International Journal of Electrical Power & Energy Systems最新文献

{"title":"Computing global optimal solutions of the secondary voltage regulation problem","authors":"Pasquale Avella ,&nbsp;Pietro Belotti ,&nbsp;Nicolò Gusmeroli ,&nbsp;Silvia Iuliano ,&nbsp;Alfredo Vaccaro","doi":"10.1016/j.ijepes.2025.111139","DOIUrl":"10.1016/j.ijepes.2025.111139","url":null,"abstract":"<div><div>Optimization problems arising in management of transmission and distribution power grids constitute a broad class of problems with an important characteristic: the power flow constraints. These nonlinear, nonconvex constraints are very challenging for general-purpose optimization solvers, and modeling them with an eye for practical solvability is nontrivial.</div><div>We consider the secondary Voltage Regulation (VR) problem for a transmission power grid, which consists in determining the set-point of the available voltage controllers, which are described by both continuous and discrete variables, subject to power flow constraints and power demand/supply constraints across the network, while minimizing a given cost function, i.e., the average squared deviation of all voltage magnitudes. Due to the nonconvex constraints, VR falls under the class of Mixed-Integer Nonlinear Optimization (MINLO) problems.</div><div>We propose several optimization models for VR that can be tackled by exact, general-purpose MINLO solvers, which find a global optimum by resorting to spatial branch-and-bound algorithms. The modeling step is crucial to find global solutions in reasonable time: we study the impact of several modeling techniques on the ability of a MINLO solver to find tight lower bounds (good convex relaxations). We use a local solver for finding feasible solutions in relatively short time. We run our models on a real-world instance arising from an Italian regional transmission power grid, with 205 buses and 232 edges. We discuss the impact of our techniques in finding good solutions and tight lower bounds.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"172 ","pages":"Article 111139"},"PeriodicalIF":5.0,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Power angle based fault recovery analysis for grid-connected GFM inverters with current limiting","authors":"Jialun Yang ,&nbsp;Yutian Liu ,&nbsp;Hua Ye ,&nbsp;Qianying Mou ,&nbsp;Xiaodong Chu ,&nbsp;Shumin Sun","doi":"10.1016/j.ijepes.2025.111076","DOIUrl":"10.1016/j.ijepes.2025.111076","url":null,"abstract":"<div><div>To meet both the requirements of current limiting and ancillary services during fault ride-through (FRT) of the GFM inverters, various current limiting strategies are developed. Recently, their post-fault behaviors and the switching characteristics have been found to have a significant impact on fault recovery capability. However, the correspondence between the switching conditions and the fault recovery capability has not been fully revealed. The commonalities and uniqueness of various current limiting strategies during fault recovery have not been thoroughly investigated and summarized. To fill these gaps, this paper first graphically illustrates the switching conditions of three typical current limiting strategies. Then, on the basis of the graphical illustration, the initial current-based conditions are converted to be based on the power angle with a fixed range. In addition, the fault recovery capability of three current limiting strategies is investigated and summarized based on the proposed power angle-based switching model. The correspondence between the fault recovery capability and switching conditions is revealed. Consequently, sufficient conditions are obtained for a successful fault recovery. The correctness of the theoretical analyses is verified and validated by numerical simulations and experimental tests.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"172 ","pages":"Article 111076"},"PeriodicalIF":5.0,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 planning method for scalable energy storage station in power system considering multiple application scenarios","authors":"Changfeng Liao ,&nbsp;Li He ,&nbsp;Zhuangxi Tan ,&nbsp;Yong Li ,&nbsp;Chaoyang Chen ,&nbsp;Yijia Cao","doi":"10.1016/j.ijepes.2025.111140","DOIUrl":"10.1016/j.ijepes.2025.111140","url":null,"abstract":"<div><div>The integration of a high proportion of renewable energy sources presents significant challenges to power system operation. To address this issue, this paper proposes a scalable planning method for energy storage station (ESS) deployment tailored to the requirements of new-type power systems. The method comprehensively considers multiple roles of ESS, including facilitating renewable energy integration, mitigating transmission congestion, performing peak shaving, and enhancing system resilience. In the proposed approach, the system’s vulnerability and weak points are first identified, followed by the construction of region-specific fault scenarios. The planning problem is formulated as a large-scale mixed-integer optimization model. To solve it efficiently, a two-stage optimization framework is adopted. In the first stage, the potential support offered by ESS to renewable sources, load-side demands, and grid-side operations is analyzed using graph theory, thereby identifying candidate nodes for ESS installation. In the second stage, the model is decomposed via Benders decomposition into a master problem (ESS planning) and a subproblem (system operation with ESS), enabling efficient solution computation. The effectiveness of the proposed method is validated using real data from a provincial power system in China and a modified IEEE system. Results demonstrate that the proposed ESS planning strategy effectively reduces operational costs, increases renewable energy utilization, alleviates power flow congestion, and minimizes load loss under severe fault conditions, thus improving the system’s economic performance, flexibility, and resilience.