stochastic programming

Optimal Bidding Strategies for Thermal and Combined Cycle Units in the Day-ahead Electricity Market with Bilateral Contracts

Publication TypeConference Paper
Year of Publication2009
AuthorsHeredia, F.-Javier; Rider, Marcos.-J.; Corchero, C.
Conference Name2009 Power Engineering Society General Meeting
Series TitleProceedings of the Power Engineering Society General Meeting, 2009. IEEE
Volume1
Pagination1-6
Conference Date26-30/07/2009
PublisherIEEE
Conference LocationCalgary, Alberta, Canada
EditorIEEE
Type of WorkContributed oral presentation
ISSN Number1944-9925
ISBN Number978-1-4244-4241-6
Key Wordsresearch; stochastic programming; electricity markets; day-ahead market, bilateral contracts; Combined Cycle Units; optimal bid
AbstractThis paper developed a stochastic programming model that integrated the most recent regulation rules of the Spanish peninsular system for bilateral contracts in the dayahead optimal bid problem. Our model allows a price-taker generation company to decide the unit commitment of the thermal and combined cycle programming units, the economic dispatch of the BC between all the programming units and the optimal sale bid by observing the Spanish peninsular regulation. The model was solved using real data of a typical generation company and a set of scenarios for the Spanish market price. The results are reported and analyzed.
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DOI10.1109/PES.2009.5275680
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Improving electricity market price scenarios by means of forecasting factor models

Publication TypeConference Paper
Year of Publication2009
AuthorsM.-Pilar Muñoz; Cristina Corchero; F.-Javier Heredia
Conference NameThe 57th Session of the International Statistical Institute
Conference Date16-22/08/2009
PublisherInternational Statistical Institute
Conference LocationDurban, South Africa
Type of WorkPlenary session
Key Wordsresearch; spot price forecasting; scenario generation; MIBEL
AbstractIn liberalized electricity markets, Generation Companies must build an hourly bid that is sent to the market operator. The price at which the energy will be paid is unknown during the bidding process and has to be forecast. In this work we apply forecasting factor models to this framework and study its suitability.
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Improving electricity market price scenarios by means of forecasting factor models

Publication TypeReport
Year of Publication2009
AuthorsM.-Pilar Muñoz; Cristina Corchero; F.-Javier Heredia
Pages12
Date09/2009
ReferenceResearch Report DR 2009/06, Dept. of Statistics and Operations Research, E-Prints UPC http://hdl.handle.net/2117/3047. Universitat Politècnica de Catalunya.
Prepared forPlenary session on the 57th Session of the International Statistical Institute, Durban, South Africa. Accepted for publication at International Statistical Review.
CityBarcelona.
Key Wordsresearch; spot price forecasting; scenario generation; MIBEL
AbstractIn liberalized electricity markets, Generation Companies must build an hourly bid that is sent to the market operator. The price at which the energy will be paid is unknown during the bidding process and has to be forecast. In this work we apply forecasting factor models to this framework and study its suitability.
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Stochastic programming models for optimal bid strategies in the Iberian Electricity Market

Publication TypeConference Paper
Year of Publication2009
AuthorsF.-Javier Heredia; Cristina Corchero
Conference NameThe 20th International Symposium of Mathematical Programming (ISMP)
Conference Date23-28/08/2009
Conference LocationChicago
Type of WorkInvited oral presentation
Key Wordsresearch; stochastic programming; electricity markets; day-ahead market; bilateral contracts; futures contracts; optimal bid
AbstractThe day-ahead market is not only the main physical energy market of Portugal and Spain in terms of the amount of traded energy, but also the mechanism through which other energy products, as bilateral (BC) and physical futures contracts (FC), are integrated into the Iberian Electricity Market (MIBEL) energy production system. We propose stochastic programming models that give the optimal bidding and BC and FC nomination strategy for a price-taker generation company in the MIBEL. Implementation details and some first computational experiences for small real cases are presented.
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Estudi i optimització de l'oferta al Mercat Ibèric d'Electricitat (MIBEL)

Publication TypeTesis de Grau i Màster // BSc and MSc Thesis
Year of Publication2009
AuthorsSilvia Nieto; Iván Ruz
DirectorF.-Javier Heredia
Tipus de tesiTesi de Grau // BSC Thesis
TitulacióDiplomatura d'Estadística
CentreFacultat de Matemàtiques i Estadística, UPC
Data defensa09/07/2009
Nota // mark9.5 (over 10) E
Key Wordsteaching; PFC-DE; MIBEL; optimal bid; BSc Thesis
AbstractEstudi de les ofertes reals de les companyies productores d'energia elèctrica a MIBEL i comparació de dos models alternatius de optimització de l'oferta.
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Lectura de dos PFC's a la DE sobre oferta òptima als mercats d'energia elèctrica.

El passat dijous 9 de juliol de 2009 es va llegir el Projecte Final de Carrera dels alumnes Silvia Nieto i Ivan Ruz, que portava per títol "Estudi i optimització de l’oferta al Mercat Ibèric ’Electricitat (MIBEL)", dirigit pel professor Javier Heredia. Els objectius del treball han estat:


  • Fer una descriptiva de les dades obtingudes de les energies tèrmiques per veure el comportament que hi tenen.
  • Entendre el model d'optimització d'oferta presentat a l'article [1], i compendre la seva implementació.
  • Entendre el model d'optimització d'oferta de l'article [2] i resoldre una nova modelització adaptant aquest model a l'anterior fent els canvis pertinents.
  • Comparar els dos models i treure'n conclusions sobre quin és el més eficient.

Aquí teniu més informació.

