基于改进萤火虫算法的考虑风光概率分布储能容量优化配置

Optimal Allocation of Energy Storage Capacity Based on Improved Firefly Algorithm Considering Wind and Solar Probability Distribution

针对风光储系统中,现有的储能容量优化配置方案无法兼顾分布式电源的发电概率问题,提出一种基于风光概率分布的储能容量优化配置方法。首先建立风电场和光伏电场出力特性数学模型,得出其概率分布曲线;其次研究了储能充放电特性及建设成本;搭建储能容量优化配置模型,并提出一种快速求全局解的改进萤火虫算法。最后结合某地区风光储系统进行算例分析,得到储能装置容量最优配置方案。结果表明:通过该储能容量优化配置方法可以得到不同风光配比下储能容量配置,进一步得到最优容量配置方案;提出的改进萤火虫算法,提高了全局和局部搜索的能力,能够快速求解得到最优储能容量。

In view of the fact that the existing optimal configuration of energy storage capacity in the wind and solar storage system can not take into account the generation probability of distributed power sources,a method for optimal configuration of energy storage capacity based on the probability distribution of wind and solar was proposed.The whole idea was as follows:firstly,establish a mathematical model of the output characteristics of wind farms and photovoltaic fields,and obtain their probability distribution curves;secondly,study the charging and discharging characteristics of energy storage and construction costs;set up an optimal configuration model of energy storage capacity,and propose an improved firefly to quickly find a global solution algorithm.Finally,a case study was carried out in combination with a wind and solar storage system in a certain area,and the optimal configuration scheme of energy storage device capacity is obtained.The experimental results show that the energy storage capacity allocation method can obtain the energy storage capacity allocation under different wind and solar ratios,and further obtain the optimal capacity allocation plan;the improved firefly algorithm proposed improves the global and local search capabilities and can quickly solve the optimal energy storage capacity.