A Real Time MPC-Based Strategy for PV Plant with Battery Energy Storage

Photovoltaic (PV) generation share in global energy has been increasing in recent years. This growth has raised concern for the power grid operators because of the intermittency in the PV power generation and prediction. Battery energy storage (BES) is introduced as a possible solution to this challenge. BES needs to be operated optimally since their investment cost is not low enough. In this paper, an innovative control strategy based on model predictive control (MPC) is proposed to manage an integrated PV plant and BES in order to get maximum revenue. Using the hourly prediction of PV output power and electricity market price in the optimization problem, the PV plant can adjust its generation so as to handle the power fluctuation with regard to the committed power and reduce economic penalties. Moreover, the BES degradation cost is modeled to precisely evaluate the PV plant income and obtain more realistic answers. Numerical results can prove and validate the effectiveness of the proposed approach.