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.
关键词
电力用户/市场化交易/智能推荐系统/发电企业
Key words
power users/market transaction/intelligent recommendation system/power generation enterprise
维普
万方数据