International Journal of Electrical Power & Energy Systems最新文献_第8页

Capacity allocation method for a hybrid energy storage system participating in secondary frequency regulation based on variational mode decomposition 基于变分模态分解的二次调频混合储能系统容量分配方法

IF 5 2区工程技术

International Journal of Electrical Power & Energy Systems Pub Date : 2025-03-29 DOI: 10.1016/j.ijepes.2025.110631

Taiying Zheng , Minghao Ye , Qinghua Wu

{"title":"Capacity allocation method for a hybrid energy storage system participating in secondary frequency regulation based on variational mode decomposition","authors":"Taiying Zheng , Minghao Ye , Qinghua Wu","doi":"10.1016/j.ijepes.2025.110631","DOIUrl":"10.1016/j.ijepes.2025.110631","url":null,"abstract":"<div><div>Hybrid Energy Storage Systems (HESSs) are extensively employed to address issues related to frequency fluctuations. This paper introduces a method for configuring the capacity of a HESS engaged in the secondary frequency regulation, utilizing Variable Mode Decomposition (VMD). An economic model for a HESS, considering lifecycle costs and frequency regulation benefits, is constructed to maximize net income. The preliminary determination of the HESS allocation is based on optimizing parameters through VMD. The frequency regulation capacity and final power allocation are established by comprehensively considering the energy storage’s state of charge and rated power. Under the requirements and operational constraints, the optimal capacity configuration for the HESS is achieved. To verify the proposed method, various factors, such as different power allocation methods, modal decomposition methods, and allocation coefficients, are considered. The results indicate that the proposed method can achieve profits even under adverse conditions in the single-day scenario. The comparison with different modal decomposition methods validates the outstanding advantages of VMD and the importance of selecting appropriate allocation coefficients. Finally, in the multi-day scenario, the recommended capacity of HESS and threshold allocation frequencies for a specific region are determined, enhancing the economic efficiency of HESS for secondary frequency regulation.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":"Article 110631"},"PeriodicalIF":5.0,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143735191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A cloud-edge collaborative optimization control strategy for voltage in distribution networks with PV stations 具有光伏电站的配电网电压云边缘协同优化控制策略

IF 5 2区工程技术

International Journal of Electrical Power & Energy Systems Pub Date : 2025-03-29 DOI: 10.1016/j.ijepes.2025.110632

Guoqing Li , Wei Wang , Dan Pang , Zhipeng Wang , Weixian Tan , Zhenhao Wang , Jinming Ge

{"title":"A cloud-edge collaborative optimization control strategy for voltage in distribution networks with PV stations","authors":"Guoqing Li , Wei Wang , Dan Pang , Zhipeng Wang , Weixian Tan , Zhenhao Wang , Jinming Ge","doi":"10.1016/j.ijepes.2025.110632","DOIUrl":"10.1016/j.ijepes.2025.110632","url":null,"abstract":"<div><div>With the continuous expansion of the power system scale and the continuous development of the power network, the traditional power system management and optimization methods face many challenges. In order to meet the requirements of voltage optimization and adjustment, the optimization problem is divided into cloud front precomputation and edge computing device cooperative optimization computation with the framework of cloud-edge cooperation. The cloud front-end precomputation uses an improved reactive-voltage sensitivity based on an improved modularity function to partition the power system on a 15 min basis and stores the results in the cloud data memory. The voltage threshold device detects the node voltage overrun and triggers the collaborative optimization computation of the edge computing devices, which sends a command to the cloud to call the partitioning result of this time period, and the cloud sends the result to each edge computing device, which determines the area it is responsible for, and adjusts the voltage overrun partitioning by using the mixed-integer second-order conic planning, and ultimately realizes the optimization strategy within the minute-level zone. Since the voltage adjustment is a fine-grained optimization of the local area, it is highly flexible and targeted. Moreover, using the cloud-edge collaboration technology, the intelligent management and optimization of the power system is finally realized. Case analysis and comparative verification show that the method proposed in this paper is accurate and highly efficient.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":"Article 110632"},"PeriodicalIF":5.0,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143735137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Explainable modeling for wind power forecasting: A Glass-Box model with high accuracy 风电预测的可解释模型：高精度玻璃盒模型

