Optimisation strategy of off-grid wind and solar hydrogen production system based on reinforcement learning

Off-grid wind and solar hydrogen technology are large-scale development of renewable energy and achieve low-carbon operation. This article studies the evaluation of the economy of systems using the lowest economic indicator of penalty costs for wind and solar curtailment. Finally, reinforcement learning algorithms are used to solve the optimal optimisation model of systems. The calculation example shows that the proposed optimisation strategy can greatly reduce wind and light waste and improve the overall economic of the system.