With the rapid development of smart grid construction and the further reform of electric power system

the development of the commercialization and marketization of electric power is faster than that in any previous stage. One of the current policy trends is to deepen the reform of the electricity market and let the market function

not just let the government plan control. Real-time electricity pricing based on demand response was conceived. It can promote the participation of power users and guide the safe and stable operation of power grid. In this paper

the demand response of real-time electricity price is studied. It introduces the background

significance

current situation and relevant theories of demand response. Then

the common types of real-time electricity prices and principle of price elasticity of demand are analyzed. Based on the analysis of users’ historical electricity consumption data

this paper studies the users’ electricity consumption response behavior

establishes a regression model of user demand response based on gradient descent method

and predicts the optimal demand of users participating in demand response under this mechanism. This model utilizes the idea of regression to analyze the user’s self elasticity and cross elasticity coefficients

in order to simulate the user’s electricity consumption behavior under the dynamic electricity pricing mechanism. The real data of a region in the United States is imported into the model

and the error between the predicted results and the actual results is not large

which verifies the feasibility and authenticity of the model.