IF 5 2区工程技术

International Journal of Electrical Power & Energy Systems Pub Date : 2025-03-29 DOI: 10.1016/j.ijepes.2025.110643

Wenlong Liao , Jiannong Fang , Birgitte Bak-Jensen , Guangchun Ruan , Zhe Yang , Fernando Porté-Agel

{"title":"Explainable modeling for wind power forecasting: A Glass-Box model with high accuracy","authors":"Wenlong Liao , Jiannong Fang , Birgitte Bak-Jensen , Guangchun Ruan , Zhe Yang , Fernando Porté-Agel","doi":"10.1016/j.ijepes.2025.110643","DOIUrl":"10.1016/j.ijepes.2025.110643","url":null,"abstract":"<div><div>Machine learning models (e.g., neural networks) achieve high accuracy in wind power forecasting, but they are usually regarded as black boxes that lack interpretability. To address this issue, the paper proposes a glass-box model that combines high accuracy with transparency for wind power forecasting. Specifically, the core is to sum up the feature effects by constructing shape functions, which effectively map the intricate non-linear relationships between wind power output and input features. Furthermore, the forecasting model is enriched by incorporating interaction terms that adeptly capture interdependencies and synergies among the input features. The additive nature of the proposed glass-box model ensures its interpretability. Simulation results show that the proposed glass-box model effectively interprets the results of wind power forecasting from both global and instance perspectives. Besides, it outperforms most benchmark models and exhibits comparable performance to the best-performing neural networks. This dual strength of transparency and high accuracy positions the proposed glass-box model as a compelling choice for reliable wind power forecasting.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":"Article 110643"},"PeriodicalIF":5.0,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143735138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A source-load collaborative stochastic optimization method considering the electricity price uncertainty and industrial load peak regulation compensation benefit 考虑电价不确定性和工业负荷调峰补偿效益的源荷协同随机优化方法

IF 5 2区工程技术

International Journal of Electrical Power & Energy Systems Pub Date : 2025-03-28 DOI: 10.1016/j.ijepes.2025.110630

Xiaoyu Yue , Lijun Fu , Siyang Liao , Jian Xu , Deping Ke , Huiji Wang , Shuaishuai Feng , Jiaquan Yang , Xuehao He

{"title":"A source-load collaborative stochastic optimization method considering the electricity price uncertainty and industrial load peak regulation compensation benefit","authors":"Xiaoyu Yue , Lijun Fu , Siyang Liao , Jian Xu , Deping Ke , Huiji Wang , Shuaishuai Feng , Jiaquan Yang , Xuehao He","doi":"10.1016/j.ijepes.2025.110630","DOIUrl":"10.1016/j.ijepes.2025.110630","url":null,"abstract":"<div><div>Energy-intensive industrial load offers substantial capacity and rapid adjustment capabilities, which can be effectively coordinated with deep peak regulation (DPR) methods of thermal power to optimize the peak regulation state of the system. The uncertainty of electricity prices and the current peak regulation compensation mechanism significantly affect the economic viability of industrial load regulation. In this study, electrolytic aluminum load (EAL) is used as a representative industrial load. This paper combines the complete ensemble empirical mode decomposition adaptive noise (CEEMDAN), whale optimization algorithm (WOA), and long short-term memory network (LSTM) to propose a CEEMDAN-WOA-LSTM prediction model for electricity price scenarios. Subsequently, comprehensive cost and fine adjustment models for electrolytic aluminum load (EAL) are developed, incorporating the current peak regulation compensation mechanism. Finally, a source-load collaborative stochastic optimization method is proposed, integrating the scenario method and chance constraints. The effectiveness of the proposed scheme is verified using a real regional system, demonstrating significant reductions in total social peak regulation costs, a substantial decrease in renewable energy (RE) abandonment rates, reduced frequency of thermal power DPR, and improved economic efficiency of thermal power. Additionally, the current peak regulation compensation mechanism effectively guarantees the benefits of EAL and encourages its adjustment willingness.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":"Article 110630"},"PeriodicalIF":5.0,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143724973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Terminal sliding mode control with sensor reduction of a permanent magnet synchronous generator supplying a pumping system with battery storage 永磁同步发电机的终端滑模控制与传感器缩减供电的抽水系统与电池存储

