Iet Generation Transmission & Distribution最新文献

{"title":"Front Cover: Multi-Dimensional Stability Constrained Bi-Level Topology Optimisation Method for HVDC Systems Embedded in Dense AC Grids","authors":"Mingxin Yan,&nbsp;Ying Huang,&nbsp;Guoteng Wang,&nbsp;Hui Cai,&nbsp;Zheng Xu,&nbsp;Xingning Han","doi":"10.1049/gtd2.70281","DOIUrl":"https://doi.org/10.1049/gtd2.70281","url":null,"abstract":"<p>The cover image is based on the article <i>Multi-Dimensional Stability Constrained Bi-Level Topology Optimisation Method for HVDC Systems Embedded in Dense AC Grids</i> by Ying Huang et al., https://doi.org/10.1049/gtd2.70249.\u0000\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"20 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.70281","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147567645","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":"Two-Stage Load Transfer Strategy for Multi-Energy Multi-Microgrids Based on Energy Hub Modelling","authors":"Hui Wang,&nbsp;Xin Li,&nbsp;Li Liu,&nbsp;Yingying Zheng","doi":"10.1049/gtd2.70208","DOIUrl":"https://doi.org/10.1049/gtd2.70208","url":null,"abstract":"<p>In the face of sudden load fluctuations or energy shortages, load transfer in multi-energy multi-microgrid (MMG) plays a critical role in ensuring energy supply security. Traditional MMG load transfer strategies typically prioritise minimising load shedding while often neglecting inter-multi-energy microgrid (MG) coordination and the regulation burden on energy devices. To address these limitations, this paper proposes a load transfer strategy for MMG systems based on the energy hub (EH) model. First, a comprehensive energy hub-based modelling framework is established for the MMG. Then, a two-stage load transfer strategy is introduced: the first stage addresses local energy shortages within individual MGs by leveraging internal resources; the second stage is activated when local resources are insufficient, enabling coordinated energy transfer across microgrids to alleviate multi-energy shortages from a system-wide perspective. Furthermore, energy flow path analysis is conducted to explore optimal energy routing and inter-MG interactions under different load scenarios. Simulation results demonstrate that, compared with conventional strategies, the proposed approach reduces operational cost variation by 10.06% and 7.63%, respectively, decreases the regulation burden on internal devices, and enables effective inter-MG load coordination. These results confirm the proposed method's effectiveness in enhancing the economic efficiency and operational stability of MMG.</p>","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"20 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.70208","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147653349","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":"Analytical Frameworks and Theories of Electric Power in Non-Linear Circuits","authors":"Rafael Escudero,&nbsp;Luis Ibarra","doi":"10.1049/gtd2.70268","DOIUrl":"https://doi.org/10.1049/gtd2.70268","url":null,"abstract":"<p>Electrical signals, especially currents, have significant distortions in modern power grids, mainly due to the increased inclusion of non-linear components and the shift towards decentralized power grids. Hence, the traditional power decomposition—active, reactive, apparent—becomes invalid, encouraging the pursuit of a generalized electrical power theory, one capable of providing both a mathematical formulation and a formal definition of power. Several theories have been proposed, but no consensus has been reached. Even the IEEE 1459 standard, devoted to this matter, recognizes the nonagreement among the different approaches. Consequently, a major challenge arises: What are the suitable definitions and methods for assessing power in grids with distorted signals? This study conducts a comprehensive systematic review of the literature to situate key developments in power theories. A deep analysis is provided, focusing on the mathematical nature of each seminal theory, their practical implementation directions, suitability for online applications, validity challenges, and reasons for their divergence. Furthermore, it identifies which theories have become the most popular within the time-domain approaches and the frequency-domain approaches. Despite the importance and maturity of this topic, the findings suggest that consensus will not be reached in the immediate future. There is a considerable ongoing debate about the definition of electrical power, which stems from the fact that each proposed power theory is currently challenged and undergoing rigorous scrutiny.</p>","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"20 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.70268","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147315618","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":"Predicting the Fault-Ride-Through Probability of Inverter-Dominated Power Grids Using Machine Learning","authors":"Christian Nauck,&nbsp;Anna Büttner,&nbsp;Sebastian Liemann,&nbsp;Frank Hellmann,&nbsp;Michael Lindner","doi":"10.1049/gtd2.70264","DOIUrl":"https://doi.org/10.1049/gtd2.70264","url":null,"abstract":"<p>Assessing and mitigating risks in future power grids requires comprehensive analysis of their dynamic behaviour. Probabilistic stability analyses, which evaluate large ensembles of disturbances, are well-suited for this purpose and became mandatory for many grid operators. However, the computational costs of simulations impose strict limits on the number of configurations that can be evaluated. This study demonstrates how machine learning (ML) can address this challenge by enabling efficient prioritization of scenarios for detailed analysis in probabilistic dynamic stability assessments. We apply fault-ride-through probability—a practical metric measuring the likelihood of all grid components remaining within operational bounds after a fault—to show how ML can bridge the gap to real-world applications. A new dataset comprising thousands of dynamic simulations of synthetic power grids is generated to train ML models. Results reveal that ML models not only accurately predict fault-ride-through probabilities but also effectively rank the criticality of buses, identifying components most likely to destabilize the system and requiring further analysis. Importantly, the models generalize well to the IEEE-96 Test System, underscoring their robustness and scalability. This work highlights the transformative potential of ML in enabling efficient, scalable probabilistic stability studies, paving the way for integration into contingency screening for real-world grid operations.