电力建设2024，Vol.45Issue(7)：134-143,10.DOI:10.12204/j.issn.1000-7229.2024.07.012
多站融合中考虑可靠性及经济性的储能站两阶段优化配置方法
Two-Stage Optimization Configuration Method for Energy Storage Stations Considering Reliability and Economy in Multi-station Fusion
摘要
Abstract
To study a multifunction optimization configuration method for energy storage stations in multi-station integration,the possibility of replacing the traditional diesel generator and UPS with energy storage is discussed.The traditional and energy storage modes were compared using reliability calculations,and the results showed that the reliability of energy storage was higher.Then,the economy of energy storage was analyzed,a life model of energy storage was established,the cost was analyzed,and the type of energy storage was determined by comparing the investment,operation and maintenance,and kilowatt-hour costs of energy storage.Finally,considering the reliability and economy of the storage station in multi-station integration,we configured the energy storage with optimal reliability of the storage station and maximum annual net return value as the objective function.The particle swarm optimization algorithm was used to obtain an optimal allocation of energy storage capacity,with 3 500 and 150 kWh of usable and standby capacity,respectively.The example results show that the two-stage optimization method proposed in this study makes the allocation capacity of energy storage in multi-station fusion more accurate and realistic.关键词
多站融合/储能站/数据中心/可靠性评估/经济性分析/粒子群优化(PSO)Key words
multi-station integration/energy storage stations/data center/reliability assessment/economic analysis/particle swarm optimization(PSO)分类
信息技术与安全科学引用本文复制引用
王彦峰,王春玲,潘柏崇,车伟娴,许成昊,董萍..多站融合中考虑可靠性及经济性的储能站两阶段优化配置方法[J].电力建设,2024,45(7):134-143,10.基金项目
This work is supported by National Natural Science Foundation of China(No.52077083),Guangdong Power Grid Key Technology Project(No.0300002022030103GH00032)and Guangdong Natural Science Foundation Offshore Wind Power Joint Fund(No.2022A1515240076). 国家自然科学基金项目(52077083) （No.52077083）
广东电网重点科技项目(0300002022030103GH00032) （0300002022030103GH00032）
广东省自然科学基金海上风电联合基金(2022A1515240076) （2022A1515240076）
