基于改进鸡群算法的非侵入式负荷监测

监测负荷运行状态有利于加强电网负荷侧管理,引导用户合理消费,实现节能降耗。针对小功率负荷与大功率负荷同时投入时,单一谐波电流特征易受线路电压、电流波动影响导致负荷辨识精度低的问题,提出一种基于改进鸡群算法的负荷监测方法,设计综合考虑稳态谐波电流和功率特征的正态分布度量函数,作为改进鸡群算法的适应度函数。实验结果表明,采用所提方法可有效提高负荷辨识准确率。

Non-intrusive load monitoring based on improved chicken swarm optimization algorithm

Monitoring load operation state is beneficial to strengthen the load side management of power grid, guide users to rationally use electricity, and realize energy saving and consumption reduction. Since the characteristics of single harmonic current is easily affected by the fluctuations of line voltage and current when the low power load and high power load are put into operation at the same time, causing low accuracy of load identification, a load monitoring method based on the improved chicken swarm optimization algorithm is proposed. The normal distribution metric function comprehensively considering the characteristics of steady-state harmonic current and active power is designed as the adaptation function of the improved chicken swarm optimization algorithm. The experimental results show that the proposed method can effectively improve the accuracy of load identification.