太阳能Issue(12)：49-56,8.DOI:10.19911/j.1003-0417.tyn20240524.03
基于PSO-KELM-GWO算法的氢-蓄混合储能系统容量优化配置研究
RESEARCH ON CAPACITY OPTIMIZATION CONFIGURATION OF HYDROGEN BATTERY HYBRID ENERGY STORAGE SYSTEM BASED ON PSO-KELM-GWO ALGORITHM
摘要
Abstract
In response to the high costs and poor economic benefits associated with wind and energy storage joint projects,this paper establishes an optimization model for the capacity configuration of a wind-hydrogen-storage hybrid energy system,and studies the system's performance in smoothing the output power fluctuations of wind turbines and tracking system load demands.The research results indicate that,based on the actual needs of the project,establishing a wind-hydrogen-storage hybrid energy storage system with load power shortage rate and energy loss rate as system evaluation indicators,considering the full life cycle cost,using particle swarm optimization kernel extreme learning machine algorithm to predic wind turbine output power as input value,and proposing an improved grey wolf optimization to solve the objective function,can achieve a more optimal solution.Through simulation analysis,the algorithm model proposed in this paper can play a certain reference role in the investment decision-making of new energy projects in terms of hybrid energy storage technology utilization,reduction of wind power curtailment,and improvement of load power supply quality.关键词
氢储能系统/蓄电池/负荷缺电率/能量损失率/灰狼算法Key words
hydrogen energy storage system/battery storage/load power shortage rate/energy loss rate/grey wolf algorithm(GWO)分类
信息技术与安全科学引用本文复制引用
涂菁菁,赵鹏,邹伟东..基于PSO-KELM-GWO算法的氢-蓄混合储能系统容量优化配置研究[J].太阳能,2024,(12):49-56,8.基金项目
国家自然科学基金青年基金资助项目(61906015) （61906015）
