14 / 2020-09-23 19:06:54

Identification of Potential Power Users Who Can Transfer Load to Valley Period Based on Association Rules Analysis

association rules analysis; load transfer; DSM; power load pattern; power user identification

Power System and Automation > Other topics in power system

with the continuous improvement of smart grid informatization and digitization, power operators have accumulated a large number of power user data in actual operation. Through data mining on power user data, the power users' power load pattern can be analyzed and reasonable power usage suggestions can be given. In this paper, the Kmeans++ clustering algorithm is used to classify the power users into the users who have realized and unrealized load shifts to valley period. At the same time, using the power data such as power consumption, energy consumption category and the business information disclosed by enterprises on the Internet, Apriori algorithm is used to mine the association rules of users who have realized the load valley period transfer, and through the analysis of these rules, the potential power users who can realize the transfer of electricity consumption to valley period are identified. The practical application shows that this method realizes the above-mentioned user identification.