User-side Participation Electricity Purchase Interaction Decision Model Based on LSTM in Competitive Markets

In order to better promote the construction of a healthy ecological system in the electricity sales market, this paper designs a user-centered electricity purchase interactive decision-making model based on LSTM (Long Short-Term Memory Network) from the user's perspective, focusing on how to integrate multiple social factors, such as coupon packages and flexible time-of-use electricity price policies, to accurately predict and guide users' electricity consumption behaviors. Through this solution, users can not only enjoy more personalized electricity price discounts, but also make more economical and reasonable electricity purchase decisions in complex electricity markets. Finally, the particle swarm algorithm combined with the CPLEX optimization tool was used to solve the model and obtain the optimal electricity purchase plan. Through actual cases and data analysis of a foreign country, this model can not only significantly improve the enthusiasm of users to participate in electricity purchase interactions, but also enable every user to obtain a more affordable and convenient electricity purchase experience in a highly competitive market environment.