Iet Generation Transmission & Distribution最新文献

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"20 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148073345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"20 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148069499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ML Assisted T-Model Feeder Reduction and Convex Fast Reconfiguration Method for Active Distribution Networks With DERs","authors":"Tharmini Thavaratnam,&nbsp;Bala Venkatesh","doi":"10.1049/gtd2.70226","DOIUrl":"https://doi.org/10.1049/gtd2.70226","url":null,"abstract":"<p>Deep electrification of energy systems and massive integration of distributed energy resources (DERs) push the growth of radial distribution networks (RDNs), requiring innovative methods to deal with the increased complexity and enhance current operational tasks. Network reconfiguration (NR) is one of the tools researched and developed during the last 50+ years for large distribution sizes for more robust operations. NR is vital for reliable operation and demands swift, accurate decision-making, prompting distribution utilities to adopt faster solution methods. In this sense, a method is proposed in this paper with the objective of minimising the execution time of reconfigured large RDNs. A T-Model feeder reduction method, a mapping artificial neural network (ANN) method to map feeder demand and power injections of DERs to T-Model parameters, a reduced RDNs representation using T-Models of feeders, and a network reconfiguration method leveraging this reduced network are proposed. The proposed T-Model reduces the number of nodes in RDNs considering connected loads and DERs by around 55%, which leads to significantly reduced network representation and thereby execution time when reconfiguring the RDNs. The proposed method is tested on several systems, including the IEEE 123-Bus network. The execution time is reduced by up to 74.53% while providing the accuracy of at least 97.17%. This method scales well and performs better for active larger RDNs.</p>","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"20 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.70226","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145986776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Active Low-Voltage Ride-Through Control Strategy for Wind Turbines to Improve Transient Stability in Power Systems","authors":"Guangyao Yu,&nbsp;Xiaolin Zheng,&nbsp;Sixuan Wang,&nbsp;Zhenbin Li,&nbsp;Shupeng Li,&nbsp;Naiyuan Liu,&nbsp;Zhenglong Sun","doi":"10.1049/gtd2.70225","DOIUrl":"https://doi.org/10.1049/gtd2.70225","url":null,"abstract":"<p>The increasing integration of wind power poses a challenge to power system transient stability. Conventional low-voltage ride-through (LVRT) control is hindered by passive triggering and delays, while synchronous generator tripping (SGT) incurs economic costs. This study proposes a coordinated strategy that enhances transient stability by combining active LVRT control of Wind Turbine Generators (WTGs) with SGT. The stability mechanism of active LVRT is analysed, and a model of an active LVRT doubly-fed induction generator (DFIG) is developed. An intelligent decision-making platform, employing the Proximal Policy Optimisation (PPO) deep reinforcement learning algorithm, dynamically optimises active LVRT parameters—start-stop timing, duration, and participating WTG count—based on real-time system states.</p><p>Furthermore, a disturbance severity-graded coordinated control strategy dynamically selects the appropriate control response level between active LVRT and SGT. Simulations confirm that the active LVRT strategy significantly improves transient stability. Its coordination with SGT optimises stability enhancement, demonstrating strong adaptability and robustness across diverse fault scenarios. This research presents a viable approach for ensuring the secure and stable operation of power grids with high penetration of renewable energy.</p>","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"20 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.70225","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145983523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"20 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148068243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 Voronoi Diagram-Based Approach for AC Optimal Power Flow","authors":"Mohammed N. Khamees,&nbsp;Kai Sun","doi":"10.1049/gtd2.70222","DOIUrl":"https://doi.org/10.1049/gtd2.70222","url":null,"abstract":"<p>The primary goal of optimal power flow (OPF) is to optimise the operation of a power system while meeting the demand and adhering to operational constraints. This paper presents a new approach for AC OPF. First, the approach constructs a Voronoi diagram by distributing multiple sample points representing potential solutions throughout the search space. Then, it recursively adds new sample points, including a tentative optimal point from the continuous gradient-projection method, a point in the most sparsely populated region to ensure high fidelity and the connecting point, until the stopping criterion is met. The proposed approach is illustrated in detail using the IEEE 9-bus system and then validated on the IEEE 39-bus and 118-bus systems to verify the quality of the obtained solution.