Journal of Modern Power Systems and Clean Energy最新文献

{"title":"Multi-Turbine Cooperative Frequency Regulation Control for Wind Farms Considering Torque-Limited Inertial Control Power Characteristics","authors":"Wei Gu;Minghui Yin;Qiang Li;Yaran Li;Zaiyu Chen;Qun Li","doi":"10.35833/MPCE.2025.000547","DOIUrl":"https://doi.org/10.35833/MPCE.2025.000547","url":null,"abstract":"Torque-limited inertial control (TLIC) offers advantages of stabilizing wind turbine (WT) operation and mitigating secondary frequency dip. When large-scale wind farm (WF) clusters simultaneously employ TLIC to provide power support, unnecessary frequency recoil (FR) phenomenon may occur, persistently degrading the frequency regulation performance. To address this issue, the paper analyzes the frequency response characteristic under TLIC method, and derives the conditions for FR under simultaneous and immediate support and simultaneous and delayed support, with the latter exhibiting more pronounced FR effects. The root cause of FR is identified as excessive power increments. Hence, the multi-turbine cooperative frequency regulation control method for WFs considering the TLIC power characteristics is proposed. By sequentially activating TLIC among WTs, the excessive power increment from simultaneous support is mitigated, and the gradual power reduction of the engaged WTs can be compensated. Experimental validation is conducted based on the test bench of wind-integrated power system, which demonstrates that the proposed method effectively avoids FR and further enhances the frequency nadir.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"14 4","pages":"1297-1307"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11293065","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148626506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Blockchain-Enabled Cyber-Resilient Trading Framework for Virtual Power Plants","authors":"Yanjia Wang;Han Zhong;Alexis P. Zhao;Mohannad Alhazmi;Da Xie;Xitian Wang","doi":"10.35833/MPCE.2025.000244","DOIUrl":"https://doi.org/10.35833/MPCE.2025.000244","url":null,"abstract":"The rapid expansion of distributed energy resources (DERs) has driven the emergence of virtual power plants (VPPs) as decentralized energy trading platforms that enhance grid flexibility and market efficiency. However, the increasing reliance on digital infrastructure has exposed VPP transactions to cyber-threats such as double-spending attack, Sybil attack, smart contract tampering, and malicious data injection attack, undermining transaction integrity and market stability. Traditional cybersecurity mechanisms, which often rely on centralized verification, are vulnerable to single points of failure and lack adaptive defense strategies. To address these challenges, this paper proposes a blockchain-enabled cyber-resilient trading framework that integrates game-theoretic smart contract optimization, Byzantine fault tolerance (BFT) consensus mechanisms, and zero-knowledge proof (ZKP) authentication to enhance cybersecurity, efficiency, and privacy in VPP transactions. The proposed framework leverages a multilayered cyber-security approach where game-theoretic modeling ensures optimal cybersecurity investment by balancing transaction efficiency and cybersecurity costs. A Stackelberg game modeling models the interactions among prosumers, VPP aggregators, and cyber attackers, allowing the system to allocate cybersecurity resources strategically. ZKP authentication ensures that transactions are validated without exposing sensitive trading information, mitigating privacy risks while maintaining transparency. To enhance resilience, a reinforcement learning-based adaptive defense mechanism continuously optimizes cybersecurity policies against evolving cyber-threats, improving attack detection and mitigation efficiency. The proposed framework incorporates multi-signature validation and BFT consensus mechanisms to prevent unauthorized modifications, while smart contracts autonomously execute transactions under predefined cybersecurity policies.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"14 4","pages":"1185-1197"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11141564","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148628298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Control-Level Sub-Synchronous Oscillation Source Identification for IBRs-Dominated Power Systems Based on Initial Instantaneous Power Characteristics","authors":"Yanhui Xu;Yundan Cheng;Le Zheng","doi":"10.35833/MPCE.2025.000464","DOIUrl":"https://doi.org/10.35833/MPCE.2025.000464","url":null,"abstract":"Sub-synchronous oscillations (SSOs) originating from inverter-based resources (IBRs), which can be specifically induced by different controls within IBRs, have become a significant challenge to the stability of power system. Identifying the specific control responsible for the oscillation is crucial for effective oscillation mitigation. However, the coupling of multi-frequency disturbance terms, along with the complexities introduced by nonlinear elements, makes it difficult to isolate the impact of individual