Predictive Power Control for PV Plants With Energy Storage

This work presents a model predictive control (MPC) approach to manage in real-time the energy generated by a grid-tied photovoltaic (PV) power plant with energy storage (ES), optimizing its economic revenue. This MPC approach stands out because, when a long enough prediction horizon is used, the saturation of the ES system (ESS) can be advanced by means of a prediction model of the PV panels production. Therefore, the PV+ES power plant can modify its production so as to manage the power deviations with regard to that committed in the daily and intraday electricity markets, with the objective of reducing economic penalties. The initial power commitment is supposed in this work to be given by a higher level energy management operator. By a proper definition of its objective function, the predictive control allows us to economically optimize the PV+ES power plant performance. This control strategy is tested in simulations with actual data measured for different days with varying meteorological conditions. Results provide a good reference on the economic benefits which can be obtained thanks to the MPC introduction.