Quantitative Analysis Model of User's Electrical Behavior for Smart Grid

Under smart power environment, mass electro-data bring new opportunities and challenges for user's electrical behavior analysis. This paper starts from individual user's electrical consumption monitoring to establish multi-dimensional load classification system and decompose individual user's electricity load. Then, for user's electrical behavior characteristics and user's electrical load characteristics, we apply improved K-means cluster to classify and analyze user's electrical behavior. On this basis, this paper designs a model for non-intrusive electrical load decomposition and recognition study to mine user's modes, assist grid company to formulate request correspondence and achieve the purpose of energy-saving and emission reduction.