Abstract:The previous time-sharing of time-of-use electricity prices only considered the change in the value of the load curve, ignoring the impact of time-sharing on the establishment of time-of-use electricity prices and the impact on user behavior. As a result, the optimization of time-of-use electricity prices was limited, and the demand-side response could not achieve optimal results. In order to solve this problem, a model of time-of-use electricity price division and price formulation based on user behavior is proposed. First, the peak segment, flat segment, and valley segment are formulated by fuzzy clustering method. For the variables to be optimized, a consumer electricity price and electricity response behavior model is established according to consumer psychology. Finally, the goal is to maximize user satisfaction and grid revenue, while optimizing time-of-use electricity prices and time division. The simulation results show that, compared with dividing the period directly based on the FCM fuzzy clustering analysis method, the model can better stimulate the user to respond to the time-of-use electricity price according to the load characteristics, promote a smoother user response curve, and further reduce the peak shaving cost. Optimize the time division method to improve the effectiveness of social welfare.