Pub Date : 2026-01-13DOI: 10.1016/j.epsr.2026.112740
Xinyan Xiao, Zhijian Lu, Lanjun Yang
The abnormal decline in DC-ageing power consumption of modern stable zinc oxide (ZnO) varistors hinders effective state assessment, and determining the ageing mechanisms of such varistors under various operating conditions is crucial for application. This study focuses on a scaled-down arrester model containing five layers of stable varistors connected in series. Negative-polarity impulse ageing characteristics were experimentally investigated, and the ageing patterns and mechanisms of key parameters were analysed. Results reveal that the varistors underwent asymmetric ageing, with all parameters exhibiting consistent polarity effects. The reverse volt–ampere characteristic curves crossing is possible attributed to the dynamic competition between the initial barrier height and hole concentration. The positive feedback effect from residual voltage dispersion intensifies non-uniform ageing within the model, causing localised premature surface breakdown and overall failure through a chain reaction. These findings provide valuable insights into microscopic material ageing mechanisms and high-performance arrester design and manufacturing.
{"title":"Unipolar impulse ageing characteristics and non-uniform ageing mechanism of zinc oxide varistors","authors":"Xinyan Xiao, Zhijian Lu, Lanjun Yang","doi":"10.1016/j.epsr.2026.112740","DOIUrl":"10.1016/j.epsr.2026.112740","url":null,"abstract":"<div><div>The abnormal decline in DC-ageing power consumption of modern stable zinc oxide (ZnO) varistors hinders effective state assessment, and determining the ageing mechanisms of such varistors under various operating conditions is crucial for application. This study focuses on a scaled-down arrester model containing five layers of stable varistors connected in series. Negative-polarity impulse ageing characteristics were experimentally investigated, and the ageing patterns and mechanisms of key parameters were analysed. Results reveal that the varistors underwent asymmetric ageing, with all parameters exhibiting consistent polarity effects. The reverse volt–ampere characteristic curves crossing is possible attributed to the dynamic competition between the initial barrier height and hole concentration. The positive feedback effect from residual voltage dispersion intensifies non-uniform ageing within the model, causing localised premature surface breakdown and overall failure through a chain reaction. These findings provide valuable insights into microscopic material ageing mechanisms and high-performance arrester design and manufacturing.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"255 ","pages":"Article 112740"},"PeriodicalIF":4.2,"publicationDate":"2026-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-13DOI: 10.1016/j.epsr.2025.112697
Weidi Cheng , Yanyan Yin , Arindam Ghosh , Shuping He , Yanqing Liu
This paper investigates the optimal control of discrete-time, single-machine, infinite-bus (SMIB) systems that are subjected to random topology changes and SCADA/relay-induced asynchronies. The system is modeled within a Markov jump system (MJS) framework to capture stochastic mode transitions caused by disturbances, such as transmission line faults. An asynchronous control architecture is adopted, accounting for mode mismatch between system and controller. To avoid the intractable analytical solution of the coupled algebraic Riccati equations (CAREs), a model-based policy iteration (PI) algorithm is proposed that guarantees convergence under the stabilizability condition. Simulation results for a two-mode SMIB case study show that the proposed controller converges within 73 iterations and maintains closed-loop mean-square stability, effectively damping electromechanical oscillations in the presence of random switching and communication delays.
{"title":"Asynchronous learning-based control for power systems with topological disturbances","authors":"Weidi Cheng , Yanyan Yin , Arindam Ghosh , Shuping He , Yanqing Liu","doi":"10.1016/j.epsr.2025.112697","DOIUrl":"10.1016/j.epsr.2025.112697","url":null,"abstract":"<div><div>This paper investigates the optimal control of discrete-time, single-machine, infinite-bus (SMIB) systems that are subjected to random topology changes and SCADA/relay-induced asynchronies. The system is modeled within a Markov jump system (MJS) framework to capture stochastic mode transitions caused by disturbances, such as transmission line faults. An asynchronous control architecture is adopted, accounting for mode mismatch between system and controller. To avoid the intractable analytical solution of the coupled algebraic Riccati equations (CAREs), a model-based policy iteration (PI) algorithm is proposed that guarantees convergence under the stabilizability condition. Simulation results for a two-mode SMIB case study show that the proposed controller converges within 73 iterations and maintains closed-loop mean-square stability, effectively damping electromechanical oscillations in the presence of random switching and communication delays.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"255 ","pages":"Article 112697"},"PeriodicalIF":4.2,"publicationDate":"2026-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-13DOI: 10.1016/j.epsr.2026.112718
Mohammed Morgan , Hatem F. Sindi , Hatem H. Zeineldin , Ahmed Lasheen
This paper proposes a novel power flow algorithm for islanded microgrids that depends on cost-based droop schemes. Cost-based droop schemes have been adopted in literature to achieve efficiency and generation cost reduction but impose challenges on solving the power flow problem using the iterative-based methods. To solve this problem, this paper aims to utilize a recursive (non-iterative) method called the holomorphic embedding load flow method (HELM) to solve the power flow problem of islanded microgrids. This method originally was developed to solve convergence issues of non-iterative methods for conventional power flow problems. Two test systems are used to evaluate the validity of the proposed method. In each case, the results from MHELM are compared to detailed time domain simulations performed using PSCAD/EMTDC to show the accuracy of the proposed algorithm.
