基于IPMOCSA的光伏微网混合储能容量优化配置  

Optimal Configuration of Optical Storage Micro-grid Hybrid Energy Storage Capacity Based on IPMOCSA

作　　者：王红艳[1] 王依妍 陈景文[2] 肖妍 莫瑞瑞 WANG Hongyan;WANG Yiyan;CHEN Jingwen;XIAO Yan;MO Ruirui(Information and Network Management Center,Shaanxi University of Science and Technology,Xi’an 710021;College of Electrical and Control Engineering,Shaanxi University of Science and Technology,Xi’an 710021)

机构地区：[1]陕西科技大学信息与网管中心,西安710021 [2]陕西科技大学电气与控制工程学院,西安710021

出　　处：《电气工程学报》2021年第3期152-160,共9页Journal of Electrical Engineering

基　　金：陕西省自然科学基础研究计划资助项目(2020JM-511)。

摘　　要：针对光伏微网中混合储能的容量优化配置问题,以经济性为目标考虑微电网和大电网的交互功率成本建立系统经济优化模型,并提出一种改进的多目标乌鸦算法进行求解,获得优化配置结果。考虑分时电价设计微电网的系统运行策略,建立系统的运行成本模型,在此基础上建立不同类型储能介质的投资模型。利用以经济最优为目标,获得不同类型储能介质的容量优化配置占比,并对比多目标粒子群算法进行算例验证。结果表明提出的IPMOCSA求解精确度更高、收敛速度更快,混合储能配置成本节省了5.13%,配置方法对实际应用有一定参考性。Aiming at the capacity optimization allocation problem of hybrid energy storage in photovoltaic micro-grid,the system economic optimization model was established by taking the interactive power cost of micro-grid and large grid as the objective,and an improved multi-objective crow search algorithm is proposed to solve the problem and obtain the optimal allocation results.Considering the time-of-use electricity price to design the system operation strategy of the micro-grid,establish the operating cost model of the system,and build the investment model of different types of energy-storing media.Using improved multi-objective crow search algorithm as the goal of economic optimization,the optimal allocation ratio of different types of energy storage media is obtained,and the multi-objective particle swarm optimization is used to verify the examples.The results show that the proposed improved multi-objective crow search algorithm solution has higher accuracy and convergence speed.The cost of hybrid energy storage configuration is saved by 5.13%,and the configuration method has certain reference for practical applications.

关 键 词：微电网 混合储能 容量配置 乌鸦算法 

分 类 号：TM615[电气工程—电力系统及自动化]