An Intelligent Recommendation System for Power Users to Participate in Market Transactions
This paper proposes an intelligent recommendation system for electric power users to participate in the market transactions to help users to participate in the electricity market transactions efficiently and accurately.By collecting and analyzing the power market data,combining the users'electricity characteristics,preferences and historical trading behav-ior,the system uses machine learning algorithm to provide users with personalized power products and trading strategy recommendations.First,the intelligent recommendation technology is summarized,and the design objectives and func-tional requirements of the intelligent recommendation system are defined.Subsequently,the intelligent recommendation algorithm and the system implementation of the power user transaction mode are elaborated in detail.Finally,the effec-tiveness of the system is verified through experiments.The experimental results show that the recommendation system can effectively improve the transaction decision efficiency and satisfaction of power users.At the same time,the research provides a new market transaction decision support tool for power users.
power usersmarket transactionintelligent recommendation systempower generation enterprise
万方数据
维普