{"title":"A holomorphic embedding power flow algorithm for cost-based droop microgrids","authors":"Mohammed Morgan , Hatem F. Sindi , Hatem H. Zeineldin , Ahmed Lasheen","doi":"10.1016/j.epsr.2026.112718","DOIUrl":"10.1016/j.epsr.2026.112718","url":null,"abstract":"<div><div>This paper proposes a novel power flow algorithm for islanded microgrids that depends on cost-based droop schemes. Cost-based droop schemes have been adopted in literature to achieve efficiency and generation cost reduction but impose challenges on solving the power flow problem using the iterative-based methods. To solve this problem, this paper aims to utilize a recursive (non-iterative) method called the holomorphic embedding load flow method (HELM) to solve the power flow problem of islanded microgrids. This method originally was developed to solve convergence issues of non-iterative methods for conventional power flow problems. Two test systems are used to evaluate the validity of the proposed method. In each case, the results from MHELM are compared to detailed time domain simulations performed using PSCAD/EMTDC to show the accuracy of the proposed algorithm.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"255 ","pages":"Article 112718"},"PeriodicalIF":4.2,"publicationDate":"2026-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-12DOI: 10.1016/j.epsr.2026.112745
Qihao Hu , Jianwen Wu , Jiawang Luo , Shangwen Xia , Ruida Zhang , Jian Lan , Ying Feng , Chengyu Wang
The dynamic characteristics and reliability of an operating mechanism directly influence the breaking performance of a vacuum circuit breaker. To achieve two rapid opening operations and one closing operation under reclosing conditions, and to enhance overall performance, a novel operating mechanism integrating an electromagnetic repulsion mechanism (ERM) with a semi-hard magnetic actuator (SHMA) is proposed. Comprehensive multi-objective optimization, along with simulation and experimental studies, has been conducted. A SHMA suitable for holding and closing operations is introduced, and its static and dynamic characteristics are analyzed and compared with those of a permanent magnetic actuator (PMA). For the multi-objective optimization of the structural parameters of the repulsion disk and coil, a combined approach using response surface methodology (RSM) and the non-dominated sorting genetic algorithm II (NSGA-II) is employed. The results indicate that the SHMA reaches steady state more rapidly, achieves higher closing speed, and exhibits reduced rebound compared to the PMA. Furthermore, the ERM demonstrates reduced current, peak mechanical stress, and radial dimensions, offering valuable guidance for engineering applications.
