evaluates an intelligent fault classification framework tailored to MV distribution networks. It explores the comparative performance of three neural architectures and supervised learning classifiers, Multilayer Perceptron (MLP), Support Vector Machine (SVM) and Radial Basis Function Neural Network (RBFNN), applied to both globally extracted features and phase-localized wavelet descriptors. In addition to the baseline classification framework, a novel phase-based analysis method is introduced to enhance diagnostic performance. This method processes each phase and neutral current independently, based on the hypothesis that fault signatures emerge more distinctly when analysed separately. The experimental results demonstrate that neural models can reliably identify fault types across both approaches and underscores the potential of wavelet-enhanced AI models for smart and localized protection in emerging power distribution systems and prove its readiness for real-world deployment in SCADA-integrated protection systems.
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Fault location in distribution networks based on an Improved Black-winged Kite Algorithm

5. Dezember 2025

Ke Xu, Jiaxin Shi

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With the large-scale integration of distributed generations (DGs) and the expansion of distribution networks, the complexity of fault location has significantly increased. Traditional fault location methods struggle to meet the demands of modern power systems. This paper explores the impact of distributed generation access on fault location in distribution networks and constructs switching functions and evaluation functions suitable for multi-state distributed generation based on fault characteristic information from automated monitoring devices. To augment the optimization performance of fault localization algorithms, this paper proposes an Improved Black Kite Algorithm (IBKA) that incorporates an Elite Learning Strategy along with Lens Imaging Reverse Learning Strategy and Golden Sine Strategy. This enhances the ability to escape local optima effectively. Simulation results demonstrate that the IBKA exhibits high localization accuracy and fault tolerance in complex scenarios, including single-section faults, multiple-section faults, and Feeder Terminal Unit (FTU) information distortion in active distribution networks, significantly improvs convergence speed and solution efficiency.
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Impact of integrating large scale solar photovoltaic on the voltage stability of the Nigeria power network

3. Dezember 2025

Richard Oladayo Olarewaju, Ayodeji Samson Ogunjuyigbe, Temitope Raphael Ayodele, Adedayo Ademola Yusuff, Thapelo Mosetlhe, Feng Yuming, Chaoran Liu

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Integration of electricity based on intermittent renewable sources such as solar power to a grid can have adverse effect on electric power grid. In this work, we investigated the impact of integration of solar photovoltaic (SPV) on voltage stability. Six transmission buses (Kano, Kaduna, Gwagwalada, New Haven, Birnin Kebbi and Lokoja) with shortest distance to each of the 13 proposed locations have been identified and each of the Solar PV farms was integrated to the transmission bus closest to the proposed solar farm sites. The effects of SPV integration on Transmission lines loading have been performed and the Nigeria 56-bus transmission network was used for the investigation. Voltage stability analysis was carried out using the load margin obtained from the PV curve at each of the six identified buses and effect of SPV integration on the system voltage profile was identified. Sensitivity analysis was also performed in order to obtain the impact of increasing penetration on the voltage stability. The investigation was conducted using DigSilent Power Factory and MATLAB. The result shows that the safe region of integration for the six identified transmission buses is between 10 % (365.8 MW) at Gwagwalada bus and 19 % (695 MW) of base load power at Kaduna. 1 % of SPV was integrated simultaneously at Egbin, Ikeja West, Akangba, Sakete, Kano, Aja, Alagbon, and Osogbo with voltages lesser than 0.95 pu at the base case and the result reveals that all the buses in the system are within acceptable voltage level of 0.95–1.05 pu. Highest improvement in load margin is achieved when 1 % SPV is integrated at Kaduna bus among the six transmission buses considered. Different locations affect system load margins and voltage stability differently. 1 % integration of SPV at different buses significantly improve the load margin from 1,107.7 MW (Birnin Kebbi) to 1,448.9 MW (Kaduna).
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Enhancing legacy OLTC performance through Cost-effective retrofitting: a field-tested approach

1. Dezember 2025

Sadheesh Kumar S. Jayaraman, Ram Jethmalani C. Hemparuva, Navin Sam Kamaraj

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Legacy On-Load Tap Changer (OLTC) systems in distribution substations are often vulnerable to phase reversal errors, voltage fluctuations, and mechanical degradation, particularly in resource-constrained environments. These challenges degrade voltage regulation accuracy and accelerate wear in OLTC components due to excessive or incorrect tap operations. This paper presents a cost-effective retrofit control strategy designed to enhance the reliability and performance of mechanical OLTC systems. The proposed solution integrates real-time phase sequence detection, adaptive tap control logic using hysteresis thresholds, and automatic motor direction correction to prevent erroneous tap movements. A comprehensive MATLAB-based simulation validates the methodology under various operational scenarios, including reverse power flow, phase reversal, and voltage sags/swells. The strategy is also experimentally deployed in a live 11 kV/433 V university distribution substation. It covers diverse loads such as administrative cum academic blocks, laboratories, guest house cum hostels, and HVAC systems. In this university campus scenario, it demonstrates a 66 % reduction in tap changes, enhanced Mean Time Between Failures (MTBF), and 80 % fewer manual interventions. The outcomes confirm that the proposed retrofit enhances voltage stability, operational efficiency, and system longevity, making it a scalable and economically viable solution for ageing power distribution infrastructure.
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Design analysis of matrix converter for wireless Vehicle-to-Vehicle charging system and ecological footprint assessment of electric vehicle charging station

