The energy dispatch of wind-solar-hydrogen storage systems is an effective technique for mitigating the intermittency of renewable energy sources. Addressing issues such as power fluctuations in off-grid hydrogen production systems and substantial tracking errors, we present a two-stage optimization scheduling strategy based on Model Predictive Control (MPC). During the first stage, a day-ahead scheduling approach is developed by comprehensively considering the stochastic behavior of renewable energy and the operational lifespan of energy storage, with the objective of optimizing the economic performance of the system. In the second stage, a day-ahead rolling optimization and correction strategy based on MPC is proposed to handle power fluctuations stemming from forecast errors in renewable energy generation, while concurrently ensuring the stable operation of the system. To tackle the inadequacies of conventional MPC in dealing with sudden disturbances, we devise an adaptive temporal parameter controller capable of determining optimal predictive and control temporal parameters. This controller design enhances the control precision and stability of MPC when confronted with abrupt changes in renewable energy generation due to sudden increases or decreases. The effectiveness of the proposed model and algorithm is validated through a case study using a microgrid as an illustrative example.
Keywords wind-solar coupling; hydrogen energy storage; model predictive control; energy management