Electric Power Systems Research最新文献

{"title":"Optimized approach for wind turbine anomaly detection: integrating uncertainty quantification and dimensionality reduction","authors":"Shaoheng Lan ,&nbsp;Haibin Li ,&nbsp;Dongsheng Li ,&nbsp;Changchun Bao ,&nbsp;Shufeng Lu","doi":"10.1016/j.epsr.2026.112818","DOIUrl":"10.1016/j.epsr.2026.112818","url":null,"abstract":"<div><div>Accurate anomaly detection in wind turbines is critical for operational stability, yet existing methods are hindered by a persistent trade-off among uncertainty quantification, high-dimensional complexity, and computational efficiency, a challenge termed the \"Anomaly Detection Trilemma\". To resolve this, we propose a novel Bayesian-refined Random Forest (BPRF) model featuring a synergistic three-stage architecture. The framework first employs a Bayesian module to generate a probabilistic feature, then uses a Random Forest as a non-linear amplifier to map data into a high-dimensional space, and finally applies Principal Component Analysis (PCA) to distill a robust low-dimensional \"normalcy\" subspace for anomaly scoring. Validated on a real-world public dataset, the BPRF model demonstrated superior performance over a comprehensive set of mainstream baselines, achieving a leading F1-score of 0.59, an accuracy of 0.87, and an AUC of 0.86. The results confirm that the BPRF model effectively escapes the \"Anomaly Detection Trilemma\", providing a solution that is not only accurate but also reliable and computationally tractable, thereby establishing a new performance benchmark for practical industrial deployment.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"255 ","pages":"Article 112818"},"PeriodicalIF":4.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146188587","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}

{"title":"A T-STATCOM converter structure synergistically combining IGBTs and SiC-MOSFETs","authors":"Salvatore Foti ,&nbsp;Gioele Baia ,&nbsp;Haseeb Hassan Khan ,&nbsp;Antonio Testa ,&nbsp;Michele Emanuele","doi":"10.1016/j.epsr.2026.112835","DOIUrl":"10.1016/j.epsr.2026.112835","url":null,"abstract":"<div><div>The paper presents a new converter topology for a Transmission-type Static Synchronous Compensator (T-STATCOM), which is composed of two sections: a three-level, neutral-point clamped (3LC) converter using silicon based Insulated-Gate Bipolar Transistors (Si-IGBTs), and a two-level converter (2LC) using Silicon Carbide Metal-Oxide-Semiconductor Field-Effect Transistors (SiC-MOSFETs). These two converters are connected to each other using a coupling transformer featuring an open-end secondary winding. Taking advantage of the high switching frequency of SiC devices, the 2LC performs harmonic compensation and reactive power control, thus eliminating the need for bulky passive filters and enhancing the system overall efficiency. The proposed topology has been validated through the simulation of a 8 MVAr, 154 kV T-STATCOM system. Moreover, the consistence of the concept has been practically confirmed by a scaled-down experimental prototype rated at 6 kVAr. Up to 50% reduction in total losses and component costs is achieved by the proposed topology in comparison with state-of-the-art designs, as well as voltage Total Harmonic Distortion (THDv) compliance with IEEE Std. 519-2014.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"255 ","pages":"Article 112835"},"PeriodicalIF":4.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146188581","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}

{"title":"A holomorphic embedding power flow algorithm for cost-based droop microgrids","authors":"Mohammed Morgan ,&nbsp;Hatem F. Sindi ,&nbsp;Hatem H. Zeineldin ,&nbsp;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":"2026-06-01","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}

