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Abstract : This paper presents a computer application (CoA) for wind energy (WEn) bidding strategies (BStr) in a pool-based electricity market (EMar) to better accommodate the variability of the renewable energy (ReEn) source. The CoA is based in a stochastic linear mathematical programming (SLPr) problem. The goal is to obtain the optimal wind bidding strategy (OWBS) so as to maximize the revenue (MRev). Electricity prices (EPr) and financial penalties (FiPen) for shortfall or surplus energy deliver are modeled. Finally, conclusions are addressed from a case study, using data from the pool-based EMar of the Iberian Peninsula.
https://hal.inria.fr/hal-01438274 Contributor : Hal IfipConnect in order to contact the contributor Submitted on : Tuesday, January 17, 2017 - 3:38:41 PM Last modification on : Tuesday, January 17, 2017 - 3:49:43 PM Long-term archiving on: : Tuesday, April 18, 2017 - 2:57:08 PM
Isaias R. Gomes, Hugo I. Pousinho, Rui Melício, Victor F. Mendes. Optimal Wind Bidding Strategies in Day-Ahead Markets. 7th Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), Apr 2016, Costa de Caparica, Portugal. pp.475-484, ⟨10.1007/978-3-319-31165-4_44⟩. ⟨hal-01438274⟩