Optimal Wind Bidding Strategies in Day-Ahead Markets

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.
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Communication dans un congrès
Luis M. Camarinha-Matos; António J. Falcão; Nazanin Vafaei; Shirin Najdi. 7th Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), Apr 2016, Costa de Caparica, Portugal. IFIP Advances in Information and Communication Technology, AICT-470, pp.475-484, 2016, Technological Innovation for Cyber-Physical Systems. 〈10.1007/978-3-319-31165-4_44〉
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Isaias Gomes, Hugo Pousinho, Rui Melício, Victor Mendes. Optimal Wind Bidding Strategies in Day-Ahead Markets. Luis M. Camarinha-Matos; António J. Falcão; Nazanin Vafaei; Shirin Najdi. 7th Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), Apr 2016, Costa de Caparica, Portugal. IFIP Advances in Information and Communication Technology, AICT-470, pp.475-484, 2016, Technological Innovation for Cyber-Physical Systems. 〈10.1007/978-3-319-31165-4_44〉. 〈hal-01438274〉

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