Optimal Wind Bidding Strategies in Day-Ahead Markets - Technological Innovation for Cyber-Physical Systems
Conference Papers Year : 2016

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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Dates and versions

hal-01438274 , version 1 (17-01-2017)

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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⟩
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