Q-Learning Algorithm Design for Distributed Economic Dispatch Problem with Multiple Coupling Constraints

The primary goal of the distributed economic dispatch challenge is to satisfy meet demand and various operational constraints while minimizing the overall generation cost of all generators. Traditional methods can be ineffective due to unknown cost functions and coupling constraints among different generators. This article introduces a Q-learning algorithm that solves the economic dispatch problem in a distributed manner, efficiently managing multiple coupling constraints. Our apptoach addresses the challenge of dynamic economic dispatch, where both the cost function and resource transfer function are unknown. Numerical simulations validate the algorithm's effectiveness, showcasing its capability to optimize power generation schedules under complex and dynamic conditions.