</div><div>© 2017 Elsevier Inc. All rights reserved.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"172 ","pages":"Article 111140"},"PeriodicalIF":5.0,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimization configuration method for shared energy storage considering economic consumption of new energy","authors":"Heng Hu ,&nbsp;Hao Lu ,&nbsp;Wenjun Zhao ,&nbsp;Xiguo Cao ,&nbsp;Xiaochao Fan ,&nbsp;Jiading Jiang","doi":"10.1016/j.ijepes.2025.111117","DOIUrl":"10.1016/j.ijepes.2025.111117","url":null,"abstract":"<div><div>In the context of the energy internet, the integration of large-scale shared energy storage (SES) within regional multiple micro energy grids (MMEGs) can effectively enhance the cooperative consumption level of local new energy. To scientifically and rationally configure the parameters of SES systems with a moderate investment scale, this study proposes an SES capacity optimization configuration method that accounts for the economic consumption of new energy for the first time. Initially, the operational service model of the SES system under the interconnection of MMEGs is constructed, and its profitability mechanisms under the economic consumption index are analyzed. Subsequently, for a type of combined cooling, heating, and power micro energy grid cluster (CCHP-MEGC), a bi-level optimization configuration model considering two different time scales is established. The upper-layer model addresses the configuration issues of the SES station during the planning period, while the lower-layer model solves the economic consumption rate and optimization operation problems of the MMEGC system during the dispatch period. Lastly, through case analysis, the economic viability and effectiveness of the proposed configuration method are validated, and the impact of the new energy consumption rate on the SES configuration results is explored. The results demonstrate that compared to full new energy consumption, implementing a moderate power curtailment rate can effectively reduce the required configuration capacity of the SES system and the operational costs of the CCHP-MEGC system, while also shortening the payback period for the SES operator. The findings affirm that the optimal power and capacity of the SES serving multi-energy systems should strive to match the optimal new energy consumption targets to facilitate mutually beneficial outcomes for all participating entities.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"172 ","pages":"Article 111117"},"PeriodicalIF":5.0,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-precision short-term predicting method of wind farm power under extreme low temperature conditions based on physics-informed neural network","authors":"Shiyu Lin,&nbsp;Hongshan Zhao","doi":"10.1016/j.ijepes.2025.111150","DOIUrl":"10.1016/j.ijepes.2025.111150","url":null,"abstract":"<div><div>Extreme cold weather may cause large-scale shutdowns and off-grid events in wind turbines, leading to significant power shortages. However, most existing wind power prediction methods assume ideal output conditions for wind turbines, which may lead to overestimation of short-term prediction accuracy in low temperature conditions. Therefore, we proposed a physics-informed neural network (PINN) to realize high-precision short-term prediction for wind farm power under extreme low temperature conditions. First, the physical behavior of wind turbines under low temperature conditions was analyzed. Second, the PINN based on successive sparse variational modal decomposition (SSVMD) and Informer was constructed, incorporating constraints related to the wind speed–power characteristics at low temperature and low temperature turbine protection mechanisms. Finally, data from a wind farm in Hebei, China, were used for experimental validation. The results demonstrate that the proposed method achieves an R² coefficient of 0.9967 under low temperature conditions. Compared with the method without considering the low temperature effect, the power shortage caused by predicting error is reduced by 46.35 MW. Additionally, this method also exhibits the highest prediction accuracy under normal temperature. Overall, the method can provide crucial support for dispatching wind power in power grids under extreme low temperature conditions.