Evaluation of User Adjustable Capacity Boundary Based on FCM Clustering and Multi-Factor Electricity Price Elasticity

With the large-scale access of renewable energy sources such as wind power and photovoltaic power to the power grid, the overall inertia of the power grid has dropped significantly, and demand response has become an effective means of demand-side management. However, the uncertainty of demand response is large, and there is currently little research on the calculation of user response boundaries. This paper first establishes a segmented time-of-use electricity price (STOU) strategy based on fuzzy C-means clustering (FCM) as a prerequisite. Secondly, an elasticity matrix correction method considering uncertain factors such as temperature and income is proposed to characterize user-side uncertainty and then calculate user response capacity. Finally, through comparison with local electricity price policies and parameter sensitivity analysis, it is verified that the STOU proposed in this paper can effectively reduce the peak-to-valley difference and smooth the load curve. The model can reflect the changes in the adjustable capacity of users under different temperature and economic conditions, and provide accurate boundaries for subsequent capacity allocation and scheduling.