{"title":"Design and optimization of vacuum circuit breaker operating mechanism considering reclosing based on electromagnetic repulsion mechanism and semi-hard magnetic actuator","authors":"Qihao Hu , Jianwen Wu , Jiawang Luo , Shangwen Xia , Ruida Zhang , Jian Lan , Ying Feng , Chengyu Wang","doi":"10.1016/j.epsr.2026.112745","DOIUrl":"10.1016/j.epsr.2026.112745","url":null,"abstract":"<div><div>The dynamic characteristics and reliability of an operating mechanism directly influence the breaking performance of a vacuum circuit breaker. To achieve two rapid opening operations and one closing operation under reclosing conditions, and to enhance overall performance, a novel operating mechanism integrating an electromagnetic repulsion mechanism (ERM) with a semi-hard magnetic actuator (SHMA) is proposed. Comprehensive multi-objective optimization, along with simulation and experimental studies, has been conducted. A SHMA suitable for holding and closing operations is introduced, and its static and dynamic characteristics are analyzed and compared with those of a permanent magnetic actuator (PMA). For the multi-objective optimization of the structural parameters of the repulsion disk and coil, a combined approach using response surface methodology (RSM) and the non-dominated sorting genetic algorithm II (NSGA-II) is employed. The results indicate that the SHMA reaches steady state more rapidly, achieves higher closing speed, and exhibits reduced rebound compared to the PMA. Furthermore, the ERM demonstrates reduced current, peak mechanical stress, and radial dimensions, offering valuable guidance for engineering applications.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"255 ","pages":"Article 112745"},"PeriodicalIF":4.2,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-10DOI: 10.1016/j.epsr.2026.112713
Jun Qi, Yi Xu, Da Jiang, Dan Zhou
Due to the inherent intermittency and variability of solar energy, the increasing penetration of photovoltaic (PV) generation brings significant challenges to distribution grid operation. To enhance PV hosting capacity, it is crucial to fully leverage user-side flexible resources (FRs) within Internet of Things (IoT) environments. This paper proposes a dynamic time‑of‑use (TOU) pricing mechanism designed to guide demand response (DR) and mitigate PV power fluctuations by emphasizing user-side responsibility and advantages in voltage regulation. A Stackelberg game framework between the distribution system operator (DSO) and users is established, and a power fluctuation penalty (PFP) term reflecting voltage-regulation responsibility (VRR) is incorporated into user-side objective functions. When user-side FRs adjust their electricity consumption according to day-ahead dynamic TOU tariffs, voltage violations that limit PV hosting capacity can be effectively alleviated. Simulation results demonstrate that power fluctuations can be smoothed by considering user-side VRR, and the PV hosting capacity will be significantly raised by dynamic TOU, compared with constant or peak-valley pricing schemes.
{"title":"Analysis of PV hosting capacity in distribution grids considering users’ voltage-regulation responsibility under dynamic Time-of-Use pricing","authors":"Jun Qi, Yi Xu, Da Jiang, Dan Zhou","doi":"10.1016/j.epsr.2026.112713","DOIUrl":"10.1016/j.epsr.2026.112713","url":null,"abstract":"<div><div>Due to the inherent intermittency and variability of solar energy, the increasing penetration of photovoltaic (PV) generation brings significant challenges to distribution grid operation. To enhance PV hosting capacity, it is crucial to fully leverage user-side flexible resources (FRs) within Internet of Things (IoT) environments. This paper proposes a dynamic time‑of‑use (TOU) pricing mechanism designed to guide demand response (DR) and mitigate PV power fluctuations by emphasizing user-side responsibility and advantages in voltage regulation. A Stackelberg game framework between the distribution system operator (DSO) and users is established, and a power fluctuation penalty (PFP) term reflecting voltage-regulation responsibility (VRR) is incorporated into user-side objective functions. When user-side FRs adjust their electricity consumption according to day-ahead dynamic TOU tariffs, voltage violations that limit PV hosting capacity can be effectively alleviated. Simulation results demonstrate that power fluctuations can be smoothed by considering user-side VRR, and the PV hosting capacity will be significantly raised by dynamic TOU, compared with constant or peak-valley pricing schemes.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"255 ","pages":"Article 112713"},"PeriodicalIF":4.2,"publicationDate":"2026-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-09DOI: 10.1016/j.epsr.2026.112720
M. Shafiee Souderjani, M.E. Hamedani Golshan
To capture the entire dynamic response of a multi-microgrid (MMG) system, detailed modeling of the MMG is necessary; however, the computational burden of such models limits their suitability for efficient dynamic studies. When the analysis focuses on a single microgrid (MG) within a MMG, external MGs can be represented using simplified equivalents that preserve accuracy while significantly reducing computational demands. To balance model detail with computational efficiency, this paper proposes a model order reduction (MOR) technique based on a nonlinear autoregressive exogenous (NARX) neural network to replace external MGs with an artificial intelligence (AI)-based black-box equivalent. To consider all dynamic modes in different disturbances, a detailed MMG model is introduced where each MG comprises doubly-fed induction generators (DFIGs), battery energy storage systems (BESSs), loads, and distribution feeders capable of operating in both grid-connected and islanded modes. To demonstrate the method’s scalability, a MMG composed of six MGs with total dynamic order of 360 has been studied. The designed training and validation scenarios capture the dynamic responses of external MGs to a wide range of representative events occurring on the target MG. The performance of the proposed reduced-order model is evaluated in comparison with a long short-term memory (LSTM) based alternative and the detailed model, which serves as the ground truth. The NARX-based equivalent achieves high accuracy while reducing simulation time by over 90%, providing a practical solution for computationally efficient MMG dynamic studies.