</p>","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"20 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.70222","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145983426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"20 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148066179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analytical Examination of Strategic and Purposeful Behaviours in Peer-to-Peer Energy Trading","authors":"Ali Izanlo,&nbsp;S. Asghar Gholamian,&nbsp;Abdolreza Sheikholeslami,&nbsp;Mohsen Khorasany,&nbsp;Mohammad Verij Kazemi,&nbsp;Atif Iqbal","doi":"10.1049/gtd2.70223","DOIUrl":"https://doi.org/10.1049/gtd2.70223","url":null,"abstract":"<p>Peer-to-peer (P2P) energy trading has emerged as a promising approach for managing energy produced by prosumers. However, the influence of diverse prosumer behaviours on P2P energy trading remains underexplored. This paper provides a comprehensive analysis of the various behavioural patterns shown by sellers in the energy trading market. Unlike previous studies that have examined only limited aspects of prosumer behaviour, this paper, in addition to behaviours such as competition and coalition, also examines the likelihood of strategic behaviours arising in sellers' decision‑making processes. To achieve this, game theory, a robust framework for modelling individual and collective behaviours, is employed. In the proposed model, buyers act as price proposers, while sellers serve as energy suppliers. The behaviour of sellers is modelled under different conditions: competition, coalition, and coalition suspension. The analysis reveals that coalition formation among sellers yields higher payoffs compared to competition behaviour. However, it is also demonstrated that coalitions can be suspended (violated) because prosumers can achieve greater gain by suspending their coalitions. Additionally, prosumers employ the grim trigger strategy to prevent the suspension of coalitions. Additionally, in another section of this article, a new bilateral negotiation mechanism is presented, which is designed to be implemented in a distributed manner within the structure of P2P energy trading. This market-clearing mechanism is designed to consider, in addition to economic constraints, technical and operational constraints and the matching of buyers and sellers. Moreover, the mechanism includes a constraint to prevent the emergence of market power and to address coalition and strategic behaviour by sellers. That constraint is applied so as, on the one hand, not to reduce sellers’ participation and, on the other, to remain effective. To evaluate the proposed approach, the performance of the bilateral negotiation mechanism, the economic aspects of the suggested method, the analysis of prosumer behaviour, the impact of coalition suspension and the effects of purposeful behaviours on P2P trading have been examined.</p>","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"20 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.70223","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145963868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"20 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148066180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Time-Varying Inertia Estimation for Grid-Connected DFIG-Based Wind Farms Using Sensitivity-Guided Clustering and Aggregation","authors":"Yulong Li,&nbsp;Wei Yao,&nbsp;Yongxin Xiong,&nbsp;Hongyu Zhou,&nbsp;Shanyang Wei,&nbsp;Wei Huang,&nbsp;Jinyu Wen","doi":"10.1049/gtd2.70220","DOIUrl":"https://doi.org/10.1049/gtd2.70220","url":null,"abstract":"<p>Accurate inertia estimation for grid-connected doubly fed induction generator (DFIG)-based wind farms is essential for providing inertia support and maintaining frequency stability. However, due to the diversity of operating conditions and control parameters among individual wind turbines, a DFIG-based wind farm cannot be represented as a single equivalent device. In this paper, a time-varying inertia estimation framework based on sensitivity-guided clustering and aggregation is proposed. First, a sensitivity analysis framework is proposed to analyse the impact factors affecting the time-varying inertia of individual DFIGs, using the extended Fourier amplitude sensitivity test. After that, the dominant factor, identified as the virtual inertia control parameter, is selected as the clustering indicator. Subsequently, DFIGs with similar dominant factors are clustered based on limited measurement data, utilizing the unscented Kalman filter to reduce the requirement for extensive measurement devices. The time-varying inertia of the wind farm is then estimated using streaming dynamic mode decomposition with information from each cluster. Simulation and experimental results demonstrate that the proposed framework achieves high-accuracy inertia estimation with limited measurements, reducing the relative error by nearly 10% compared with existing methods. Moreover, it exhibits strong robustness to noise and disturbances, confirming the effectiveness of the inertia estimation.</p>","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"20 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.70220","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145891566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}