基于学习因子异步变化CPSO混合储能容量优化配置  

Optimal allocation of CPSO hybrid energy storage capacitybase on asynchronous change of learning factor

作　　者：马丙泰 刘海涛[1,2] 张匡翼 陆恒 MA Bingtai;ZHANG Kuangyi;LU Heng(Nanjing Institute of Engineering School of Electrical Engineering,Nanjing 211167,China)

机构地区：[1]南京工程学院电力工程学院,南京211167 [2]江苏省配电网智能技术与装备协同创新中心,南京211167

出　　处：《自动化与仪器仪表》2022年第7期125-130,共6页Automation & Instrumentation

基　　金：国家自然科学基金(51777197)。

摘　　要：为提升新能源发电储能系统的经济性,对风光互补发电混合储能系统(HESS)的容量配置模型进行研究,分析混沌粒子群算法(CPSO)及混合储能容量优化方法。首先,确立以HESS全生命周期费用为目标函数,负荷缺电率等为约束条件,构建HESS容量优化配置模型;其次,将混沌映射理论引入粒子群算法并应用于混合储能容量优化配置,相比于传统粒子群算法(PSO),CPSO体现了全局寻优的优越性;同时,在CPSO中提出学习因子随惯性权重异步变化的方法,使寻优过程中获得的最优解浮动范围减小;最后,利用算例进行仿真分析,结果表明,该方法不仅降低了混合储能系统的全生命周期费用,稳定了收敛速度;而且缩减了最优值寻优浮动范围,增强寻优稳定性。In order to improve the economy of new energy generation and energy storage system,the capacity allocation model of hybrid energy storage system(HESS) for wind-solar hybrid power generation is studied,and the chaotic particle swarm optimization(CPSO) and hybrid energy storage capacity optimization method are analyzed.Firstly,the HESS capacity optimal allocation model is established with the HESS life cycle cost as the objective function and the load power shortage rate as the constraint.Secondly,chaos mapping theory is introduced into particle swarm optimization and applied to the optimal allocation of hybrid energy storage capacity.Compared with traditional particle swarm optimization(PSO),CPSO shows the superiority of global optimization.At the same time,a method of asynchronous change of learning factor with inertia weight is proposed in CPSO,which reduces the floating range of the optimal solution obtained in the optimization process.Finally,an example is used for simulation analysis,and the results show that this method not only reduces the life cycle cost of hybrid energy storage system,but also stabilizes the convergence speed,reduce the floating range of optimal value optimization and enhance the stability of optimization.

关 键 词：容量优化配置 CPSO 学习因子异步变化 

分 类 号：TP29[自动化与计算机技术—检测技术与自动化装置]