Probabilistic forecasting for sizing in the capacity firming framework
Autor: | Antonio Vicino, Antonello Giannitrapani, Simone Paoletti, Bertrand Cornélusse, Xavier Fettweis, Jonathan Dumas |
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Rok vydání: | 2021 |
Předmět: |
Mathematical optimization
Optimization problem Computer science Stochastic process Probabilistic logic Context (language use) Systems and Control (eess.SY) stochastic optimization capacity firming PV scenarios Sizing Electrical Engineering and Systems Science - Systems and Control Optimization and Control (math.OC) Hyperparameter optimization FOS: Mathematics FOS: Electrical engineering electronic engineering information engineering Stochastic optimization Probabilistic forecasting Mathematics - Optimization and Control |
DOI: | 10.48550/arxiv.2106.02323 |
Popis: | This paper proposes a strategy to size a grid-connected photovoltaic plant coupled with a battery energy storage device within the \textit{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 Li\`ege University (ULi\`ege), Belgium. |
Databáze: | OpenAIRE |
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