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"172 ","pages":"Article 111150"},"PeriodicalIF":5.0,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced control strategy for wind-storage to compensate hammer effect based on SID and FRR","authors":"Hongchun Shu ,&nbsp;Jing Chen ,&nbsp;Botao Shi ,&nbsp;Guangxue Wang ,&nbsp;Xi Wang ,&nbsp;Shunguang Lei","doi":"10.1016/j.ijepes.2025.111104","DOIUrl":"10.1016/j.ijepes.2025.111104","url":null,"abstract":"<div><div>To address the seasonal variations in frequency regulation requirements (FRRs) for a hybrid renewable hydropower system, this study proposes an advanced wind-storage coordinated control strategy to compensate for the water hammer effect, based on system inertia demand (SID) and FRRs. Firstly, the coupling mechanism and regulation requirements between power system inertia response and primary frequency regulation (PFR) were analyzed. A coordinated wind turbine frequency control strategy based on inertia support-frequency regulation demand was developed, incorporating dual frequency security constraints of minimum frequency (<em>f</em>_min) and maximum rate of change of frequency (<em>RoCoF</em>_max). Subsequently, an improved time-delay control method for energy storage systems (ESSs) is proposed to precisely compensate the reverse regulation power caused by hydraulic hammer effects in hydro units. Furthermore, to fully utilize the regulation capacity of ESSs, a frequency coordination control method is developed that considers both state of charge (SOC) and self-recovery requirements, achieving dual compensation both inside and outside the system’s frequency dead band. Finally, by leveraging the regulation capabilities of both wind turbines and ESSs, comprehensive frequency adjustment is achieved throughout the grid’s inertia response and PFR processes. An RT-LAB based simulation model of the wind-storage-hydro control system is established and validated using actual case data from Yunnan Power Grid. The results demonstrate: during wet season with 10 % renewable penetration: frequency violation index <em>d</em>₁ improves by 0.078; Frequency violation index <em>d</em>₂ improves by 0.223. During dry season with 55 % renewable penetration: energy storage compensates up to 0.0027p.u. reverse regulation power during initial hydro unit primary frequency response; Frequency violation index <em>d</em>₁ improves by 0.524; Frequency violation index <em>d</em>₂ improves by 0.449. The proposed strategy effectively enhances frequency regulation capability for renewable-hydro dominated power systems under different seasonal conditions.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"172 ","pages":"Article 111104"},"PeriodicalIF":5.0,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing the robustness of cyber–physical power systems: From the perspective of information flow control","authors":"Huibin Jia ,&nbsp;Siqi Wan ,&nbsp;Jiahe Li ,&nbsp;Shaoyan Li ,&nbsp;Weiran Hou ,&nbsp;Longyue Su","doi":"10.1016/j.ijepes.2025.111082","DOIUrl":"10.1016/j.ijepes.2025.111082","url":null,"abstract":"<div><div>In Cyber–Physical Power Systems (CPPSs), the deep coupling of physical and cyber systems can trigger cascading failures, resulting in cross-space fault propagation and an elevated risk of system collapse. This paper explores how controlling the information flow in the cyber layer can enhance the robustness of CPPSs during such cascading failures. First, the Software Defined Networking-enabled CPPS (SDN-enabled CPPS) model, which integrates information flow control, has been established to describe the interdependent relationship between cyber and physical systems concerning power supply, monitoring, and control. Corresponding to the power flow control strategy, an information flow control model was established to maximize the observability recovery of the power grid. Second, based on the inverse-time overload protection of power lines and the latency of information flow control, a timeliness model for information flow control was proposed. Subsequently, a CPPS robustness assessment method, which incorporates information flow control, was presented, with the load loss rate serving as the evaluation metric. Finally, the simulation results for the IEEE-39 and IEEE-118 systems reveal average load loss reductions of 5.20% and 6.28% in single-fault scenarios, and 6.33% and 6.66% in multiple-fault scenarios. This indicates that information flow control effectively mitigates load loss and enhances the robustness of CPPSs.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"172 ","pages":"Article 111082"},"PeriodicalIF":5.0,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementing demand response in the park: leveraging specialized agents for large-scale inverter air conditioners","authors":"Weifeng Liu ,&nbsp;Guangyu He ,&nbsp;Yu Shen ,&nbsp;Zhihua Wang ,&nbsp;Qing Wu ,&nbsp;Yi Zhang","doi":"10.1016/j.ijepes.2025.111130","DOIUrl":"10.1016/j.ijepes.2025.111130","url":null,"abstract":"<div><div>A significant number of decentralized Inverter Air Conditioners (IACs) have been installed within the industrial park, and effectively leveraging the regulation capabilities of these appliances is crucial for park operators in engaging with demand response (DR). However, the operational characteristics, environments, user behaviors, and habits of the numerous IACs within the park vary widely, presenting challenges for operators when guiding their participation in DR. First, a framework has been proposed to enable the large-scale participation of IAC Agents in DR. This framework integrates qualitative guidance with quantitative control, drastically