Jingjing Wang, L. Yao, Jun Wang, S. Liao, Jian Xu, B. Mao, Boyu Xie
{"title":"Bi-level Optimization Model for Coordinated Operation of Wind Power and Energy Storage System","authors":"Jingjing Wang, L. Yao, Jun Wang, S. Liao, Jian Xu, B. Mao, Boyu Xie","doi":"10.1109/ICoPESA56898.2023.10141332","DOIUrl":null,"url":null,"abstract":"The need for energy transition from fossil energy to clean energy has resulted in the rapid development of renewable energies, such as wind and solar power. However, the increasing penetration of renewable energies in power grids has imposed new challenges on energy balance management and control, etc, of the power grid due to the intermittence and fluctuation of renewable energies. The use of energy storage has been considered an effective way to mitigate the impact of renewable energy on power grids, however, the coordinated operation method between energy storage and renewable energies in power grids is required, in order to increase the dispatch ability of renewable energies and improve renewable energy consumption capacity of power grids. Aiming to investigate optimal coordinated operation methods between wind power and energy storage, this paper proposes a bi-level optimization model to realize the coordinated operation of wind power and energy storage system. The grid optimization layer optimizes the day-ahead schedule of the wind power, and the scheduled result is transmitted to the energy storage system optimization layer, which optimizes the output power and capacity of the energy storage system by designing the charging and discharging strategy. Simulation results show that the proposed bi-level optimization model can reduce the wind curtailment penalty caused by network congestion and insufficient regulation ability, thus reducing the operation cost.","PeriodicalId":127339,"journal":{"name":"2023 International Conference on Power Energy Systems and Applications (ICoPESA)","volume":"19 22","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Power Energy Systems and Applications (ICoPESA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICoPESA56898.2023.10141332","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The need for energy transition from fossil energy to clean energy has resulted in the rapid development of renewable energies, such as wind and solar power. However, the increasing penetration of renewable energies in power grids has imposed new challenges on energy balance management and control, etc, of the power grid due to the intermittence and fluctuation of renewable energies. The use of energy storage has been considered an effective way to mitigate the impact of renewable energy on power grids, however, the coordinated operation method between energy storage and renewable energies in power grids is required, in order to increase the dispatch ability of renewable energies and improve renewable energy consumption capacity of power grids. Aiming to investigate optimal coordinated operation methods between wind power and energy storage, this paper proposes a bi-level optimization model to realize the coordinated operation of wind power and energy storage system. The grid optimization layer optimizes the day-ahead schedule of the wind power, and the scheduled result is transmitted to the energy storage system optimization layer, which optimizes the output power and capacity of the energy storage system by designing the charging and discharging strategy. Simulation results show that the proposed bi-level optimization model can reduce the wind curtailment penalty caused by network congestion and insufficient regulation ability, thus reducing the operation cost.