Electricity consumption pattern recognition based on the big data technology to support the peak shifting potential analysis

High GDP growth coupled with extensive power consumption of users lead to the rapid growth of peak load, causing the increase of the gap between peak and valley load and the dropping of the power utilization. In order to reduce peak-valley load difference and improve load rate effectively, this paper proposed a new idea for peak load shifting management faced with smart grid. The paper uses big data technology for electricity users´ pattern recognition, and applies it to peak load shifting management. This kind of peak load shifting potential analysis of users based on pattern recognition can provide the basis for the management of power supply companies, and cover the shortage of extensive management before, at the same time it supports peak load shifting management as a long-term work to implement.