基于灰狼优化算法的分布式电源定容选址研究

Siting and Sizing of Distributed Generation Based on Grey Wolf Optimization Algorithm

分布式电源具有环境友好性和可持续性,但分布式电源接入配电网的位置及所注入的容量会对系统功率损耗和电压稳定性产生影响。为削弱这一影响,提出一种灰狼优化算法(GWOA)并应用于分布式系统的多个DG选址和定容研究中,在满足各种约束条件限制的情况下建立了以无功功率损耗最小化和电压偏移最小的多目标函数。利用GWOA应用于IEEE 69节点配电系统中进行多种DG类型分配的不同案例研究,并将结果分别与引力搜索算法(GSA)和蝙蝠算法(BA)两种方法进行比较分析,验证了GWOA在降低无功功率损耗和改善电压分布特性方面的可行性和有效性。

Distributed generation(DG)is of environmental friendliness and sustainability,but the siting and sizing of DG connected to distribution network has influence on the power loss and voltage stability of the system.In order to weaken the influence,the paper proposes a gray wolf optimization algorithm(GWOA),and applies it to the siting and sizing of several DGs in distributed systems.In the case of satisfying various constraints,a multi-objective function with minimum reactive power loss and minimum voltage deviation is established.The different cases about the siting and sizing of several DGs in IEEE 69-node distribution system by using GWOA are studied,and the results are compared with those of two methods of gravitational search algorithm(GSA)and bat algorithm(BA),verifying the feasibility and effectiveness of GWOA in reducing the reactive power loss and improving the voltage distribution.