IF 5 2区工程技术

International Journal of Electrical Power & Energy Systems Pub Date : 2025-03-28 DOI: 10.1016/j.ijepes.2025.110609

Clotaire Thierry Sanjong Dagang , Mathieu Jean Pierre Pesdjock , Godpromesse Kenné

{"title":"Terminal sliding mode control with sensor reduction of a permanent magnet synchronous generator supplying a pumping system with battery storage","authors":"Clotaire Thierry Sanjong Dagang , Mathieu Jean Pierre Pesdjock , Godpromesse Kenné","doi":"10.1016/j.ijepes.2025.110609","DOIUrl":"10.1016/j.ijepes.2025.110609","url":null,"abstract":"<div><div>This work is concerned with the study and development of a terminal sliding mode control process that employs an estimator of the wind speed and the mechanical rotation speed of the permanent magnet synchronous generator (PMSG). This results in a reduction in the overall cost of the wind power system, which comprises a PMSG, a Pulse Width Modulation (PWM) rectifier, a battery, a DC–DC converter, a PWM inverter and a centrifugal pump driven by an asynchronous squirrel-cage machine. The wind power system is validated in the MATLAB Simulink numerical simulation environment. Subsequently, the results obtained are compared with those of a conventional sliding-mode control (with a tachometric sensor and an anemometric sensor) in order to ascertain the efficacy of the proposed control method in terms of trajectory tracking, energy consumption and the reliability of the proposed estimation algorithm. The simulation results demonstrate that the proposed approach is both robust and reliable. However, it should be noted that the settling time of the estimated quantities is greater than that of the same quantities when measured with the compared approach (conventional sliding mode control).</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":"Article 110609"},"PeriodicalIF":5.0,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143714628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Efficient optimal power flow learning: A deep reinforcement learning with physics-driven critic model 高效最优潮流学习：物理驱动的深度强化学习模型

IF 5 2区工程技术

International Journal of Electrical Power & Energy Systems Pub Date : 2025-03-27 DOI: 10.1016/j.ijepes.2025.110621

Ahmed Sayed , Khaled Al Jaafari , Xian Zhang , Hatem Zeineldin , Ahmed Al-Durra , Guibin Wang , Ehab Elsaadany

{"title":"Efficient optimal power flow learning: A deep reinforcement learning with physics-driven critic model","authors":"Ahmed Sayed , Khaled Al Jaafari , Xian Zhang , Hatem Zeineldin , Ahmed Al-Durra , Guibin Wang , Ehab Elsaadany","doi":"10.1016/j.ijepes.2025.110621","DOIUrl":"10.1016/j.ijepes.2025.110621","url":null,"abstract":"<div><div>The transition to decarbonized energy systems presents significant operational challenges due to increased uncertainties and complex dynamics. Deep reinforcement learning (DRL) has emerged as a powerful tool for optimizing power system operations. However, most existing DRL approaches rely on approximated data-driven critic networks, requiring numerous risky interactions to explore the environment and often facing estimation errors. To address these limitations, this paper proposes an efficient DRL algorithm with a physics-driven critic model, namely a differentiable holomorphic embedding load flow model (D-HELM). This approach enables accurate policy gradient computation through a differentiable loss function based on system states of realized uncertainties, simplifying both the replay buffer and the learning process. By leveraging continuation power flow principles, D-HELM ensures operable, feasible solutions while accelerating gradient steps through simple matrix operations. Simulation results across various test systems demonstrate the computational superiority of the proposed approach, outperforming state-of-the-art DRL algorithms during training and model-based solvers in online operations. This work represents a potential breakthrough in real-time energy system operations, with extensions to security-constrained decision-making, voltage control, unit commitment, and multi-energy systems.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":"Article 110621"},"PeriodicalIF":5.0,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143706241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Distributed transmission-distribution coordinated voltage control: A bidirectional Anderson acceleration based master slave splitting approach 分布式输电-配电协调电压控制：一种基于双向安德森加速的主从分离方法