</p>","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"20 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.70264","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147315542","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":"Metaheuristic-Based Load Frequency Control of Multi-Source Renewable Systems With SMES and AC-DC Parallel Tie-Lines","authors":"Md. Shahan Sarker","doi":"10.1049/gtd2.70266","DOIUrl":"https://doi.org/10.1049/gtd2.70266","url":null,"abstract":"<p>Maintaining frequency stability in interconnected, renewable-rich power systems is challenging due to low inertia and stochastic generation. This paper introduces a hybrid evolutionary exploration algorithm (HEEA) that combines the genetic algorithm (GA) and grey wolf optimiser (GWO) to co-tune PID controller gains and superconducting magnetic energy storage (SMES) parameters in a two-area, multi-source system linked by parallel AC–DC tie-lines. Compared to a triple-PID controller without SMES (best classical baseline), HEEA with SMES reduces the settling time by 84.4% in Area 1 (6.8813 to 1.0732 s), 64.6% in Area 2 (5.6571 to 2.0008 s) and 53.0% for tie-line power (5.0692 to 2.3798 s). Against contemporary metaheuristics (PSO, GA, GWO, SCA, ABC, WOA, DBOA and HHO), HEEA achieves the lowest ITAE (0.0003797) with faster convergence and improved overshoot/undershoot across 70 runs. Sensitivity tests variations of the parameter and renewable fluctuations under <span></span><math>\u0000 <semantics>\u0000 <mo>±</mo>\u0000 <annotation>$pm$</annotation>\u0000 </semantics></math> 25% and <span></span><math>\u0000 <semantics>\u0000 <mo>±</mo>\u0000 <annotation>$pm$</annotation>\u0000 </semantics></math> 50% confirm robustness. This approach enables grid operators to achieve faster recovery and tighter frequency regulation in renewable-dominated multi-area systems using AC–DC tie-lines and SMES.</p>","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"20 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.70266","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147315538","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":"Scenario Generation Approach of Regional Wind Power Driven by Meteorological Data","authors":"Qian Kai,&nbsp;M. X. Wang,&nbsp;Heng Yan,&nbsp;Shengyuan Zhou","doi":"10.1049/gtd2.70244","DOIUrl":"https://doi.org/10.1049/gtd2.70244","url":null,"abstract":"<p>Regarding the time-series scenario generation of regional wind power, conventional methods face challenges in accurately characterizing the variation patterns of the wind power under installed capacity expansion. To address this issue, this paper presents a historical meteorological data-driven regional wind power scenario generation approach, which can generate time-series regional wind power scenarios under historical weather conditions and expected wind power capacity expansion. First, wind power aggregation points (WPAPs) in the study region are selected based on the consistency of the wind turbine models and wind speeds among wind farms. Then, the wind speed spatial distribution in the study region is classified into several patterns, and a dual-layer convolutional neural network (DCNN) is designed to model the dependence of the regional wind power on wind speeds and installed capacities at WPAPs for each pattern. Finally, the expected installed capacities of wind power are aggregated to WPAPs to enable the trained DCNN models to generate regional wind power scenarios driven by the historical weather data. By means of the meteorological reanalysis data, the proposed approach can provide time-series regional wind power scenarios with heterogeneity and a high degree of credibility for long-term planning. Case studies in Shandong Province, China, are carried out to verify the effectiveness of the proposed approach.</p>","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"20 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.70244","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147320917","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":"Impact of P2P Trading on the Dynamic Performance of Transmission Grids","authors":"Ekaterina Dudkina,&nbsp;Emanuele Crisostomi,&nbsp;Federico Milano","doi":"10.1049/gtd2.70263","DOIUrl":"https://doi.org/10.1049/gtd2.70263","url":null,"abstract":"<p>Peer-to-peer (P2P) markets facilitate the integration of distributed energy resources, reduce distance between generation and consumption, and provide a convenient opportunity to reduce congestion on the transmission grid. In this context, P2P markets are usually investigated under the assumption that P2P trades are limited in size and number, thus ignoring the possible impact of the transmission network and its dynamic performance. However, the transmission grid is required to accommodate all the transactions that can not be satisfied in P2P markets, for example, due to local high prices or low generation. Accordingly, as P2P markets gain momentum, there is an increasing interest in assessing their potential impact on the transmission grid dynamic performance. This paper evaluates through extensive realistic simulations, the sensitivity of the frequency of the transmission grid to different parameters related to the P2P markets, such as variations in price, number of market participants, frequency of market clearance, and proposes a countermeasure to mitigate such an impact. The results show that P2P trading indeed affects system dynamics and an increasing number of P2P transactions may even lead to instability of the transmission system, but the proposed market price strategies are able to mitigate such undesirable effects.