Day-Ahead Planning and Real-Time Control of Integrated PV-Storage Systems by Stochastic Optimization

Abstract

Abstract This paper proposes a solution for the day-ahead planning and the control of real-time operation of a large utility-scale grid-connected system composed by a photovoltaic plant (PV) integrated with a battery energy storage system (BESS). The day-head planning algorithm determines the optimal daily energy delivery profile based on a prediction of the PV power production. The objective is to maximize the power delivery, according to the request of specific profile shape constraints, which can be defined by the transmission system operator. The real-time operation algorithm dynamically regulates the BESS power exchange, in order to realize the planned power profile and satisfying operational and technical constraints. The proposed algorithms use chance-constrained stochastic optimization, which allows the day-ahead planning and the real-time operation to stochastically take into to account long-term and short-term PV power predictions, respectively. Simulations results show the effectiveness of the proposed solutions.