The Decomposition Method for Customer Directrix Load Based on Power Customers Load Profile Clustering

Due to the global warming caused by the excessive use of fossil energy, the uncertainty and volatility of new energy have put pressure on the regulation of the power system, resulting in problems such as abandoning wind and light. The customer directrix load has been proposed to define the ideal load curve shape to smooth the fluctuation, and achieve the balance of adjustable resources and non-adjustable resources. However, this method cannot personalize and guide different types of users, and fails to fully tap the user's adjustment potential. Therefore, a customer directrix load decomposition method based on power customers load profile clustering is proposed. Firstly, the research on user clustering and load customer directrix load is analyzed, especially for the problems faced by personalized clustering of users’ electricity consumption. Secondly, the decomposition scheme of the customer directrix load, the model of the sub-customer directrix load and the measurement of the effect are proposed, and a set of decomposition mechanism of the sub-customer directrix load is designed based on the clustering algorithm of user characteristics. The results of the example analysis show that compared with the existing mechanism, the sub-customer directrix load decomposition mechanism can fully tap the user's adjustment ability and guide the user closer to the customer directrix load. This mechanism is suitable for different kinds of clusters of spontaneous clustering according to the user power consumption characteristics. Finally, this mechanism can effectively reduce the problem of wind and light abandonment and improve the absorption capacity of new energy.