{"title":"Intelligent prediction of photovoltaic inverter failures for improved reliability and control in smart grid systems","authors":"Safwan Nadweh ,&nbsp;Nabil Mohammed ,&nbsp;Saad Mekhilef","doi":"10.1016/j.epsr.2026.112735","DOIUrl":"10.1016/j.epsr.2026.112735","url":null,"abstract":"<div><div>The increasing demand for renewable energy sources necessitates advanced methods to ensure grid stability and operational efficiency. Smart grids present a viable solution by enabling the seamless integration of renewable energy systems, such as solar photovoltaic (PV) and other sources. However, the performance and reliability of such systems are critically dependent on the performance and functionality of power inverters (e.g., solar PV inverters). This paper proposes the application of several decision tree algorithms, which are traditional decision tree (TDT), iterative dichotomizer tree (IDT), C4.5 algorithm, and CART algorithm, for fault prediction and diagnostics in solar PV inverters. The training and prediction phases of the decision tree models employ both key inverter specifications, such as nominal operating ranges, abnormal readings, and fault conditions, alongside critical operational parameters, including voltage, current, temperature, conversion efficiency, power factor (PF), and total harmonic distortion (THD). Also, a cost-benefit analysis is made to consider the cost-effectiveness of predictive maintenance of solar PV inverters with the presence of significant economic benefits. A substantial cost advantage is shown, where 12,000 $/year in losses is saved with an investment of merely 4000 $/year in support of a predictive maintenance model with a first year ROI of 200%. Overall, the results of all decision tree models, implemented in MATLAB, confirm that both TDT algorithm and CART algorithm attain a high classification accuracy of about 95% with TDT possessing the shortest fault prediction time of about 50 ms. Markedly, the CART algorithm proves effective when it comes to dealing with an up to 90% missing values. Additionally, the analysis demonstrates a direct proportional relationship between voltage, current, temperature, and conversion efficiency, while revealing an inverse relationship between conversion efficiency and THD. The proposed algorithms for fault prediction hold significant potential for enhancing the reliability of solar PV systems integrated within smart grid frameworks.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"255 ","pages":"Article 112735"},"PeriodicalIF":4.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980431","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}

{"title":"Optimal distribution network reconfiguration with non-adaptive overcurrent relay re-coordination","authors":"Rasoul Abdollahi,&nbsp;Reza Mohamadi Chabanloo","doi":"10.1016/j.epsr.2025.112668","DOIUrl":"10.1016/j.epsr.2025.112668","url":null,"abstract":"<div><div>Reconfiguring distribution networks is a well-established strategy to reduce power losses and enhance operational efficiency. However, topology changes may alter the roles of primary and backup overcurrent relays and modify short-circuit currents, thereby compromising the reliability of the protection system. This paper addresses this challenge by formulating a joint optimization problem with two objectives: (i) loss-minimizing distribution network reconfiguration and (ii) simultaneous coordination of overcurrent relays. Instead of discarding configurations that violate protection constraints, the proposed method determines a single set of general relay settings and then optimizes reconfiguration under these settings while maintaining coordination requirements. The framework is non-adaptive, requires no telecommunication links, and thus offers practical advantages over adaptive schemes. A Pareto-based multi-objective optimization is developed, combining a Genetic Algorithm (GA) for network reconfiguration with a Linear Programming (LP) model for relay re-coordination. Simulation results on the standard 33-bus distribution system demonstrate that the method significantly expands the set of feasible configurations, achieves notable loss reduction, and ensures reliable relay coordination across multiple operating states.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"255 ","pages":"Article 112668"},"PeriodicalIF":4.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146078803","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}

{"title":"Resilient control of DC microgrids under false data injection attacks using adaptive sliding mode unknown input observer","authors":"Ziji Su,&nbsp;Yile Dai,&nbsp;Jiawei Zhang,&nbsp;Miao Yu","doi":"10.1016/j.epsr.2026.112781","DOIUrl":"10.1016/j.epsr.2026.112781","url":null,"abstract":"<div><div>The rapid advancement of communication and control technologies has significantly enhanced the intelligence of DC microgrids, yet it also introduces cybersecurity risks such as false data injection attacks (FDIAs). Existing studies on FDIA mitigation still exhibit limitations. For example, their reliance on distributed communication leads to slow convergence. Moreover, most methods assume an ideal primary layer, neglecting actuator faults and parameter perturbations. To this end, this paper proposes a resilient control scheme: at the secondary layer, an auxiliary reference system (ARS) is designed to generate reference values without requiring data transmission from the primary layer, while the primary layer employs a control law based on the super-twisting algorithm to achieve robustness against actuator faults and parameter perturbations. Furthermore, a decentralized adaptive sliding mode unknown input observer is developed to reconstruct ARS states for FDIA mitigation. Compared with existing approaches, the proposed strategy demonstrates superior FDIA suppression capability and robustness against non-ideal conditions at the primary layer. The proposed scheme achieves control recovery within 15 ms, which is significantly faster than the comparative methods (0.45 s and 1.26 s, respectively). Stability analysis and parameter design guidelines are provided. Hardware-in-the-loop results validate the effectiveness and superiority of the proposed scheme.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"255 ","pages":"Article 112781"},"PeriodicalIF":4.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146078812","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}

{"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 ,&nbsp;Liu Zhaobin ,&nbsp;Sheng Chenxing ,&nbsp;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":"2026-06-01","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}

