{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/probabilistic-forecasting-for-sizing-in-the","title":"Probabilistic forecasting for sizing in the capacity firming framework","arxiv_id":"2106.02323","date":"2021-06-04","proceeding":null,"authors":["Jonathan Dumas","Bertrand Cornélusse","Xavier Fettweis","Antonello Giannitrapani","Simone Paoletti","Antonio Vicino"],"abstract":"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.","url_abs":"https://arxiv.org/abs/2106.02323v1","url_pdf":"https://arxiv.org/pdf/2106.02323v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"probabilistic-forecasting-for-sizing-in-the","repo_url":"https://github.com/jonathandumas/capacity-firming","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"probabilistic-forecasting-for-sizing-in-the","repo_url":"https://github.com/jonathandumas/capacity-firming-ro","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}