[en] 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. In this context, the sizing problem is challenging due to the 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 deterministic and stochastic approaches. The optimization problems are formulated as mixed-integer quadratic problems, 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 Liège University (ULiège), Belgium.
Disciplines :
Energy Computer science
Author, co-author :
Dumas, Jonathan ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Smart-Microgrids
Language :
English
Title :
Powertech 2021 presentation: Probabilistic forecasting for sizing in the capacity firming framework
Publication date :
June 2021
Event name :
14th IEEE PES PowerTech Conference
Event date :
28/06/2021 - 02/07/2021
By request :
Yes
Audience :
International
References of the abstract :
Paper in open access: http://hdl.handle.net/2268/253898