23. Oktober 2025

Shah Faisal, Govind Rai Goyal, Bhanu Pratap Soni, Dilawar Husain

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Electric vehicles (EVs) are increasingly being adopted as a sustainable transportation due to their lower dependency on fossil fuels and low emissions. However, charging time and range anxiety issues in battery technology are affecting the development and growth of EVs. The proposed study examined the system performance of wireless power transmission between two vehicles using a single-phase phase charging matrix converter system. Thus, besides its capability to convert the voltage level, the proposed matrix converter is designed to be an active power filter that helps enhance the power factor and the quality of the wave shape of the input current. A transmitter and receiver shape of coil is also recommended for a wireless Vehicle-to-Vehicle (V2V) charging system with consideration of misalignment and geometrical matching between the transmitters coils are mounted on the front side while the receiver coils are fixed on the rear side. The currently proposed core elements were seen to be effective in transferring power by super-thick silicon steel laminated core (current drawn up to 1.64 A) and a super-thick ferrite core (current drawn up to 1.89 A), both have very less hysteresis loss, which improves system performance. The ecological footprint (EF) associated with electric vehicle (EV) battery charging is estimated to be approximately 3.1 × 10 −4  gha/kWh. New research shows V2V wireless electrical vehicle charging can play a critical role in lowering greenhouse gas emissions combined with other air pollutants compared to traditional battery charging systems. The proposed methodology contains comprehensive modelling of the switching behaviour of the matrix converter as well as control strategies and equations of power flow. The experimental validation is conducted with alternative core materials, and the analysis of the efficiency of the proposed wireless V2V charging system is made with the results that justify the possibility and functionality of the proposed system.
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Data mining based transient stability prediction for power system integrated with varying levels of renewable penetration

17. Oktober 2025

Gayathri K, Manas Kumar Jena

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The power system’s transient stability is affected by the increase in generation from renewable energy sources (RES). Applications such as the transient stability predictor assist the operator in initiating emergency control actions. In this work, predictors such as relative center of active power speed reference (RCOAPSR), relative center of reactive power voltage reference (RCORPVR), and inertia distribution index (IDI) are derived from the phasor measurement unit (PMU) measurements and fed to data mining models such as decision tree (DT) and random forest (RF). The aforementioned parameter’s area-wise calculations provide insights into the regional dynamics, which are important for RES-dominated systems. The simulations are carried out on the IEEE-39 bus system and northern regional power grid (NRPG) using DSA Tools software. The DT and RF models show a prediction accuracy of more than 97 % and 99 % respectively. The suggested scheme has an average early prediction time of more than 18 s. This can help prevent large-scale disturbance propagation.

Special Issue: Control Strategies for Distributed Renewable Energy Resources using AI

Special Issue on Smart Energy Infrastructures for Smart Cities

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Special Issue: Sustainable Energy Management using Green Computing; Guest Editors: Fadi Al-Turjman, Walaa Hamouda, and Shahid Mumtaz

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Special Issue: Sustainable Energy Management using Green Computing; Guest Editors: Fadi Al-Turjman, Walaa Hamouda, and Shahid Mumtaz

Special Issue: Emerging Sustainable Green Energy Technologies for Smart Grid; Guest Editors: Surender Reddy Salkuti, Papia Ray and Sandeep Vuddanti

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Special Issue Title: Emerging Sustainable Green Energy Technologies for Smart Grid; Guest Editors: Surender Reddy Salkuti, Papia Ray and Sandeep Vuddanti

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Special Issue Title: Emerging Sustainable Green Energy Technologies for Smart Grid; Guest Editors: Surender Reddy Salkuti, Papia Ray and Sandeep Vuddanti

Special Issue on Power Electronics Applications in Smart Distribution Grids with Renewable Energy Sources; Guest Editors: B.Chitti Babu, Sabha Raj Arya, Ahmed F. Zobaa

Special Issue: Renewable Energy Systems, Guest Editors: Mohamed Becherif, Paul Lefley, Olivier Bethoux, Haitham Saad Mohamed Ramadan

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Ontario Tech University
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CANADA L1H7K4

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Bhaveshkumar R. Bhalja, Indian Institute of Technology Roorkee, INDIA
Gyu-Jung Cho, Pai Chai University, REPUBLIC OF KOREA
Fei Gao, University of Technology of Belfort-Montbéliard, FRANCE
Y. Liao, University of Kentucky, USA
M. Jaya Bharata Reddy, National Institute of Technology Tiruchirappalli, INDIA
Salkuti Surender Reddy, Woosong University, REPUBLIC OF KOREA
Ke Xu, Nanjing Institute of Technology, CHINA
Cesar Albenes Zeferino, University of Vale do Itajaí (Univali), BRAZIL

Editorial Board
O.H. Abdalla, University of Helwan, EGYPT
M. El Hachemi Benbouzid,University of Western Brittany, FRANCE
W. Fan, Commonwealth Edison Company (ComEd), USA
Andrea Fioravanti, University of L'Aquila, ITALY
G. Harrison, The University of Edin burgh, UK
Y-L. Ke, Kun Shan University of Technology, TAIWAN
P. Lopes, INESC Porto, PORTUGAL
H. Nouri, Universi ty of the West of England, UK
R. Mota Palomino, National Polytechnic Institute, MEXICO
A. Pahwa, Kansas State University, USA
A.G. Phadke, Virginia Tech, USA
S. R. Salkuti, Woosong University, REPUBLIC OF KOREA
M. Sanaye-Pasand, University of Tehran, IRAN
M. Shahidehpour, Illinois Institute of Technology, USA
C. Singh, Texas A&M University, USA
E. Tag-Eldin, Cairo University, EGYPT
D. Thukaram, Indian Institute of Science, INDIA
D. Tziouvaras, Schweitzer Engineering Labs, USA
F. Wang, Shanghai University, Shanghai, CHINA
F. Wen, Zhejiang University, CHINA
I. Zamora, ETSI de Bilbao - University of the Basque Country, SPAIN

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