IF 5 2区工程技术

International Journal of Electrical Power & Energy Systems Pub Date : 2025-03-26 DOI: 10.1016/j.ijepes.2025.110625

Zhenming Lu , Zhongkai Yi , Ying Xu , Zhenghong Tu , Zhimin Li , Junfei Wu

{"title":"Distributed transmission-distribution coordinated voltage control: A bidirectional Anderson acceleration based master slave splitting approach","authors":"Zhenming Lu , Zhongkai Yi , Ying Xu , Zhenghong Tu , Zhimin Li , Junfei Wu","doi":"10.1016/j.ijepes.2025.110625","DOIUrl":"10.1016/j.ijepes.2025.110625","url":null,"abstract":"<div><div>As the penetration of renewable energy increases, the voltages in power systems frequently change and fluctuate significantly. A tractable coordinated voltage control model for transmission and distribution systems is formulated to make efficient control decisions and realize distributed transmission-distribution coordinated voltage control, which avoids nonlinear and non-convex terms. Subsequently, using the data-driven bidirectional Anderson acceleration method, this study proposes an improved generalized master–slave-splitting method (G-MSSM), which is employed to solve the proposed coordinated voltage control model. Finally, the convergence index is introduced and derived with a rigid mathematical proof that can quantitatively evaluate the convergence efficiency of the proposed G-MSSM. Numerical simulations illustrate the effectiveness and scalability of the proposed approach in multiple scenarios with high-penetration renewable energy. The proposed approach achieves higher computational efficiency and better convergence performance than several representative approaches in the state-of-the-art literature.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":"Article 110625"},"PeriodicalIF":5.0,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143706240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on modeling and simulation of traction power supply system of guideway rubber-tires train 导轨橡胶轮胎列车牵引供电系统建模与仿真研究

IF 5 2区工程技术

International Journal of Electrical Power & Energy Systems Pub Date : 2025-03-25 DOI: 10.1016/j.ijepes.2025.110555

Haida Xu , Liwei Zhang , Jiapeng Wang , Xu Wang

{"title":"Research on modeling and simulation of traction power supply system of guideway rubber-tires train","authors":"Haida Xu , Liwei Zhang , Jiapeng Wang , Xu Wang","doi":"10.1016/j.ijepes.2025.110555","DOIUrl":"10.1016/j.ijepes.2025.110555","url":null,"abstract":"<div><div>Guideway rubber-tires system, also known as Rapid rubber-tires trail (RRT), is a new type of urban rail transit. The train uses rubber tires as running wheels and uses guide rails to achieve steering. The guideway rubber-tires train generally adopts the power supply mode of on-board energy storage and can operate in an unmanned way. Through the simulation research of traction power supply system of guideway rubber-tires train, it can provide important support data for system planning and design, economic benefit evaluation and safety performance monitoring. In this paper, the component model of traction power supply system of guideway rubber-tires train is established. According to the dynamic multi-train condition, the execution flow of AC-DC power flow calculation is proposed, the load simulation of traction power supply system is realized, and the calculation results are analyzed. On the basis of normal condition simulation, fault condition simulation is carried out. The simulation results mainly include the performance of key components in the traction power supply system, the simulation of the fault charging curve of the vehicle overcapacity, and the verification of the redundancy performance of the line. The results show that the simulation system can simulate the normal and fault conditions of the traction power supply system well, and the simulation results show that the traction power supply system of the line meets the design requirements.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":"Article 110555"},"PeriodicalIF":5.0,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143687049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimized multi-unit coordinated scheduling based on improved IGDT: Low-carbon scheduling research for the electric-heat-oxygen integrated energy system 基于改进IGDT的多机组协同调度优化：电-热-氧一体化能源系统低碳调度研究

IF 5 2区工程技术

International Journal of Electrical Power & Energy Systems Pub Date : 2025-03-25 DOI: 10.1016/j.ijepes.2025.110629

