Double-layer optimal scheduling method for solar photovoltaic thermal system based on MPC

Solar photovoltaic thermal system (SPTS) can fully tap solar energy resources to realize thermal and electric supply for users simultaneously, while achieving the optimal scheduling of SPTS, keeping the system power stable and reliable operation of energy storage equipment become a new challenge. This paper proposes a double-layer optimal scheduling method for SPTS based on model predictive control (MPC) considering battery performance deterioration. Firstly, in day-ahead scheduling stage, the minimization economic cost of SPTS is taken as the optimization function to obtain day-ahead scheduling plan. Secondly, in the day-in scheduling stage, the rolling optimization scheme is implemented by using MPC to reduce power fluctuations and achieve optimal scheduling adjustment. Moreover, the battery performance decay parameter is introduced into MPC model and embedded into the optimization problem to prolong the cyclic life deterioration of the battery. Finally, the results show that the proposed double-layer scheduling method improves 5.03% and 14.28% respectively in terms of total cost and battery maintenance.