Probabilistic forecasting for sizing in the capacity firming framework

This paper proposes a strategy to size a grid-connected photovoltaic plant coupled with a battery energy storage device within the capacity firming specifications of the French Energy Regulatory Commission. The sizing problem is difficult to solve due to the capacity firming framework that consists in a two-phase engagement control with a day ahead nomination and an intraday control to minimize deviations from the planning. The two-phase engagement control is modeled with a deterministic and stochastic approaches. The optimization problems are formulated as mixed-integer quadratic problems with linear constraints, using a Gaussian copula methodology to generate PV scenarios, to approximate the mixed-integer non-linear problem of the capacity firming. Then, a grid search is conducted to approximate the optimal sizing for a given selling price using both the deterministic and stochastic approaches. The case study is composed of PV production monitored on site at the University of Liège (ULiège), Belgium.