Bidding strategy of wind-thermal energy producers |
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| Affiliation: | 1. IDMEC, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal;2. Departamento de Física, Escola de Ciências e Tecnologia, Universidade de Évora, R. Romão Ramalho 59, 7002-554 Évora, Portugal;3. Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emídio Navarro, 1950-062 Lisbon, Portugal;1. Faculty of Science and Biotechnology, Universiti Selangor, Bestari Jaya 45600, Malaysia;2. Department of Bioprocess Engineering, Faculty of Chemical Engineering, c/o Institute of Bioproduct Development, Universiti Teknologi Malaysia, UTM, Skudai 81310, Malaysia;1. Institut national de la recherche scientifique, Centre Eau Terre Environnement, 490 rue de la Couronne, Québec, QC, G1K 9A9, Canada;2. Département de génie mécanique, École de Technologie Supérieure, 1100 rue Notre-Dame Ouest, Montréal, QC, H3C 1K3, Canada;1. Department of Materials Science and Engineering, China Jiliang University, Hangzhou 310018, PR China;2. Zhejiang Tianneng Energy Technology Co., Ltd., Changxing County, Zhejiang Province 313100, PR China;1. Department of Electrical Engineering, College of Engineering, King Saud University, Riyadh, 11421, Saudi Arabia;2. Electrical & Computer Engineering, University of Waterloo, Waterloo, Ontario, N2L 3G1, Canada;1. Faculty of Engineering, Department of Electrical Engineering, Bu-Ali Sina University, Hamedan, Iran;2. Faculty of Engineering, Department of Electrical Engineering, Ayatollah Borujerdi University, Broujerd, Iran |
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| Abstract: | This paper presents a stochastic mixed-integer linear programming approach for solving the self-scheduling problem of a price-taker thermal and wind power producer taking part in a pool-based electricity market. Uncertainty on electricity price and wind power is considered through a set of scenarios. Thermal units are modelled by variable costs, start-up costs and technical operating constraints, such as: forbidden operating zones, ramp up/down limits and minimum up/down time limits. An efficient mixed-integer linear program is presented to develop the offering strategies of the coordinated production of thermal and wind energy generation, having as a goal the maximization of profit. A case study with data from the Iberian Electricity Market is presented and results are discussed to show the effectiveness of the proposed approach. |
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| Keywords: | Bidding strategy Stochastic programming Mixed integer linear programming Wind thermal coordination |
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