基于改进粒子群算法的混合储能系统容量优化

Capacity optimization of hybrid energy storage based on improved PSO algorithm

为了调高风光互补发电储能系统的经济性,减少其运行费用,研究风光互补发电储能系统的容量优化配置模型,探讨粒子群算法的改进及混合储能容量优化方法。首先通过对全生命周期费用静态模型的介绍,利用蓄电池和超级电容器作为风光互补系统混合储能装置,以其全生命周期费用最小为目标,以系统的缺电率等运行指标为约束条件,建立了一种混合储能系统容量优化配置模型,其次,通过优化不对称加速因子进而改进了粒子群算法,最后利用算例在Matlab中进行了仿真与求解,结果表明,该方法不仅优化了蓄电池的工作状态,降低了储能系统的全生命周期费用,而且加快了收敛速度。

In order to increase the economy of wind-solar generation storage system and reduce its operation cost, we study its capacity optimal allocation model, and presented a hybrid energy storage capacity optimization method by im- proving PSO algorithm. A hybrid energy storage capacity optimization model has been constructed, which considers battery and super capacitor as a hybrid energy storage device, considers the lowest annual life cycle cost of hybrid en- ergy storing device as the optimization objective, and considers the indices such as the loss of power supply probability as constrain conditions. Then we optimize the asymmetric acceleration coefficient, thereby improving PSO algorithm, and simulate the case using Matlab. The simulation result shows that the method not only can optimize the work condi- tion of the battery, reduce the cost of the energy storage system and the life cycle cost, but also can improve the con- vergence speed.