{"title":"NARX neural network-based black-box equivalence model of external microgrids in a multi-microgrid including DFIG and BESS","authors":"M. Shafiee Souderjani, M.E. Hamedani Golshan","doi":"10.1016/j.epsr.2026.112720","DOIUrl":"10.1016/j.epsr.2026.112720","url":null,"abstract":"<div><div>To capture the entire dynamic response of a multi-microgrid (MMG) system, detailed modeling of the MMG is necessary; however, the computational burden of such models limits their suitability for efficient dynamic studies. When the analysis focuses on a single microgrid (MG) within a MMG, external MGs can be represented using simplified equivalents that preserve accuracy while significantly reducing computational demands. To balance model detail with computational efficiency, this paper proposes a model order reduction (MOR) technique based on a nonlinear autoregressive exogenous (NARX) neural network to replace external MGs with an artificial intelligence (AI)-based black-box equivalent. To consider all dynamic modes in different disturbances, a detailed MMG model is introduced where each MG comprises doubly-fed induction generators (DFIGs), battery energy storage systems (BESSs), loads, and distribution feeders capable of operating in both grid-connected and islanded modes. To demonstrate the method’s scalability, a MMG composed of six MGs with total dynamic order of 360 has been studied. The designed training and validation scenarios capture the dynamic responses of external MGs to a wide range of representative events occurring on the target MG. The performance of the proposed reduced-order model is evaluated in comparison with a long short-term memory (LSTM) based alternative and the detailed model, which serves as the ground truth. The NARX-based equivalent achieves high accuracy while reducing simulation time by over 90%, providing a practical solution for computationally efficient MMG dynamic studies.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"255 ","pages":"Article 112720"},"PeriodicalIF":4.2,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145928951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-09DOI: 10.1016/j.epsr.2025.112707
Shuyi Wang , Huan Zhao , Yuji Cao , Zibin Pan , Guolong Liu , Gaoqi Liang , Junhua Zhao
The Wind Storage Integrated System with Power Smoothing Control (PSC) has emerged as a promising solution for efficient and reliable wind energy generation. However, existing PSC strategies exhibit several limitations. Many fail to capture the cooperative interactions and distinct control frequencies between wind turbines and battery energy storage systems (BESSs). In addition, the impacts of wake effects and battery degradation costs are often overlooked. This paper proposes a novel multi-agent coordinated control framework to address these challenges, which explicitly integrates a wake model and a battery degradation model to construct a more realistic operating environment. The problem is formulated as a multi-agent Markov decision process (MMDP), where the wind farm and the BESS agents pursue complementary objectives to achieve optimal control. Furthermore, a Physics-informed Neural Network-assisted Multi-agent Deep Deterministic Policy Gradient (PAMA-DDPG) algorithm is introduced, embedding a partial differential equation of power fluctuation as a physics-guided loss term to accelerate learning and enhance physical consistency. Simulations using WindFarmSimulator (WFSim) in four scenarios demonstrate that the proposed method outperforms benchmark approaches, achieving an 11% increase in total profit and a 19% reduction in power fluctuation. These results effectively address the dual objectives of economic efficiency and grid reliability.
{"title":"Coordinated power smoothing control for wind storage integrated system with physics-informed deep reinforcement learning","authors":"Shuyi Wang , Huan Zhao , Yuji Cao , Zibin Pan , Guolong Liu , Gaoqi Liang , Junhua Zhao","doi":"10.1016/j.epsr.2025.112707","DOIUrl":"10.1016/j.epsr.2025.112707","url":null,"abstract":"<div><div>The Wind Storage Integrated System with Power Smoothing Control (PSC) has emerged as a promising solution for efficient and reliable wind energy generation. However, existing PSC strategies exhibit several limitations. Many fail to capture the cooperative interactions and distinct control frequencies between wind turbines and battery energy storage systems (BESSs). In addition, the impacts of wake effects and battery degradation costs are often overlooked. This paper proposes a novel multi-agent coordinated control framework to address these challenges, which explicitly integrates a wake model and a battery degradation model to construct a more realistic operating environment. The problem is formulated as a multi-agent Markov decision process (MMDP), where the wind farm and the BESS agents pursue complementary objectives to achieve optimal control. Furthermore, a Physics-informed Neural Network-assisted Multi-agent Deep Deterministic Policy Gradient (PAMA-DDPG) algorithm is introduced, embedding a partial differential equation of power fluctuation as a physics-guided loss term to accelerate learning and enhance physical consistency. Simulations using WindFarmSimulator (WFSim) in four scenarios demonstrate that the proposed method outperforms benchmark approaches, achieving an 11% increase in total profit and a 19% reduction in power fluctuation. These results effectively address the dual objectives of economic efficiency and grid reliability.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"255 ","pages":"Article 112707"},"PeriodicalIF":4.2,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145915241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-09DOI: 10.1016/j.epsr.2026.112710
