基于改进布谷鸟算法的风光储联合供电系统储能容量优化配置研究

Research on Capacity Optimization of Hybrid Energy Storage System in Wind-PV-Storage Power Generation System Based on Improved Cuckoo Search Algorithm

在风光储联合供电系统中,科学的配置储能元件的容量,分配不同储能元件之间的容量比,具有非常深远的意义。通过分析蓄电池和超级电容器的特性,提出基于该两类元件的混合储能系统及其能量分配策略,根据全生命周期(LCC)理论,以储能费用最小为目标,以蓄电池输出功率和系统负荷缺电率等指标为约束条件,建立储能容量优化模型。提出了自适应布谷鸟搜索算法,并用于求解某风光储联合供电系统的储能优化问题。算例结果分析显示,采用文中所述的能量分配策略和改进的布谷鸟算法可以有效降低储能系统成本,验证了模型及算法的正确性。

Rational planning to configure the system capacity and storage capacity and different energy elements is of great significance to the wind-PV-storage power generation system. By analyzing the energy storage characteristics of batteries and ultra-capacitors, a hybrid energy storage system based on the two energy storage element as well as its energy management strategy are proposed in this paper. According to the life cycle cost（LCC） theory, an optimization model is con- structed, which considers the lowest cost of energy storing device as the optimization objective, and considers the battery output power with LPSP of the system as the constraints. An adaptive Cuckoo search is proposed and then is used to solve the energy storage optimization problem of the Wind-PV- Storage Power Generation. The example analysis demonstrates that by using the energy management strategy and the improved Cuckoo search algorithm, the cost of energy storage could be reduced, thus proving correctness of the model with its algorithm.