A Stochastic Programming Model for the Thermal Optimal Day-Ahead Bid Problem with Physical Futures Contracts
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| Názov: | A Stochastic Programming Model for the Thermal Optimal Day-Ahead Bid Problem with Physical Futures Contracts |
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| Autori: | Corchero García, Cristina, Heredia, F.-Javier (Francisco Javier) |
| Prispievatelia: | Universitat Politècnica de Catalunya. Departament d'Estadística i Investigació Operativa, Universitat Politècnica de Catalunya. GNOM - Grup d'Optimització Numèrica i Modelització |
| Zdroj: | UPCommons. Portal del coneixement obert de la UPC Universitat Politècnica de Catalunya (UPC) Recercat. Dipósit de la Recerca de Catalunya Universitat Jaume I |
| Informácie o vydavateľovi: | 2009. |
| Rok vydania: | 2009 |
| Predmety: | Classificació AMS::90 Operations research, Optimal bid, Programming (Mathematics), Matemàtiques i estadística::Investigació operativa::Programació matemàtica [Àrees temàtiques de la UPC], mathematical programming::90C Mathematical programming, Classificació INSPEC::Optimisation::Mathematical programming::Stochastic programming, Stochastic programming, Àrees temàtiques de la UPC::Matemàtiques i estadística::Investigació operativa::Optimització, 90 Operations research, mathematical programming::90C Mathematical programming [Classificació AMS], Optimisation::Mathematical programming::Stochastic programming [Classificació INSPEC], Classificació AMS::90 Operations research, mathematical programming::90C Mathematical programming, Classificació AMS::90 Operations research, mathematical programming::90B Operations research and management science, mathematical programming::90B Operations research and management science, Futures contracts, 90 Operations research, mathematical programming::90B Operations research and management science [Classificació AMS], Programació (Matemàtica), Àrees temàtiques de la UPC::Matemàtiques i estadística::Investigació operativa::Programació matemàtica, Electricity day-ahead market, Matemàtiques i estadística::Investigació operativa::Optimització [Àrees temàtiques de la UPC] |
| Popis: | The reorganization of the electricity industry in Spain completed a new step with the start-up of the Derivatives Market. One main characteristic of MIBEL’s Derivatives Market is the existence of physical futures contracts; they imply the obligation to settle physically the energy. The market regulation establishes the mechanism for including those physical futures in the day-ahead bidding of the Generation Companies. The goal of this work is to optimize coordination between physical futures contracts and the Day-Ahead bidding which follow this regulation. We propose a stochastic quadratic mixed-integer programming model which maximizes the expected profits, taking into account futures contracts settlement. The model gives the simultaneous optimization for the Day-Ahead Market bidding strategy and power planning production (unit commitment) for the thermal units of a price-taker Generation Company. The uncertainty of the day-ahead market price is included in the stochastic model through a set of scenarios. Implementation details and some first computational experiences for small real cases are presented. |
| Druh dokumentu: | Report |
| Popis súboru: | application/pdf |
| Jazyk: | English |
| Prístupová URL adresa: | https://hdl.handle.net/2117/2795 http://hdl.handle.net/2117/2795 |
| Rights: | CC BY NC ND |
| Prístupové číslo: | edsair.dedup.wf.002..f9dd5311b762db8b93c16bebbf91cf3f |
| Databáza: | OpenAIRE |
Nájsť tento článok vo Web of Science | Abstrakt: | The reorganization of the electricity industry in Spain completed a new step with the start-up of the Derivatives Market. One main characteristic of MIBEL’s Derivatives Market is the existence of physical futures contracts; they imply the obligation to settle physically the energy. The market regulation establishes the mechanism for including those physical futures in the day-ahead bidding of the Generation Companies. The goal of this work is to optimize coordination between physical futures contracts and the Day-Ahead bidding which follow this regulation. We propose a stochastic quadratic mixed-integer programming model which maximizes the expected profits, taking into account futures contracts settlement. The model gives the simultaneous optimization for the Day-Ahead Market bidding strategy and power planning production (unit commitment) for the thermal units of a price-taker Generation Company. The uncertainty of the day-ahead market price is included in the stochastic model through a set of scenarios. Implementation details and some first computational experiences for small real cases are presented. |
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