{"title":"Real-time performance evaluation and enhancement of industrial-grade overcurrent relay for feeder protection in inverter interfaced distribution network","authors":"Arjita Pal ,&nbsp;Rakesh Shamrao Patekar ,&nbsp;Rabindra Mohanty ,&nbsp;Bijaya Ketan Panigrahi","doi":"10.1016/j.epsr.2026.112760","DOIUrl":"10.1016/j.epsr.2026.112760","url":null,"abstract":"<div><div>This paper presents the performance evaluation of a commercially available overcurrent relay (OCR) in a distribution system with inverter-interfaced source. A practical situation of an inverter operating at unity power factor is considered for the study. The inverter is interfaced with the distribution grid through a delta (Δ)-star-grounded (Yg) transformer. The available OCR operations for different fault types, including ground and phase faults are analyzed. In such a system, it is found that the ground fault protection is not a challenge, which can be easily detected without a change in the settings of OCR. However, phase fault detection is a problem using OCR with existing settings. A method is proposed to detect phase faults using negative-sequence superimposed current. Different fault types are also classified using current phasors from the inverter side measurement. A Power Hardware-in-the-Loop (PHIL) test bed is developed with Typhoon HIL and Real-Time Digital Simulator (RTDS) to verify the performance of the OCR during ground faults and to validate the proposed algorithms for phase faults in a modified CIGRE low voltage distribution network.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"255 ","pages":"Article 112760"},"PeriodicalIF":4.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146039058","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}

{"title":"Day-ahead coordinated operation strategy for a price-maker virtual power plant with multiple prosumers","authors":"Wei Wang ,&nbsp;Shunfu Lin ,&nbsp;Bo Zhou ,&nbsp;Liang Qian ,&nbsp;Yunwei Shen ,&nbsp;S.M. Muyeen","doi":"10.1016/j.epsr.2026.112777","DOIUrl":"10.1016/j.epsr.2026.112777","url":null,"abstract":"<div><div>With the advancement of electricity market reforms and the rapid development of distributed energy resources, virtual power plants (VPPs) and prosumers have emerged as new market participants. However, individual prosumers may fail to meet market entry thresholds and lack market competitiveness due to scale constraints. This paper proposes a coordinated operation strategy for a price-maker VPP aggregating multiple prosumers to participate in day-ahead energy and ancillary services markets, aiming to improve VPP profitability and reduce prosumers’ operational costs. First, a market clearing model based on price quota curves is established. Then, a mixed game framework is constructed to characterize the complex interest interactions between the VPP and prosumers. Furthermore, risk-averse and opportunity-seeking decision models are developed based on the information gap decision theory to address price uncertainties. Finally, a hybrid solution method is employed to solve the model while protecting prosumers' commercial privacy. Simulation results demonstrate that the VPP aggregating prosumers for market participation reduces total operational costs by 14.4 %, with the mixed game framework providing an additional 1.9 % reduction. Moreover, the risk-averse and opportunity-seeking decision models can accommodate different risk preferences of the VPP.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"255 ","pages":"Article 112777"},"PeriodicalIF":4.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146039172","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}

{"title":"Ultra-short-term wind power forecasting based on multi-scale dual-domain fusion","authors":"Zijie Wei,&nbsp;Yuxing Mao,&nbsp;Hengyu Yan,&nbsp;Ruidi Yang","doi":"10.1016/j.epsr.2026.112768","DOIUrl":"10.1016/j.epsr.2026.112768","url":null,"abstract":"<div><div>Ultra-short-term wind power forecasting is crucial for grid stability amid rising wind energy penetration. Wind power generation data inherently exhibits interactive characteristics in both the temporal domain (time-series evolution) and spatial domain (inter-sensor correlations). Existing methods often overlook this complex spatiotemporal interaction, resulting in limitations in prediction accuracy. We propose a Multi-Scale Dual-Domain Fusion Network (MDFNet) with three components: (1) a multiscale causal module with parallel convolutions to capture short-term and long-term trends without future leakage; (2) a sensor graph via MIC to model spatial dependencies with graph attention networks; and (3) a dual-domain fusion module using FFT to extract key frequency bands for adaptive fusion. A novel loss function is proposed, which innovatively integrates point-wise errors and trend errors to optimize the training process. Compared to the top baseline, our method cuts prediction root mean square error (RMSE) by 6.08%, 3.46%, and 6.41% and mean square error (MSE) by 11.78%, 6.80%, and 12.49% across three multi-scale tasks. These results show MDFNet outperforms existing methods in spatiotemporal feature decoupling and fusion, offering insights for enhancing safety and efficiency in high-penetration wind systems.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"255 ","pages":"Article 112768"},"PeriodicalIF":4.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146039173","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}