Optimal Joint Bidding and Pricing of Electricity Retailers Using Multi-agent Deep Reinforcement Learning
2023 IEEE 7th Conference on Energy Internet and Energy System Integration (EI2)(2023)
摘要
In real electricity markets, it is more valuable and difficult to study the optimal decision-making of a price-maker entity than those of a price-taker entity. This paper concerns with the optimal joint bidding and pricing problem of a price-maker electricity retailer. After formulating the original optimization problem into a Markov decision process (MDP), a novel multi-agent deep reinforcement learning (MADRL) approach is proposed to solve for the optimal joint bidding and pricing strategy. Two agents are responsible for the bidding strategy and pricing srategy respectively. Numerical results prove the effectiveness of the proposed method. Insightful comparative analysis is also conducted for price-maker and price-taker cases.
更多查看译文
关键词
multi-agent deep reinforcement learning,electricity retailer,electricity market,bidding,pricing
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要