基于自适应差分进化算法的电力系统动态状态估计

Dynamic State Estimation of Power System Based on Adaptive Differential Evolution Algorithm

提出一种基于自适应差分进化算法的电力系统状态动态估计方法。动态估计包括预测和滤波2个阶段。在预测阶段,利用布朗双指数平滑方法预测下一个时间间隔的状态;在滤波阶段,利用预测阶段获得的预测状态,基于自适应差分进化算法对目标函数进行寻优,通过优化算法提高预测精度,从而减小状态预测的误差。仿真结果表明:所提方法具有较小的估计误差,对坏数据具有较好的抑制能力。

A dynamic state estimation method of power system based on adaptive differential evolution algorithm is proposed in this paper.The dynamic estimation includes prediction and filtering stages.In the prediction stage,the Brownian double exponential smoothing method is used to predict the state of the next time interval;in the filtering stage,the predicted state obtained in the prediction stage is used to perform the objective function based on the adaptive differential evolution algorithm.With the optimization algorithm,the error of state prediction is reduced,and the prediction accuracy is improved.Simulation results show that the proposed method has less estimation error and better ability to suppress bad data.