基于ISSA的光储微网混合储能容量优化配置

ISSA-based Optimal Configuration of Optical Storage MicrogridHybrid Energy Storage Capacity

近年来,新能源的大力发展促使分布式能源结合本地负荷的微网结构应运而生,针对光储微网混合储能容量优化配置的问题,提出一种改进的麻雀搜索算法(ISSA)对以经济性为目标建立的储能容量配置模型进行求解。首先,利用分时电价策略优化混合储能系统充放电功率,建立以储能系统年综合成本最小为目标的容量优化配置模型;其次,针对传统麻雀搜索算法求解精度低、收敛速度慢、易陷入局部最优等问题,采用精英反向学习初始化种群,并结合粒子群算法改进麻雀位置更新公式,同时引入莱维飞行策略扩大算法搜索范围。最后,通过算例分析验证了所提策略的合理性和有效性。

In recent years,the rapid development of new energy has led to the emergence of microgrid structure of distributed energy combined with local load.Aiming at the optimal configuration of hybrid energy storage capacity in optical storage microgrids,an improved sparrow search algorithm(ISSA)is proposed to solve the energy storage capacity allocation model established with the goal of economy.Firstly,the charging and discharging power of hybrid energy storage system is optimized by using the time-of-use electricity price strategy,and the capacity optimal allocation model is established with the objective of minimizing the annual comprehensive cost of energy storage system;Secondly,aiming at the problems of traditional sparrow search algorithm,such as low accuracy,slow convergence speed and easy to fall into local optimum,the elite reverse learning is used to initialize the population,and the particle swarm optimization algorithm is combined to improve the sparrow position update formula,while introducing Levy flight strategy to expand the algorithm search range.Finally,the rationality and effectiveness of the proposed strategy are verified through specific example analysis.