control. To address this issue, this paper proposes a control-level SSO source identification method for IBRs-dominated power systems based on initial instantaneous power characteristics. First, the expressions of instantaneous power during SSOs induced by different controls are derived for grid-following (GFL)-IBRs and grid-forming (GFM)-IBRs. The causes of current saturation triggering are revealed, and the coupling effects introduced by nonlinear elements are examined. Then, the initial instantaneous power characteristics of grid-side converter (GSC)-control-induced oscillations (GCIOs) and synchronization-control-induced oscillations (SCIOs) are analyzed, by comparing cases where the saturation limit is reached and not reached. The proposed method incorporates the dynamic characteristics of IBR controls, and can identify the SSO source using measurement data at the IBR port. Finally, the effectiveness of the proposed method in various SSO scenarios is validated through real-time simulations. Comparisons with existing methods demonstrate that the proposed method achieves higher identification accuracy.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"14 4","pages":"1246-1258"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11318103","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148625946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Net Load Forecasting for Renewable Energy Integrated Power Systems: A Critical Review","authors":"Nusraat Nawreen;Nima Amjady;Rakibuzzaman Shah;S. M. Muyeen","doi":"10.35833/MPCE.2025.000940","DOIUrl":"https://doi.org/10.35833/MPCE.2025.000940","url":null,"abstract":"Net load (NL) refers to the difference between gross demand and variable renewable energy (RE) generation. As the integration of RE continues to grow, the variability and uncertainty of power systems increase, creating significant challenges for power system operators due to the intermittent behavior of RE sources. NL forecasting (NLF) has become crucial to maintaining the reliable and secure operation of power systems. This paper critically reviews the state-of-the-art NLF models in RE-integrated power systems, with a particular focus on emerging techniques such as Transformer models and generative artificial intelligence (Gen-AI) models. This paper systematically explores and analyses various data preprocessing, feature engineering (feature selection and extraction), and hyperparameter tuning methods as well as forecasting engines used in NLF. Furthermore, this paper categorizes the NLF models with corresponding strengths and challenges. In addition, an assessment of the interpretability, scalability, and applicability of NLF models is presented, highlighting their performance under varying levels of RE penetration. This paper also outlines challenges for NLF, e. g., the quality of data and the spatial and temporal scales. Finally, the future research directions are outlined based on the identified gaps in NLF.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"14 4","pages":"1210-1227"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11522664","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148625950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptive Robust Optimization for Operation of Active Distribution Networks in Real-Time Energy Markets","authors":"Ali Arab-Kuhsar;Morteza Rahimiyan;Pierluigi Siano;Mahsa Azarnia","doi":"10.35833/MPCE.2025.000481","DOIUrl":"https://doi.org/10.35833/MPCE.2025.000481","url":null,"abstract":"Energy management system (EMS) and volt-var optimization (VVO) programs are jointly employed to achieve the efficient operation of active distribution networks (ADNs). However, current studies often overlook that the operation of ADNs is coupled with trading energy in real-time (RT) energy markets. To fill this gap, this paper develops an adaptive robust optimization (ARO) model of ADNs in RT energy markets. The studied ADN consists of photovoltaic (PV) units, electric vehicle (EV) charging stations, and flexible demands interconnected through a medium-voltage distribution network. Through the proposed model, the integrated EMS and VVO programs can decide to offer energy in the hourly RT energy market, schedule flexible demands, and adjust slow-acting devices (e. g., on-load tap changers and capacitors), while anticipating the operation conditions of the ADN under uncertain prices, charging power level of EVs, and available PV power generation through the uncertainty sets. Once the market outcomes are known, the integrated EMS and VVO programs dispatch the fast-acting devices of PV units and EV charging stations. The results of a realistic case study indicate that prioritizing the reduction of voltage violations leads to lower energy trading in the RT energy market and a decrease in profit.