Given the significant amount of installed generation-capacity based on wind power, and also due to current economic downturn, the subsidies and incentives that have been widely used by wind-power producers to recover their investment costs have decreased and are even expected to disappear in the near future. In these conditions, wind-power producers need to develop offering strategies to make their investments profitable counting solely on the market. This paper proposes a multi-stage risk-constrained stochastic complementarity model to derive the optimal offering strategy of a wind-power producer that participates in both the day-ahead and the balancing markets. Uncertainties concerning wind-power productions, market prices, demands' bids, and rivals' offers are efficiently modeled using a set of scenarios. The conditional-value-at-risk metric is used to model the profit risk associated with the offering decisions. The proposed model is recast as a tractable mixed-integer linear programming program solvable using available branch-and-cut algorithms. Results of a case study are reported and discussed to show the effectiveness and applicability of the proposed approach.
机构:
Hong Kong Polytech Univ, Dept Elect Engn, Hung Hom, Hong Kong, Peoples R ChinaHong Kong Polytech Univ, Dept Elect Engn, Hung Hom, Hong Kong, Peoples R China
Gao, Xiang
Chan, Ka Wing
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Hong Kong Polytech Univ, Dept Elect Engn, Hung Hom, Hong Kong, Peoples R ChinaHong Kong Polytech Univ, Dept Elect Engn, Hung Hom, Hong Kong, Peoples R China
Chan, Ka Wing
Xia, Shiwei
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机构:
North China Elect Power Univ, State Key Lab Alternate Elect Power Syst Renewabl, Beijing 102206, Peoples R ChinaHong Kong Polytech Univ, Dept Elect Engn, Hung Hom, Hong Kong, Peoples R China
Xia, Shiwei
Zhou, Bin
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机构:
Hunan Univ, Hunan Key Lab Intelligent Informat Anal & Integra, Changsha 410082, Hunan, Peoples R ChinaHong Kong Polytech Univ, Dept Elect Engn, Hung Hom, Hong Kong, Peoples R China
Zhou, Bin
Lu, Xi
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Hong Kong Polytech Univ, Dept Elect Engn, Hung Hom, Hong Kong, Peoples R ChinaHong Kong Polytech Univ, Dept Elect Engn, Hung Hom, Hong Kong, Peoples R China
Lu, Xi
Xu, Da
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Hunan Univ, Hunan Key Lab Intelligent Informat Anal & Integra, Changsha 410082, Hunan, Peoples R ChinaHong Kong Polytech Univ, Dept Elect Engn, Hung Hom, Hong Kong, Peoples R China
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Univ Castilla La Mancha, Escuela Tecn Super Ingn Ind, E-13071 Ciudad Real, SpainUniv Castilla La Mancha, Escuela Tecn Super Ingn Ind, E-13071 Ciudad Real, Spain
Gonzalez, Virginia
Pozo, David
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Pontificia Univ Catolica Chile, Dept Ind & Syst Engn, Santiago, ChileUniv Castilla La Mancha, Escuela Tecn Super Ingn Ind, E-13071 Ciudad Real, Spain
Pozo, David
Contreras, Javier
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Univ Castilla La Mancha, Escuela Tecn Super Ingn Ind, E-13071 Ciudad Real, SpainUniv Castilla La Mancha, Escuela Tecn Super Ingn Ind, E-13071 Ciudad Real, Spain