计及电器状态关联规则的非侵入式负荷分解

非侵入式负荷监测与分解(NILMD)是获取电器用电信息的关键技术,针对当前NILMD缺乏考虑不同电器关联运行的用电模式和电器状态的强波动性以致分解精度低的问题,提出一种计及电器状态关联规则的新型负荷分解方法。通过仿射传播聚类提取电器的运行状态,基于互信息熵,运用关联规则算法挖掘电器状态的关联性;调整含关联规则的样本权值并结合k近邻算法实现状态辨识;利用极大似然估计完成负荷功率分解。测试算例验证了所提方法的有效性和准确性。

Non-intrusive load decomposition considering association rules of appliances’state

NILMD(Non-Intrusive Load Monitoring and Decomposition)is the key technology to obtain elec tricity consumption information of appliances.Aiming at the problem of low decomposition accuracy which is caused because that current NILMD lacks of concerning about the electricity consumption pattern of associated operation between different appliances and high volatility of appliances’state,a novel load decom-position method considering the association rules of appliances’state is proposed.The operation state of each appliance is extracted by affinity propagation clustering.Based on mutual information entropy,the association rule algorithm is used to mine the association of appliances’state.The sample weights with association rules are adjusted and combined with kNN(k-Nearest Neighbor)algorithm to realize the state identification.The maximum likelihood estimation is used to decompose load power.Test examples verify the effectiveness and accuracy of the proposed method.