</p>","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"20 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.70263","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147315632","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":"Deep Reinforcement Learning and IoT for Renewable Energy Optimization in Smart Buildings: A Comprehensive Review","authors":"Tehseen Mazhar,&nbsp;Sghaier Guizani,&nbsp;Habib Hamam","doi":"10.1049/gtd2.70255","DOIUrl":"https://doi.org/10.1049/gtd2.70255","url":null,"abstract":"<p>This paper presents the implications of integrating deep reinforcement learning (DRL) and the Internet of Things (IoT) in optimizing energy management, specifically in smart buildings for sustainable urban development. It further explores how DRL, along with real-time IoT sensor-based data, helps improve energy performance in responding to actual HVAC, lighting and renewable energy conditions. Key techniques like genetic algorithms, particle swarm optimization and hybrid techniques are critically examined in maintaining an equilibrium between energy consumption versus renewable sourcing in smart building models. Boundary-preserving strategies and federated learning appear as techniques addressing expansibility and information protection difficulties, notably over IOT systems. Further research would include technology in local processing and situation-responsive DRL to enhance more independent, user-focused and ecologically responsive buildings. This review provides a roadmap for implementing robust, privacy-conscious AI frameworks in smart buildings, underlining their potential to cut energy use and contribute to broader environmental goals.</p>","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"20 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.70255","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147320876","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":"Updated Frequency Response Model in Modern Power Grids: An Analytical Approach and Parameters Estimation","authors":"Sirwan Shazdeh,&nbsp;Sharara Rehimi Sharara,&nbsp;Hassan Bevrani","doi":"10.1049/gtd2.70265","DOIUrl":"https://doi.org/10.1049/gtd2.70265","url":null,"abstract":"<p>Emerging converter-based resources (CBRs) results in changing dynamics of the power grids. Hence, the conventional frequency response model (FRM) cannot properly cover the frequency dynamics of the modern power grids. An effective approach is required to achieve an updated FRM which has been missing in the previous studies. In this regard, this paper presents an analytical approach to provide the updated FRM regarding the penetration of the grid-forming (GFM)-based units in power grids. To this end, the power grid is divided into the GFM and synchronous generation (SG) areas from the frequency response point of view. After providing the updated FRM, a sequential procedure is followed to estimate the unknown parameters in the model. Firstly, the total moment of inertia (MoI) of the power grid is estimated through an optimization-based method called pattern search. Then, the MoI values of the SG and GFM areas are calculated based on the optimization method and the obtained data from the power grid. Finally, according to the obtained MoI values and acquired data, the rest of the proposed FRM parameters are computed using the same method. To verify the obtained updated FRM and the accuracy of the estimated parameters, some scenarios are applied to the modified 39-bus IEEE power system in the MATLAB/Simulink environment.This research paper offers an analytical approach for obtaining an updated FRM. Then, it proposes an estimation approach to figure out the parameters of the updated FRM in modern power systems using data acquisition from PMUs. 2</p>","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"20 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.70265","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147315565","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":"Preventive Control Considering Stability Constraints for Repeated Low Voltage Ride Through Events","authors":"Zhichong Cao,&nbsp;Cheng Liu,&nbsp;Chao Jiang,&nbsp;Rijun Wang,&nbsp;Jianyi Che,&nbsp;Rundong Tian","doi":"10.1049/gtd2.70258","DOIUrl":"https://doi.org/10.1049/gtd2.70258","url":null,"abstract":"<p>With the continuous increase in renewable energy penetration, power systems are facing two major challenges: first, the reduction in system voltage stability margin and significantly weakened resilience to disturbances; second, although grid-integration control strategies such as low voltage ride-through (LVRT) in renewable energy units are increasingly critical to system stability, their inherent control limitations introduce new dynamic stability issues that seriously threaten the secure operation of power systems. To address these challenges, this paper proposes a preventive control method that incorporates short-term voltage stability constraints to enhance system stability margins. First, an equivalent model for grid-connected wind power was developed to analyse the mechanism of voltage instability at the point of common coupling (PCC) post-disturbance, summarizing the impact of wind turbine generators on system voltage stability. Furthermore, the system was partitioned based on the admittance matrix, and short-term voltage stability assessment indices suitable for different regions were established. Subsequently, considering the system short-circuit ratio (SCR), static voltage stability constraints, and short-term voltage stability constraints, an optimal preventive control strategy was derived using a particle swarm optimization (PSO) algorithm, with the objective of minimizing control costs. Finally, the proposed preventive control method was validated through three simulation case studies. In the 10-machine 39-bus system and a 100-bus test system, the truncated mean of the voltage deviation index reduction rate reached 61.26% and 47.52%, respectively. Compared to conventional methods, the proposed approach generated more favourable power flow optimization outcomes, effectively enhanced the system's ability to withstand transient disturbances, and provided an engineering-feasible control strategy for future power systems.This paper proposes a preventive control method that considers short-term voltage stability constraints under new power system scenarios. The proposed method effectively enhances the system's capability to mitigate short-term voltage risks and improves voltage stability margins.</p>","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"20 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.70258","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147320764","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}