基于改进粒子群算法的分布式电源经济性最优规划

Distributed power optimally economical planning based on modified discrete particle swarm optimization algorithm

分布式电源接入运行对系统造成的影响是多方面的。建立了综合系统费用模型,在货币量纲下将DG投资、发电成本、短路电流水平、可靠性水平、网损等因素纳入同一个目标函数进行优化。DG的选址定容是一个复杂的非连续性、非凸、非线性优化问题,引入疫苗接种和稀释等策略,对传统离散粒子群算法(DPSO)进行改进,得到求解效果更佳的改进离散粒子群算法(MDPSO)。应用IPLAN环境下的MDPSO算法对IEEE43节点系统进行分布式电源优化规划,并与传统DPSO算法优化结果进行比较,说明MDPSO算法可以成功应用于此类问题的求解。

In order to induct the multiple objects of DG planning into one single objective function, an integrated cost model is built, which uses monetary unit to measure the diverse impacts of DG on the power system, considering the investment cost of DG, power generation cost, system short circuit current level, system reliability level, net loss as five factors, and describes the locating and sizing of DG as a non-continuous, non-convex, nonlinear optimization problem. The problem can be better solved by a modified discrete particle swarm optimization algorithm （MDPSO）, which introduces immunization, dilution, and variation strategy, than by the traditional DPSO algorithm.The feasibility of the MDPSO method is verified by the simulation results of IEEE 43-bus system.