Joint Optimal Operation of Multi Wind-Hydrogen System Based on Multi-Agent Reinforcement Learning

In allusion to the joint operation of multi wind-hydrogen system, based on multi-agent reinforcement learning a multi wind-hydrogen system joint optimization operation method was proposed to make the multi wind-hydrogen system enable to accommodate wind power effectively and meanwhile to maximize the joint revenue. Firstly, considering the joint operation of wind farm, hydrogen generation and hydrogenation station in the manner of contract transaction, respective operation models for them were constructed. Secondly, taking the maximized joint operation revenue of multi wind-hydrogen system as the objective, a joint optimization operation model was established. Thirdly, to cope with the dimension disaster caused by multi decision variables of multi wind-hydrogen system, the multi agent was led into the reinforcement learning and the method of multi-decision update was adopted to speed up the algorithm convergence. Finally, the reasonableness of the established model and the feasibility of the adopted method are verified by simulation example.