Dynamic Pricing Strategies for the Electricity Retail Market Using Reinforcement Learning Algorithms
This paper models the dynamic pricing problem of power retailers as a Markov decision process within a continuous action space and proposes a solution framework based on proximal policy optimization algorithms, validating the feasibility and practical effectiveness of reinforcement learning approaches for dynamic prici...