基于自适应免疫粒子群优化算法的配电网状态估计

State Estimation Based on Optimization Algorithm of Adaptive Immune Particle Swarm for Distribution System

针对配电网中分布式发电机等设备的非线性特性和配电网量测配置特点,结合粒子群优化算法(PSO)的特点,提出了采用自适应免疫PSO算法进行配电网状态估计的思路。该算法引入免疫系统的免疫信息处理机制和自动调整动量系数的自适应因子的粒子群算法,解决了配电网状态估计中的非线性问题,克服了基本PSO算法容易陷入局部最优解的缺点,不仅增强了全局搜索能力,而且获得了理想的收敛速度和精度。算例证实了该算法的有效性,与基本粒子群算法的比较,显示了其优越性。

This paper proposes an adaptive immune particle swarm optimization algorithm for a practical distribution state estimation taking into account the nonlinear characteristics in the distribution such as distributing generator and measurement configuration and combining with PSO’s characteristic. The proposed method make use of particle swarm optimization with transacting mechanism of immune information in immune system and an adaptive factor with an ability of adjusting momentum coefficient automatically, sol...