Research on Microgrid Power Direct Transaction Behavior Based on Blockchain

Abstract

Because data mining has a good processing capacity for data, the clustering analysis of the historical data which is direct transactions of microgrid power provides a reliable technical support. In order to solve the problem of the imbalance between the power demand of users and the power supply of the grid in the direct transaction of microgrid power, an algorithm based on spectral clustering combined with empirical rules is proposed in this paper. The historical data (such as electricity energy, quotation submission time, and transaction price) between users and power suppliers who complete transaction settlement through the blockchain is used for clustering analysis by this method. By analyzing the clustering results, a reliable adjustment scheme to control the balance of supply and demand in microgrid power market is obtained. Through simulation experiments, the feasibility of the direct power trading model based on blockchain and the effectiveness of the algorithm based on spectral clustering combined with empirical rules are verified, so as to obtain the variation law of electricity demand and electricity price in different time periods.