Iet Generation Transmission & Distribution最新文献

{"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}

{"title":"A Two-Stage Preference-Aware Model for Electric Vehicle Spatiotemporal Charging Scheduling","authors":"Yueben Zheng,&nbsp;Ronghui Liu,&nbsp;Gaiping Sun","doi":"10.1049/gtd2.70261","DOIUrl":"https://doi.org/10.1049/gtd2.70261","url":null,"abstract":"<p>The popularity of electric vehicles (EVs) is driving the electrification of transportation. However, the high penetration of EVs may lead to road congestion and overload of the distribution network (DN). With the overall goal of optimising the spatiotemporal distribution of EV charging load and reducing the charging navigation cost, a two-stage spatiotemporal scheduling method considering different user preferences is proposed. In Stage I, a multi-agent cooperative framework and an improved Dijkstra algorithm are proposed. To effectively perceive user preferences, this method incorporates dynamic traffic flow, DN information and the value preferences of EV users to improve the charging station (CS) utility function, and sets the search area to reduce the time complexity of the Dijkstra algorithm. In Stage II, variable time-scale charging scheduling is performed for EVs with different charging requirements to optimise the temporal distribution of EV loads. The simulation case verifies the effectiveness of the two-stage EV spatiotemporal scheduling model. The results show that this method provides a low-cost and fast-response charging navigation solution, effectively alleviating traffic congestion and the peak-to-valley difference of DN is reduced by 23.4%.</p>","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"20 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.70261","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147280933","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":"Regional Cooperative Control Method of Reactive Voltage in Distribution Network Containing Distributed Power Sources","authors":"Bo Yang,&nbsp;Chongchong Xu,&nbsp;Xinhui Shi,&nbsp;Chen Wang,&nbsp;Bin Zhao,&nbsp;Yonghai Xu,&nbsp;Yutong Wu,&nbsp;Lei Tan,&nbsp;Yang Li,&nbsp;Jianyong Zhao","doi":"10.1049/gtd2.70259","DOIUrl":"https://doi.org/10.1049/gtd2.70259","url":null,"abstract":"<p>With the rapid increase in penetration of distributed generation predominantly based on renewable energy sources within distribution networks, the inherent volatility and intermittency of distributed generation exacerbate voltage fluctuations and uneven voltage profiles. Concurrently, insufficient coordination mechanisms for diverse controllable devices lead to frequent limit violations of automatic voltage control actions at substations, causing significant voltage control challenges. To address these issues, this study proposes a reactive power voltage control method for distribution networks based on a ‘network partitioning and distributed scheduling’ process. First, the affinity propagation clustering algorithm is employed to partition the network based on the reactive power-voltage sensitivity matrix. Subsequently, a Markov game model is formulated for voltage control within each partition and the twin delayed deep deterministic policy gradient algorithm is utilised for a distributed solution, outputting target reactive power setpoints for both distributed generators and static Var compensators. Compared to conventional real-time control methods, the proposed approach significantly reduces the dependence on centralised communication infrastructures and achieves autonomous regional control of reactive power and voltage. Consequently, it effectively minimises the frequency of automatic voltage control corrective actions and enhances the robustness of voltage control. Finally, the effectiveness of the proposed methodology is validated through simulation case studies utilising the IEEE 33-bus test system and a real-world network model based on the Beijing distribution grid.</p>","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"20 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.70259","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147268955","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":"Energy Management for Low-Carbon Distribution System With Smart Building Prosumers and EVs Interaction","authors":"Armin Mohajeri Avval,&nbsp;Abdolmajid Dejamkhooy","doi":"10.1049/gtd2.70240","DOIUrl":"https://doi.org/10.1049/gtd2.70240","url":null,"abstract":"<p>This paper develops a model for energy management in low-carbon distribution systems that considers multiple goals: reducing costs, cutting emissions, and keeping the grid reliable. The framework links the distribution system operator (DSO) with prosumers such as buildings equipped with solar panels, batteries, and smart parking lots. Parking lots play an essential role since electric vehicles (EVs) can act as mobile batteries, charging when demand is low and returning power to the grid at peak times. A risk-averse method is applied to handle uncertainty in renewable generation, demand, and market prices rather than relying only on fixed forecasts. The model shows that coordinated interaction between DSOs and prosumers can lower costs and emissions while improving system stability. It also highlights the economic opportunities for prosumer owners and EV participants in transitioning toward low-carbon distribution networks. Over a 24 h horizon, the proposed framework reduced operating costs by 13.9%, emissions by 18.1%, and network losses by approximately 2%.</p>","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"20 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.70240","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147288412","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":"Optimized Nonlinear Grid-Forming Controller Based on Feedback Linearization","authors":"Bingwei Jiang,&nbsp;Yongning Chi,&nbsp;Weifang Lin,&nbsp;Yiwen Fan","doi":"10.1049/gtd2.70253","DOIUrl":"https://doi.org/10.1049/gtd2.70253","url":null,"abstract":"<p>The grid-forming (GFM) converters connected renewable energy (RE) to the power grid, which can offer inertia and damping support under disturbance, thereby enhancing the stability of power grid in weak-grid conditions. However, in the controller, the active and reactive power are coupled with each other. Thus brings errors into the GFM controller, leading to the inaccuracy of the GFM controller. To address this issue, this paper designs a feedback controller for GFM converters based on exact linearization. First, considering the characteristics of the GFM converter, the simplified model of the GFM converter is built and the mathematical expression of the GFM controller is derived. Then, the diffeomorphism is built to linearize the nonlinear GFM controller. After that, the feedback controller is designed and the parameters are modified to improve the dynamics of the GFM controller. Finally, simulation results are provided to verify the effectiveness of the feedback controller.