Industrial user demand response flexibility improvement method for machine learning in electricity-carbon market

The invention discloses an industrial user demand response flexibility improvement method based on machine learning in an electricity-carbon market, and the method specifically comprises the following steps: analyzing the load characteristics of an industrial park user, and obtaining the influence factors of the load of the industrial park on the demand response flexibility according to the load characteristics; a demand response flexibility comprehensive evaluation index system of industrial users in the park is constructed based on a carbon transaction and demand response mechanism, and comprehensive weights of indexes are determined by adopting a method of combining an analytic hierarchy process and an improved entropy weight method; based on an SPA and TOPSIS coupling method, establishing a quantitative evaluation method for the user load flexibility of the industrial park; a power consumption demand mode is predicted by adopting a machine learning algorithm, and a carbon emission and power consumption co