Zhe Yin , Zhifan Zhang , Ruijin Zhu , Yifan Zhang , Jiyuan Wang , Wenxing Tang

{"title":"Optimized multi-unit coordinated scheduling based on improved IGDT: Low-carbon scheduling research for the electric-heat-oxygen integrated energy system","authors":"Zhe Yin , Zhifan Zhang , Ruijin Zhu , Yifan Zhang , Jiyuan Wang , Wenxing Tang","doi":"10.1016/j.ijepes.2025.110629","DOIUrl":"10.1016/j.ijepes.2025.110629","url":null,"abstract":"<div><div>To address the oxygen supply demands and the challenges posed by high penetration of renewable energy in high-altitude regions, this paper proposes a low-carbon scheduling model for an electric-heat-oxygen integrated energy system (EHO-IES), designed for energy dispatch and management in these areas. The model integrates carbon capture and storage with power-to-gas (CCS-P2G), concentrated solar power plant (CSPP), combined heat and power (CHP) unit, and ground-source heat pump (GSHP). By optimizing the coordinated operation of multiple energy sources, the model enhances their complementarity and interaction. To effectively manage the multiple uncertainties in renewable energy and load, this study introduces an improved information-gap decision theory (IGDT) model, referred to as EWNS-IGDT. This model combines the entropy weight method (EWM) and non-dominated sorting genetic algorithm II (NSGA-II), improving the objectivity and rationality of uncertainty weight settings in risk-averse strategy (RAS) and risk-seeking strategy (RSS). The paper further analyzes the impact of these strategies on low-carbon scheduling. Case study results show that the coordinated operation of multiple units significantly reduces total cost (by 89.93 %) and carbon trading cost (by 97.95 %), while achieving near-complete integration of photovoltaic (PV) and wind turbine (WT) output. Under the RAS, total cost increased by 20 %, and carbon trading cost rose by 90.06 %. In contrast, under the RSS, total cost decreased by 19.98 %, while carbon trading cost significantly dropped by 321.90 %.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":"Article 110629"},"PeriodicalIF":5.0,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143687050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing resilience of distribution system under extreme weather: Two-stage energy storage system configuration strategy based on robust optimization 增强极端天气下配电系统的恢复能力：基于稳健优化的两阶段储能系统配置策略

IF 5 2区工程技术

International Journal of Electrical Power & Energy Systems Pub Date : 2025-03-25 DOI: 10.1016/j.ijepes.2025.110624

Ye He , Hongyun Fu , Andrew Y. Wu , Hongbin Wu , Ming Ding

{"title":"Enhancing resilience of distribution system under extreme weather: Two-stage energy storage system configuration strategy based on robust optimization","authors":"Ye He , Hongyun Fu , Andrew Y. Wu , Hongbin Wu , Ming Ding","doi":"10.1016/j.ijepes.2025.110624","DOIUrl":"10.1016/j.ijepes.2025.110624","url":null,"abstract":"<div><div>Extreme natural disasters can easily cause large-scale power outages in distribution networks (DN), and energy storage system (ESS) contributes to an essential part of integrated solutions to this problem owing to its flexible regulation and rapid response characteristics. A two-stage robust optimization model for ESS that considers the resilience enhancement of a DN under extreme weather conditions is proposed. First, the impacts of secondary hazards on the component failure rates were quantified, and a time-varying matrix of distribution line failures was constructed. Second, an overall recovery index of the DN and an important load recovery index were proposed. Finally, a two-stage robust optimization model for the ESS is established to improve DN resilience with the objective of minimizing the comprehensive economic cost of the ESS and the annual comprehensive weighted load loss, which is solved using the column-and-constraint generation algorithm (C&CG). Furthermore, numerous simulations were performed on the IEEE 33-node system, and it showed that the proposed method can not only ensure the optimal comprehensive economics of the ESS and fully tap the support potential of the ESS, but also maximize the resilience of the DN. Compared to the DN without energy storage system, the proposed method improves the overall resilience and important load recovery of the DN by about 15.9% and 4.3%, respectively.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"167 ","pages":""},"PeriodicalIF":5.0,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143687051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0