[1] Arroyo, José M. ; Carrión, Miguel. A computationally efficient mixed-integer linear formulation for the termal unit commitment problem. Institute of Electrical and Electronics Engineers transactions on power systems, vol. 21, nº3, agost 2006.

[2] Cristina Corchero, F. Javier Heredia, "A Stochastic Programming Model for the Thermal Optimal Day-Ahead Bid Problem with Physical Futures Contracts", Submitted to European Journal of Operations Research, Barcelona, Espanya, Dept. of Statistics and Operations Research, Universitat Politècnica de Catalunya, 03/2009

 

A Stochastic Programming Model for the Thermal Optimal Day-Ahead Bid Problem with Physical Futures Contracts

Publication TypeReport
Year of Publication2009
AuthorsCristina Corchero; F. Javier Heredia
Pages19
Date03/2009
ReferenceResearch Report DR 2009/03, Dept. of Statistics and Operations Research, E-Prints UPC http://hdl.handle.net/2117/2795, Universitat Politècnica de Catalunya
Prepared forAccepted for publication at Computers and Operations Research
CityBarcelona, Spain.
Key Wordsresearch; Stochastic programming; OR in energy; electricity day-ahead market; futures contracts; optimal bid
AbstractThe 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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Optimal Bidding Strategies for Thermal and Generic Programming Units in the Day-ahead Electricity Market

Publication TypeReport
Year of Publication2008
AuthorsHeredia, F.-Javier, Rider, Marcos.-J., Corchero, C.
Pages12
Date11/2008
ReferenceResearch report DR 2008/13, Dept. of Statistics and Operations Research. E-Prints UPC, http://hdl.handle.net/2117/2468. Universitat Politècnica de Catalunya
Prepared forPublished on august 2010 at IEEE Transactions on Power Systems
Key Wordsresearch; stochastic programming; electricity markets; day-ahead market, bilateral contracts; Virtual Power Plants; optimal bid
AbstractThis paper develops a stochastic programming model that integrates the day-ahead optimal bidding problem with the most recent regulation rules of the Iberian Electricity Market (MIBEL) for bilateral contracts, with a special consideration for the new mechanism to balance the competition of the production market, namely virtual power plants auctions (VPP). The model allows a price-taker generation company to decide the unit commitment of the thermal units, the economic dispatch of the bilateral contracts between the thermal units and the generic programming unit (GPU) and the optimal sale/purchase bids for all units (thermal and generic) observing the MIBEL regulation. The uncertainty of the spot prices is represented through scenario sets built from the most recent real data using scenario reduction techniques. The model was solved with real data from a Spanish generation company and spot prices, and the results are reported and analyzed.
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A stochastic programming model for the optimal electricity market bid problem with bilateral contracts for thermal and CC units

HerediaRiderCorchero_EprintsUPC_08

This work, co-authored by Dr. Marcos.-J Rider and Ms. Cristina Corchero and submitted to the journal  Annals of Operations Research, developed a stochastic programming model that integrated the most recent regulation rules of the Spanish peninsular system for bilateral contracts in the day-ahead optimal bid problem. This model allows a price-taker generation company to decide the unit commitment of the thermal and combined cycle programming units, the economic dispatch of the bilateral contracts between all the programming units and the optimal sale bid by observing the Spanish peninsular regulation. See the full text at  http://hdl.handle.net/2117/2282

Optimal thermal and virtual power plants operation in the day-ahead electricity market.

Publication TypeConference Paper
Year of Publication2008
AuthorsF.-Javier Heredia; Marcos-J. Rider; Cristina Corchero
Conference NameAPMOD 2008 International Conference on Applied Mathematical Programming and Modelling
Series TitleAPMOD2008 CONFERENCE BOOK
Pagination21
Conference Date27-30/05/2008
Conference LocationComenius University, Bratislava, Slovak Republic
Type of WorkContributed presentation
Key Wordsstochastic programming; electricity markets; day-ahead market; bilateral contracts; Virtual Power Plant; Generic Programming Unit; MIBEL; modellization; research
AbstractThe new rules of the electrical energy production market operation of the Iberic Electricity Market MIBEL (mainland Spanish and Portuguese systems), for the diary and intra-diary market (July 2007), bring new challenges in the modeling and solution of the production market operation. Aiming to increase the proportion of electricity that is purchased through bilateral contracts with duration of several months and intending to stimulate liquidity in forward electricity markets, the Royal Decree 1634/2006, dated December 29th, 2006 imposes to Endesa and Iberdrola (the two dominant utility companies in the Spanish peninsular Markets) to hold a series of five auctions offering virtual power plant (VPP) capacity to any party who is a member of the MIBEL. Other experience of the application of VPP auctions can be seen in France, Belgium and Germany. In Spain, the VPP capacity means that the buyer of this product will have the capacity to generate MWh at his disposal. The buyer can exercise the right to produce against an exercise price that is set in advance, by paying an option premium. So although Endesa and Iberdrola still own the power plants, part of their capacity to produce will be at the disposal of the buyers of VPP. VPP capacity is represented by a set of hourly call options giving the buyer the right to nominate energy for delivery at a pre-defined exercise price. There will be baseload and peakload contracts with different exercise prices. The energy resulting from the exercise of the VPP options can be used by buyers in several ways: (a) national and international bilateral contracts prior to the day-ahead market; (b) bids to the day-ahead market and (c) national bilateral contracts after the day-ahead market. In order to operate the VPP options each buyer agent will have a Generic Unit (GU). This work develops an stochastic programming model for a Generation Company (GenCo) to find the optimal management of a VPP in the day-ahead electricity market under the most recent bilateral contracts regulation rules of MIBEL energy market.
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