PV/Hydrogen hybrid renewable energy system control using distributed economic MPC scheme under partial shading conditions

Combining hydrogen energy with conventional islanded photovoltaic (PV) plants as PV/Hydrogen hybrid renewable energy system (HRES) is emerging as a promising solution for renewable energy sources generation. However, solar and hydrogen energy systems are intermittent, with complex dynamics and multiple constraints. In addition, electro-hydrogen synergy, power regulation, and economic optimization of HRES face challenges due to the stochastic nature of the loads (i.e., electro-hydrogen demand) and the partial shading conditions. The traditional hierarchical distributed model predictive control and the centralized economic model predictive control suffer from poor dynamic performance and high computational burden, respectively. In this paper, considering an HRES of geographically dispersed integrated standalone PVs/fuel cells/supercapacitors/electrolyzes/hydrogen refueling stations, constituted a distributed economic model predictive control (DEMPC) scheme that integrates these objectives into one optimal control framework. By designing a global cost function, the Nash optimal solutions within distributed framework approach the Pareto optimum. This approach thus achieves energy supply-demand balance, DC bus voltage stability, and economic system operation in the coupled microgrid and hydrogen refueling station system. Simulations verify the superiority of the DEMPC scheme under the complex partial shading conditions and electro-hydrogen load perturbations.