simplifying the complexity of DR implementation while effectively enhancing the robustness of benefits for park operators. Second, a qualitative guidance strategy based on customer directrix load (CDL) has been introduced, with the derived CDL serving as the guiding profile for all IAC Agents. This strategy ensures that, even under the most adverse conditions, it remains possible to aggregate a significant number of decentralized and random IAC Agents at minimal cost, thereby achieving substantial collective impact. Next, drawing on the concepts of embodied general artificial intelligence, IAC Agents have been developed across four dimensions: proactive perception, proactive interaction, proactive action, and proactive evolution. This development allows them to effectively integrate cyber-physical-social attributes during DR periods, striving to align their load shapes with the issued CDL targets. Finally, a simulation of the scenario involving 12,000 IAC Agents participating in DR was conducted using the discrete event simulation framework SimPy to evaluate its collective impact and the performance of the IAC Agents. The results indicate that the proposed method demonstrates significant advantages in terms of economy, reliability, robustness, timeliness, and user satisfaction, and it may serve as a viable technical approach for park operators managing large-scale IAC participation in DR.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"172 ","pages":"Article 111130"},"PeriodicalIF":5.0,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic reconfiguration of distribution network considering typical wind −Solar-Load joint scenarios","authors":"Gaiping Sun ,&nbsp;Geng Chen ,&nbsp;Ronghui Liu ,&nbsp;Shunfu Lin ,&nbsp;Xu Wang","doi":"10.1016/j.ijepes.2025.111121","DOIUrl":"10.1016/j.ijepes.2025.111121","url":null,"abstract":"<div><div>With the increasing integration of high proportions of renewable energy, the network losses and wind-solar accommodation issues in the distribution network have become more prominent, reducing the economic efficiency of distribution network operation. This paper proposes a dynamic reconfiguration strategy for distribution networks based on typical wind-solar-load joint scenarios and optimal time interval partitioning. Firstly, a scenario generation method based on the Information Maximizing Wasserstein Generative Adversarial Network with Gradient Penalty (Info-WGAN-GP) is proposed, which can generate spatiotemporally correlated scenario sets from historical data. Then, a dynamic reconfiguration with Fisher optimal segment method is developed under typical wind −solar-load joint scenarios, aiming to minimize the comprehensive cost, including network loss cost, switching operation cost, and wind-solar curtailment cost. Subsequently, intermediate variables are introduced to transform the distribution network reconfiguration model into a mixed-integer second-order cone programming (MISOCP) problem, which is solved using YALMIP and CPLEX. The simulation results show that the proposed model can effectively reduce network losses, decrease the number of switching operations, and enhance the utilization rate of wind and solar power. The total cost of dynamic reconfiguration in the distribution network can be reduced by up to 32.31%, validating the effectiveness of the model.</div><div>© 2017 Elsevier Inc. All rights reserved.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"172 ","pages":"Article 111121"},"PeriodicalIF":5.0,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Two-stage robust optimization strategy for VPP participation in the energy and reserve markets considering intertemporal carbon trading","authors":"Hadi Nemati,&nbsp;Álvaro Ortega,&nbsp;Pedro Sánchez-Martín","doi":"10.1016/j.ijepes.2025.111093","DOIUrl":"10.1016/j.ijepes.2025.111093","url":null,"abstract":"<div><div>This paper proposes a coordinated strategy for Virtual Power Plants (VPPs), including both renewable and conventional units, to participate in the Day-Ahead Market (DAM) and Secondary Reserve Market (SRM), while incorporating intertemporal Carbon Trading Market (CTM) constraints. The model enables the VPP to leverage differences in CTM prices across multiple sample days by strategically selling excess carbon credits or purchasing required credits on sample days with more favorable prices. A two-stage robust optimization framework is developed to account for multiple uncertainties in market prices, renewable energy production, and demand consumption. The proposed scheduling strategy encourages the VPP to prioritize low-emission resources and limit the use of polluting units, contributing to both profitability and emission reduction. To evaluate the effectiveness of the proposed approach, simulations are conducted for a 220 MW VPP supplying 80 MW of internal demand under various uncertainty-handling strategies and carbon credit allowance levels. The findings show that the proposed model enables more flexible carbon trading, with CTM-related profitability increasing by 29.0–55.3%, and carbon emissions reduction improvement up to 8.9% compared to daily carbon trading.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"172 ","pages":"Article 111093"},"PeriodicalIF":5.0,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}