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"14 4","pages":"1361-1373"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11395464","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148626054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiscale Energy Coordination of Integrated Thermal Power-Energy Storage System for Enhanced Primary Frequency Regulation","authors":"Chenhui Zhang;Xianzhuo Sun;Lei Ding;Weiyu Bao;Vladimir Terzija","doi":"10.35833/MPCE.2025.000607","DOIUrl":"https://doi.org/10.35833/MPCE.2025.000607","url":null,"abstract":"The increasing integration of renewable energy sources weakens system frequency security, requiring enhanced primary frequency regulation (PFR) from conventional thermal power units (TPUs). In this case, integrating energy storage system (ESS) with TPUs offers a promising solution. However, most existing methods primarily focus on turbine dynamics while overlooking multiscale coordination among ESS, turbine, and boiler, thereby limiting sustained power support and safe operation of TPUs. To this end, this paper firstly analyzes the multiscale energy dynamics of TPUs under power disturbances, revealing that insufficient boiler thermal storage can cause secondary frequency dips (SFDs). An analytical energy balance equation is then established to quantify the ESS energy requirement for compensating thermal storage. Based on this, a novel multiscale energy coordination method for the integrated thermal power-energy storage system (TPESS) is developed, including three dedicated controls: a deviation-based power control (DPC) for ESS, a coordinated energy allocation (CEA) between thermal storage and ESS, and a fuel-assisted restoration (FAR) for state of charge (SOC). This method enables the ESS to take the leading role in PFR while simultaneously coordinating with the boiler thermal storage and fuel systems to ensure safe operation and state recovery. Simulation in DIgSILENT/PowerFactory validates the effectiveness of the proposed method in enhancing system frequency security and boiler safety.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"14 4","pages":"1259-1271"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11471003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148625949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"LLM-Augmented Multi-Agent System for Trading Behavior Modeling in Coupled Electricity-Carbon Markets","authors":"Xiyuan Zhou;Yuheng Cheng;Haozhe Lu;Wenxuan Liu;Yan Xu;Junhua Zhao","doi":"10.35833/MPCE.2025.000645","DOIUrl":"https://doi.org/10.35833/MPCE.2025.000645","url":null,"abstract":"The deep integration of electricity and carbon markets introduces new challenges for trading behavior modeling, driven by strategic diversity, adaptive agent behaviors, and bidirectional market feedback. Traditional optimization and gametheoretic formulations, which rely on fixed rationality assumptions and static behavioral structures, often fail to capture these dynamics with sufficient fidelity. This paper proposes a large language model (LLM)-augmented multi-agent system (MAS) framework for trading behavior modeling in coupled electricity-carbon markets, where LLMs act as cognitive agents capable of generating context-dependent strategies, interpreting market rules, and responding to evolving system states. The MAS provides a structured environment for interaction among heterogeneous agents, enabling more expressive, adaptive, and interpretable representations of cross-market behaviors. Case studies based on China's coupled electricity - carbon markets demonstrate that the proposed framework can reflect realistic bidding responses, emission-driven adjustments, and market feedback dynamics. This paper also identifies key challenges and outlines future directions including constraint-aware generation to ensure feasibility, structured reasoning and memory to enhance interpretability, and improved computational efficiency to enable scalable MAS deployment.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"14 4","pages":"1465-1478"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11370553","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148627291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Three-Stage Distributionally Robust Optimization Planning of Island Microgrid Cluster Considering Marine Environmental Uncertainties","authors":"Deng Ma;Chengjin Ye;Xiran Wang;Jiaming Wang","doi":"10.35833/MPCE.2025.000600","DOIUrl":"https://doi.org/10.35833/MPCE.2025.000600","url":null,"abstract":"In order to fully utilize the energy resources of different offshore islands and improve the power reliability, establishing island microgrid (IMG) clusters has become a promising way for marine energy systems. However, the relatively harsh and variable weather condition poses challenges to the planning of IMGs. This paper proposes a three-stage distributionally robust optimization (DRO) planning model to configure IMG clusters considering marine environmental uncertainties. Firstly, an energy management framework for IMG clusters is established, which includes diesel generator, renewable energy generation, and fixed battery energy storage as the island energy supply components, and utilizes the submarine cables (SCs) as well as mobile energy storage vessels (MESVs) as the energy interconnections among different islands. Then, the ambiguity set for marine environmental uncertainties, which include the wind