Yuyao Hu , Yulin Wang , Fangbin Liu , Xingliang Jiang , Wentao Jia , Qiang Zhou , Hui Liu
As the insulation equipment of the power grid, the original contact angle of the silicone rubber of the main material of the composite insulator is about 110°, which does not meet the superhydrophobic standard. To improve the hydrophobicity, a biomimetic superhydrophobic structure, namely the grating micro/nano composite structure of rice leaf, was textured on silicone rubber surface using nanosecond pulsed laser, and the influence of laser technological parameters on the grating microstructure and wetting performance was investigated. Moreover, the chemical elements and functional groups on the surface of silicone rubber before and after laser treatment were tested with an energy dispersive spectrometer and Fourier transform infrared spectroscope. The results show that after laser processing, the grating microstructure and micro / nano particles on the surface of silicone rubber increase the average roughness from 0.6537 μm to 2.5191 μm, and the maximum contact angle is 154.25°. The elemental species on the surface of silicone rubber remain unchanged, but the overall content of carbon and oxygen elements increases, while that of silicon element declines. In summary, the grating microstructure prepared by nanosecond laser can effectively improve the hydrophobicity of the silicone rubber surface, thereby improving the performance of the composite insulator.
{"title":"Study on surface hydrophobicity of silicone rubber insulator with grating structure based on nanosecond pulse laser processing","authors":"Yuyao Hu , Yulin Wang , Fangbin Liu , Xingliang Jiang , Wentao Jia , Qiang Zhou , Hui Liu","doi":"10.1016/j.epsr.2026.112710","DOIUrl":"10.1016/j.epsr.2026.112710","url":null,"abstract":"<div><div>As the insulation equipment of the power grid, the original contact angle of the silicone rubber of the main material of the composite insulator is about 110°, which does not meet the superhydrophobic standard. To improve the hydrophobicity, a biomimetic superhydrophobic structure, namely the grating micro/nano composite structure of rice leaf, was textured on silicone rubber surface using nanosecond pulsed laser, and the influence of laser technological parameters on the grating microstructure and wetting performance was investigated. Moreover, the chemical elements and functional groups on the surface of silicone rubber before and after laser treatment were tested with an energy dispersive spectrometer and Fourier transform infrared spectroscope. The results show that after laser processing, the grating microstructure and micro / nano particles on the surface of silicone rubber increase the average roughness from 0.6537 μm to 2.5191 μm, and the maximum contact angle is 154.25°. The elemental species on the surface of silicone rubber remain unchanged, but the overall content of carbon and oxygen elements increases, while that of silicon element declines. In summary, the grating microstructure prepared by nanosecond laser can effectively improve the hydrophobicity of the silicone rubber surface, thereby improving the performance of the composite insulator.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"255 ","pages":"Article 112710"},"PeriodicalIF":4.2,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145915240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-09DOI: 10.1016/j.epsr.2025.112694
Wang Tian , Liu Zhaobin , Sheng Chenxing , Guo Wei
Photovoltaic power forecasting is highly influenced by meteorological conditions.To address the forecasting issue under sudden weather changes,this study proposes a SHAP-NMTCN-BiGRU model for nonlinear power prediction, and applies an error correction model for secondary adjustment of the predicted values.First,use the McClear model to calculate the clear - sky radiation and clear - sky index (k).Then, divide the dataset into sudden and non - sudden weather subsets based on k.Next, employ Random Forest to enhance the sudden weather subset, incorporating k in sub - decision tree division to capture nonlinear features.Furthermore,use SHAP values to optimize the weighted method between models and feature dimensions,improving computational efficiency.To overcome the nonlinear forecasting problem,NAS is used to automatically search for the optimal network structure of the hybrid model.Finally, the error between the predicted and actual power values is calculated,and a Transformer model is used for linear error prediction and secondary correction of the power values.Experimental results show that the RF-enhanced feature method combined with k effectively captures short-term trends.In nonlinear forecasting,the SHAP-NMTCN-BiGRU model demonstrates strong performance and stability.
