基于果蝇优化算法的配电网状态估计

State Estimation of Power Distribution Network Based on Fruit Fly Optimization Algorithm

配电网状态估计的目的是根据获取的配电网的各种量测信息,估计配电网系统的运行状态,是配电管理系统(DMS)的重要核心功能之一。根据配电网特点,以电压幅值和相角为状态变量,以量测值和估计值误差最小为目标函数,以潮流方程和估计值的上、下限为约束条件,构建配电网状态估计的优化模型,采用果蝇优化算法对该模型进行求解。算例表明,基于视觉和嗅觉的觅食行为启发的果蝇优化算法可有效求解该优化模型,具有易于实现、控制参数少和计算精度高的特点,为配电网状态估计提供了新的途径。

The purpose of distribution network state estima. tion is to estimate the current operating state of the distribution network system based on various measured information obtained from the distribution network,which is one of the important core functions of the distribution management system(DMS). Accor. ding to the characteristic of distribution network,taking the vol. tage amplitude and phase angle as state variables,and with min. imizing the error between the measured value and the estimated value as the objective function,and the upper and lower limits of the power flow equation and estimated value as the constraint conditions,we constructed an optimization model of distribution network state estimation in this paper and used the fruit fly opti. mization algorithm to solve the model. The example shows that, inspired by the foraging behavior of vision and smell,the pro. posed optimization algorithm has the characteristics of easy im. plementation,less control parameters and higher computing pre. cision,providing a new way for the distribution network state es. timation.