School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China
This work is supported by National Natural Science Foundation of China (No. 51777068).
Load monitoring is an important part of intelligent electricity consumption. A non-intrusive load disaggregation method considering time-phased state behavior is proposed to solve the problem that existing low frequency non-intrusive load disaggregation methods require more priori information and have lower accuracy for load with similar or lower power. Firstly, power data of the load device is clustered to construct a load state template.An intelligent optimization method for the typical behavior time period that does not require a specified number of time periods is proposed. Load state behavior law is extracted by time-phase to construct a load behavior template. Then, on the basis of the traditional power characteristics, considering the two dimensions of probability and time, the time-phased state probability factor (TSPF) is introduced into the objective function as a new load characteristic, and the load disaggregation is realized by multi-feature genetic optimization iteration. Finally, the validity and accuracy of the method are verified on the public data set.
CUI Liangjie,SUN Yi,LIU Yaoxian,et al.Non-intrusive Load Disaggregation Method Considering Time-phased State Behavior[J].Automation of Electric Power Systems,2020,44(5):215-222.DOI:10.7500/AEPS20190225006Copy