{"title":"A Novel Robust Energy Storage Planning Method for Grids With Wind Power Integration Considering the Impact of Hurricanes","authors":"Huaizhi Yang;Cong Zhang;Jiayong Li;Lipeng Zhu;Ke Zhou","doi":"10.1109/TSTE.2025.3527448","DOIUrl":null,"url":null,"abstract":"This paper proposes a novel energy storage system (ESS) planning method for improving ESS emergency capability during hurricanes, as well as enhancing the integration of renewable power generation under normal weather simultaneously. First, a novel robust ESS planning (NREP) model is proposed that considers the uncertainties of wind power and transmission line faults, along with their correlation during hurricanes, thereby reducing load shedding losses and wind curtailment. Secondly, to improve both the modeling accuracy of line fault uncertainties and the solution efficiency, a spatio-temporal uncertainty set related to hurricane intensity is constructed through information fusion. Furthermore, an improved column-and-constraint generation (ICCG) algorithm, incorporating nonanticipativity constraints, is proposed to solve the NREP model. The ICCG is able to interrelate scenarios and identify generation-dependent worst-case scenarios, thereby improving the feasibility of multi-period generation decisions under nonanticipative uncertainty realization while reducing losses from wind curtailment and load shedding across all scenarios. Simulation results, obtained by comparisons to previous models and algorithms, validate the effectiveness and superiority of the proposed method.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"16 2","pages":"1388-1400"},"PeriodicalIF":8.6000,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Sustainable Energy","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10844010/","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
This paper proposes a novel energy storage system (ESS) planning method for improving ESS emergency capability during hurricanes, as well as enhancing the integration of renewable power generation under normal weather simultaneously. First, a novel robust ESS planning (NREP) model is proposed that considers the uncertainties of wind power and transmission line faults, along with their correlation during hurricanes, thereby reducing load shedding losses and wind curtailment. Secondly, to improve both the modeling accuracy of line fault uncertainties and the solution efficiency, a spatio-temporal uncertainty set related to hurricane intensity is constructed through information fusion. Furthermore, an improved column-and-constraint generation (ICCG) algorithm, incorporating nonanticipativity constraints, is proposed to solve the NREP model. The ICCG is able to interrelate scenarios and identify generation-dependent worst-case scenarios, thereby improving the feasibility of multi-period generation decisions under nonanticipative uncertainty realization while reducing losses from wind curtailment and load shedding across all scenarios. Simulation results, obtained by comparisons to previous models and algorithms, validate the effectiveness and superiority of the proposed method.
期刊介绍:
The IEEE Transactions on Sustainable Energy serves as a pivotal platform for sharing groundbreaking research findings on sustainable energy systems, with a focus on their seamless integration into power transmission and/or distribution grids. The journal showcases original research spanning the design, implementation, grid-integration, and control of sustainable energy technologies and systems. Additionally, the Transactions warmly welcomes manuscripts addressing the design, implementation, and evaluation of power systems influenced by sustainable energy systems and devices.