</p>","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"20 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.70253","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147268956","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":"Case Study of Vehicle-to-Grid Incentive Design Under Multiple Scenarios: A Policy-Making Perspective","authors":"Muchun Wan,&nbsp;Lin Xia,&nbsp;Yingning Huo,&nbsp;Yuzhong Gong,&nbsp;Guangchao Geng,&nbsp;Quanyuan Jiang","doi":"10.1049/gtd2.70254","DOIUrl":"https://doi.org/10.1049/gtd2.70254","url":null,"abstract":"<p>The commercialization of vehicle-to-grid (V2G) technology is critically hindered by the absence of a cost-effective and user-acceptable incentive mechanism, which limits electric vehicles (EVs) users' willingness to participate in grid dispatch. To address this issue, this paper thoroughly designs the optimal V2G incentive from a policy-making perspective, based on real-world data from Zhejiang Province, China. The methodology involves: 1) defining the lower and upper limits of V2G incentive from user and utility perspectives; 2) categorizing V2G application scenarios (industrial parks, residential communities, public parking lots) and designing each business schemes; 3) constructing optimization models and performing Monte Carlo simulations; 4) conducting a social experiment in Zhejiang Province, China, to modeling user participation willingness based on real data. The quantitative results indicate that the optimal V2G incentives are 0.71 CNY/kWh for industrial parks, 0.77 CNY/kWh for residential communities and 0.32 CNY/kWh for public parking lots. A unified policy incentive is derived as 0.75 CNY/kWh through welfare weighting. Sensitivity analysis reveals that while the power source mix and V2G technology cost have limited impacts, advancements in power battery technology, higher time-of-use tariff differentials and increased subsidies can enhance overall welfare. Furthermore, improved power supply reliability and larger EVs numbers can reduce the optimal V2G incentive, projecting a decline to 0.30 CNY/kWh by 2029.</p>","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"20 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.70254","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147268870","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":"Operation of Microgrids Under Uncertainty With Critical Loads","authors":"Abolfazl Mokhtari,&nbsp;Amir Mahdi Heydari Tafreshi","doi":"10.1049/gtd2.70237","DOIUrl":"https://doi.org/10.1049/gtd2.70237","url":null,"abstract":"<p>Ensuring reliable operation of active microgrids with critical loads, such as emergency infrastructure or energy-sensitive industries, under uncertain conditions such as unplanned grid power outages, introduces a significant challenge to electric power system operators. This paper proposes an optimization framework to address the operational complexities of an active microgrid that participates in the day-ahead and real-time electricity markets while prioritizing uninterrupted power supply to mission-critical loads during unplanned utility grid power outages. Given the constraints of the electrical power grid, this paper utilizes a customized stochastic adaptive robust optimization method to handle various uncertainties that such a microgrid faces, including electricity prices, duration and time of unplanned grid power outages, and renewable energy sources output. This customized method enables the microgrid operator to consider unintentional islanding events rationally using a modified uncertainty budget allocation logic. In order to investigate the effectiveness of the proposed management framework, case studies were conducted using an IEEE base case model. Results have shown that, utilizing the proposed method, the microgrid operator is able to reduce total system costs by 27% while lowering the instances of critical load curtailment by 71% compared to the deterministic approach. In addition, results of assessments demonstrate that using the proposed method, the microgrid is able to operate safely under at least 98% of the simulated days, securing the safe power supply for the critical loads using the proposed framework.</p>","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"20 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.70237","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147280914","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":"A Constrained Online Convex Optimisation Approach for Setpoint Tracking and Deviation Compensation","authors":"Zhong Wang,&nbsp;Jianping Zhang","doi":"10.1049/gtd2.70250","DOIUrl":"https://doi.org/10.1049/gtd2.70250","url":null,"abstract":"<p>Price-based demand response has been widely implemented by load aggregators to guide end-users to optimise power usage patterns. However, a key problem in practical implementation is that the current values of user price elasticity cannot be known before the current price is announced to users. To address this issue, we propose a constrained online convex optimisation (OCO) pricing strategy, which utilises the previous price adjustment and the corresponding user price elasticity to make the current price adjustment, schedule the uncertain load to track the power setpoint and combine energy storage to compensate for the tracking deviations in each round. The proposed OCO approach incorporates adversarial loss functions and adversarial constraints. Notably, these constraints are revealed only after making decisions and can tolerate instantaneous violations, yet they must be satisfied in the long term on average. Besides, dynamic <i>Regret</i> and dynamic <i>Violation</i> are introduced to guarantee the performance of the proposed approach. Finally, step and sinusoidal fluctuations are tested to validate the tracking performance. The findings highlight great application potential of the proposed constrained OCO pricing strategy in EV charging stations.</p>","PeriodicalId":13261,"journal":{"name":"Iet Generation Transmission & Distribution","volume":"20 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.70250","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147320751","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}