{"title":"SHapley additive exPlanations-based neural architecture search and multi-channel temporal convolutional network with bidirectional gated recurrent unit-based photovoltaic power ultra-short-term fusion prediction with abrupt weather feature enhancement","authors":"Wang Tian , Liu Zhaobin , Sheng Chenxing , Guo Wei","doi":"10.1016/j.epsr.2025.112694","DOIUrl":"10.1016/j.epsr.2025.112694","url":null,"abstract":"<div><div>Photovoltaic power forecasting is highly influenced by meteorological conditions.To address the forecasting issue under sudden weather changes,this study proposes a SHAP-NMTCN-BiGRU model for nonlinear power prediction, and applies an error correction model for secondary adjustment of the predicted values.First,use the McClear model to calculate the clear - sky radiation and clear - sky index (k).Then, divide the dataset into sudden and non - sudden weather subsets based on k.Next, employ Random Forest to enhance the sudden weather subset, incorporating k in sub - decision tree division to capture nonlinear features.Furthermore,use SHAP values to optimize the weighted method between models and feature dimensions,improving computational efficiency.To overcome the nonlinear forecasting problem,NAS is used to automatically search for the optimal network structure of the hybrid model.Finally, the error between the predicted and actual power values is calculated,and a Transformer model is used for linear error prediction and secondary correction of the power values.Experimental results show that the RF-enhanced feature method combined with k effectively captures short-term trends.In nonlinear forecasting,the SHAP-NMTCN-BiGRU model demonstrates strong performance and stability.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"255 ","pages":"Article 112694"},"PeriodicalIF":4.2,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145928952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-09DOI: 10.1016/j.epsr.2026.112722
Moustafa Sahnoune Chaouche , Faouzi Didi , Abderrazak Amara , Hamza Houassine , Mohd Fairouz Mohd Yousof , Ahmad F. Tazay , Aymen Flah , Mohamed K. Metwaly , Ramy N.R. Ghaly , Sherif S.M. Ghoneim
In this article, a new analytical method is introduced to effectively estimate the self-inductance, mutual inductances, and series capacitance of transformer windings. The approach uses FR data collected at the winding terminals with the neutral open test. It applies an analytical formula that converts the sum of the inverse squares of both short-circuit and open-circuit natural frequencies, derived from the FR curve, into a polynomial function. These formulas are based on a lumped, mutually coupled equivalent model of the winding, with relationships expressed as a polynomial function connected by a factor relating the inductances, generalized to an N-1 degree for the N-th section of the model. By solving this polynomial, all winding inductance values can be accurately estimated, enabling the determination of the series capacitance. Notably, this method relies solely on measurements of the FR curve, ground capacitance, and equivalent inductance, providing an indirect yet highly efficient way to determine all parameters of the lumped mutually coupled equivalent model. This technique has been rigorously validated through experimental frequency response measurements on two air-core insulated windings, producing remarkably precise results that demonstrate its effectiveness in the field of frequency modeling.
{"title":"A novel analytical methodology for estimating high-frequency lumped model inductances and series capacitance of transformer winding: an indirect measurement procedure","authors":"Moustafa Sahnoune Chaouche , Faouzi Didi , Abderrazak Amara , Hamza Houassine , Mohd Fairouz Mohd Yousof , Ahmad F. Tazay , Aymen Flah , Mohamed K. Metwaly , Ramy N.R. Ghaly , Sherif S.M. Ghoneim","doi":"10.1016/j.epsr.2026.112722","DOIUrl":"10.1016/j.epsr.2026.112722","url":null,"abstract":"<div><div>In this article, a new analytical method is introduced to effectively estimate the self-inductance, mutual inductances, and series capacitance of transformer windings. The approach uses FR data collected at the winding terminals with the neutral open test. It applies an analytical formula that converts the sum of the inverse squares of both short-circuit and open-circuit natural frequencies, derived from the FR curve, into a polynomial function. These formulas are based on a lumped, mutually coupled equivalent model of the winding, with relationships expressed as a polynomial function connected by a factor relating the inductances, generalized to an N-1 degree for the N-th section of the model. By solving this polynomial, all winding inductance values can be accurately estimated, enabling the determination of the series capacitance. Notably, this method relies solely on measurements of the FR curve, ground capacitance, and equivalent inductance, providing an indirect yet highly efficient way to determine all parameters of the lumped mutually coupled equivalent model. This technique has been rigorously validated through experimental frequency response measurements on two air-core insulated windings, producing remarkably precise results that demonstrate its effectiveness in the field of frequency modeling.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"255 ","pages":"Article 112722"},"PeriodicalIF":4.2,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145915242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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