摘要
根据蓄电池数学模型和充放电特点,综合考虑蓄电池投资成本和风电场弃风率,建立了由蓄电池投资成本和风电场弃风率组成综合成本为目标函数的风电场储能容量优化配置模型,并给出了模型的约束条件。采用惯性权系数调整、越界粒子变异操作和粒子初始化规则调整等策略对粒子群-差分融合算法(Particle Swarm Optimization-Differential Evolution,PSO-DE)算法进行改进,得到改进PSO-DE融合算法,对风电场储能容量优化配置模型进行求解。结果表明,改进PSO-DE融合算法只需要48次迭代就找到了综合成本最小值为624.18万元,对应的最优储能容量为11.25 MWh,风电场弃风率为0.15%,验证了所提出的风电场最优储能容量计算方法的实用性。
According to the mathematical model as well as the characteristics of charge and discharge of battery,and considering the investment cost of battery and the abandonment rate of wind farm,an optimal allocation model of wind farm energy storage capacity with the objective function of comprehensive cost composed of battery investment cost and wind farm abandonment rate was established,and the constraints of the model were given.The PSO-DE algorithm was improved by using the strategies of inertia weight coefficient adjustment,cross-border particle mutation operation and particle initialization rule adjustment to solve the optimal allocation model of wind farm energy storage capacity.The results show that the improved PSO-DE fusion algorithm only needs 48 iterations to find the optimal value.The minimum comprehensive cost is 6.2418 million yuan,the corresponding optimal energy storage capacity is 11.25 MWh,and the wind abandonment rate of the wind farm is 0.15%.The practicability of the calculation method of the optimal energy storage capacity for wind farm are verified.
作者
陈涛
邢金晶
刘闯
卢银均
李俊
陈海旭
CHEN Tao;XING Jinjing;LIU Chuang;LU Yinjun;LI Jun;CHEN Haixu(State Grid Jingmen Power Supply Company,Jingmen 448000,China;College of Electrical and New Energy,Three Gorges University,Yichang 443002,China;State Grid Fuzhou Power Supply Company,Fuzhou 350000,China)
出处
《山东电力技术》
2023年第1期8-13,共6页
Shandong Electric Power
基金
国家自然科学基金项目(51907104)
国家电网公司科技项目“面向能源转型的县域能源互联网规划设计关键技术研究”(5211HZ21004H)。
关键词
风电场
储能容量
优化配置
粒子群
差分进化
wind farm
energy storage capacity
optimizing configuration
particle swarm
differential evolution
作者简介
陈涛(1979),男,工程师,从事电力安全监督管理、电力应急管理、电力设施保护管理等工作。