speed, solar irradiance, ocean current, and wave, is constructed based on Wasserstein distance. On this basis, the proposed planning model is established to configure island energy supply and link components. Specifically, the first stage determines the configuration of SCs and the capacity of energy storage systems and MESVs. The second stage determines the operational decisions and the third stage solves the real-time power dispatch of IMGs. Finally, the two-layer column constraint generation algorithm is utilized to solve the proposed planning model. A realistic island cluster in the South China Sea is selected for case study. The results show that the proposed planning model can greatly enhance the power reliability and reduce 30.8% operational costs of the IMG. In a real typhoon scenario, the expected energy not supplied (EENS) can be reduced by 59.3% through the adoption of the proposed planning model.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"14 4","pages":"1399-1412"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11473941","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148627769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-Proportion Reactive Power Compensation Control for Delta-Connected High-Voltage Transformerless Battery Energy Storage System via Optimal Zero-Sequence Current Injection","authors":"Xiaoping Zhou;Yizhen Hu;Lerong Hong;Qianming Xu;Fenfen Zhu;Lingfeng Deng;Lei Zhang;Hanting Peng;Zhen Zhang;Le Li;Ruotong Wang","doi":"10.35833/MPCE.2025.000516","DOIUrl":"https://doi.org/10.35833/MPCE.2025.000516","url":null,"abstract":"The structural configuration of delta-connected high-voltage transformerless battery energy storage system (D-HVT-BESS) inherently introduces second-order ripple currents (SORCs) into the battery cells. Under low power factor conditions, the SORCs exhibit frequent zero-crossing, which accelerates battery aging and compromises the accuracy of state monitoring. Therefore, a high-proportion reactive power compensation control method for D-HVT-BESS via optimal zero-sequence current injection is proposed. The key to the proposed method is to use zero-sequence current to adjust the reactive-to-active power ratio of each phase leg. This adjustment enhances the power factor per phase, thereby eliminating the zero-crossing of SORCs. Furthermore, an optimization model is formulated to minimize the system power loss induced by zero-sequence current. The optimization model achieves this by optimizing the amplitude and phase angle of zero-sequence current. Additionally, to mitigate the inter-phase state of charge (SOC) imbalance caused by the zero-sequence current, an inter-phase SOC balancing control strategy based on an absolute phase selector is developed, enabling real-time optimization of the absolute phase of zero-sequence current to achieve dynamic SOC equalization among phases. Finally, a 380 V/100 kW/50 kWh experimental prototype is constructed for validation. Experimental results verify the effectiveness and operational feasibility of the proposed method.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"14 4","pages":"1335-1347"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11370565","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148626289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Data-Driven Multi-Agent Framework for Electricity Market Simulation Using Practical and Heterogeneous Bidding Strategy Spaces","authors":"Hanning Mi;Ji Qiao;Ye Li;Zibo Wang;Fujia Han;Sijie Chen","doi":"10.35833/MPCE.2025.000212","DOIUrl":"https://doi.org/10.35833/MPCE.2025.000212","url":null,"abstract":"Existing electricity market simulation research assumes that energy providers share theoretical and homogeneous strategy spaces. However, practical bidding strategies differ significantly from those based on theoretical simulation. The factors that determine energy providers' bidding patterns are heterogeneous. Ignorance of practical and heterogeneous bidding strategy spaces distorts real market results. To fill the research gap, this paper proposes a data-driven multi-agent framework for electricity market simulation using practical and heterogeneous bidding strategy spaces. Firstly, a clustering algorithm is proposed for extracting practical and heterogeneous bidding strategy spaces from historical bidding strategies. The bidding strategy spaces are formed by the centers. Then, energy providers are modeled by agents with practical and heterogeneous strategy spaces in a multi-agent framework. Finally, the proximal policy optimization is implemented by agents to model the bidding behaviors in markets. Numerical results based on real data from the Australian Energy Market Operator show that market clearing results under practical and heterogeneous strategy spaces are closer to reality than those under theoretical and homogeneous strategy spaces.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"14 4","pages":"1503-1514"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11152640","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148626839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}