A Stochastic Optimization Method for Planning and Real-Time Control of Integrated PV-Storage Systems: Design and Experimental Validation

This paper proposes a solution for the day-ahead planning and the real-time control of an integrated system composed of a photovoltaic (PV) plant and a battery energy storage system (BESS). The day-ahead algorithm provides the optimal daily energy delivery profile based on a prediction of the PV production. The objective is to maximize the economic gain, according to the request of specific profile shape. The real-time operation algorithm dynamically regulates the BESS power exchange, in order to realize the scheduled power profile. Both of the proposed algorithms exploit chance-constrained stochastic optimization, in order to take into account the uncertainties of the PV power predictions. Simulation results show the effectiveness of the proposed solutions, while their validation is achieved by experimental tests, executed on a low-voltage microgrid controlled by a distribution management system.