futures contracts

Stochastic optimal generation bid to electricity markets with emissions risk constraints.

Publication TypeJournal Article
Year of Publication2018
AuthorsF.-Javier Heredia; Julián Cifuentes-Rubiano; Cristina Corchero
Journal TitleJournal of Environmental Management
Volume207
Issue1
Pages12
Start Page432
Journal DateFebruary 2018
PublisherElsevier
ISSN Number0301-4797
Key Wordsresearch; OR in Energy; Stochastic Programming; Risk Management; Electricity market; Emissions reduction; paper
AbstractThere are many factors that influence the day-ahead market bidding strategies of a generation company (GenCo) within the framework of the current energy market. Environmental policy issues are giving rise to emission limitation that are becoming more and more important for fossil-fueled power plants, and these must be considered in their management. This work investigates the influence of the emissions reduction plan and the incorporation of the medium-term derivative commitments in the optimal generation bidding strategy for the day-ahead electricity market. Two different technologies have been considered: the high-emission technology of thermal coal units and the low-emission technology of combined cycle gas turbine units. The Iberian Electricity Market (MIBEL) and the Spanish National Emissions Reduction Plan (NERP) defines the environmental framework for dealing with the day-ahead market bidding strategies. To address emission limitations, we have extended some of the standard risk management methodologies developed for financial markets, such as Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR), thus leading to the new concept of Conditional Emission at Risk (CEaR). This study offers electricity generation utilities a mathematical model for determining the unit’s optimal generation bid to the wholesale electricity market such that it maximizes the long-term profits of the utility while allowing it to abide by the Iberian Electricity Market rules as well as the environmental restrictions set by the Spanish National Emissions Reduction Plan. We analyze the economic implications for a GenCo that includes the environmental restrictions of this National Plan as well as the NERP’s effects on the expected profits and the optimal generation bid.
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DOI10.1016/j.jenvman.2017.11.010
Preprinthttp://hdl.handle.net/2117/114024
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Parallel Proximal Bundle Methods for Stochastic Electricity Market Problems

Publication TypeConference Paper
Year of Publication2015
AuthorsF.-Javier Heredia; Antonio Rengifo
Conference Name27th European Conference on Operational Research
Conference Date12-15/07/2015
Conference LocationGlasgow, UK.
Type of Workinvited
Key Wordsresearch; MTM2013-48462-C2-1; mixed-integer nonlinear programming; proximal bundle methods; multimarket electricity problems; parallelism
AbstractThe use of stochastic programming to solve real instances of optimal bid problems in electricity market usually implies the solution of large scale mixed integer nonlinear optimization problems that can't be tackled with the available general purpose commercial optimisation software. In this work we show the potential of proximal bundle methods to solve large scale stochastic programming problems arising in electricity markets. Proximal bundle methods was used in the past to solve deterministic unit commitment problems and are extended in this work to solve real instances of stochastic optimal bid problems to the day-ahead market (with embedded unit commitment) with thousands of scenarios. A parallel implementation of the proximal bundle method has been developed to take profit of the separability of the lagrangean problem in as many subproblems as generation bid units. The parallel proximal bundle method (PPBM) is compared against general purpose commercial optimization software as well as against the perspective cuts algorithm, a method specially conceived to deal with quadratic objective function over semi-continuous domains. The reported numerical results obtained with a workstation with 32 threads show that the commercial software can’t find a solution beyond 50 scenarios and that the execution times of the proposed PPBM are as low as a 15% of the execution time of the perspective cut approach for problems beyond 800 scenarios.
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Stochastic Optimal Bid to Electricity Markets with Emission Risk Constraints

Publication TypeConference Paper
Year of Publication2014
AuthorsF.-Javier Heredia; Julián Cifuentes; Cristina Corchero
Conference NameIFORS2014: 20th Conference of the International Federation of Operational Research Societies
Conference Date13-18/07/2014
Conference LocationBarcelona
Type of WorkInvited presentation
Key Wordsresearch; emission limits; risk; stochastic programming; day-ahead electricity market; combined cycle units
AbstractThis work allows investigating the influence of the emission reduction plan, and the incorporation of the derivatives medium-term commitments in the optimal generation bidding strategy to the day-ahead electricity market. Two different technologies have been considered: the coal thermal units, high-emission technology, and the combined cycle gas turbine units, low-emission technology. The Iberian Electricity Market (MIBEL) and the Spanish National Emission Reduction Plan (NERP) defines the environmental framework to deal with by the day-ahead market bidding strategies. To address emission limitations, some of the standard risk management methodologies developed for financial markets, such as Value-at-Risk (VaR) and Conditional Valueat- Risk (CVaR), have been extended giving rise to the new concept of Conditional Emission at Risk (CEaR). The economic implications for a GenCo of including the environmental restrictions of this National Plan are analyzed, and the effect of the NERP in the expected profits and optimal generation bid are analyzed.
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Stochastic optimal generation bid to electricity markets with emission risk constraints.

Publication TypeReport
Year of Publication2013
AuthorsF.-Javier Heredia; Julian Cifuentes; Cristina Corchero
Pages21
Date09/2013
ReferenceResearch report DR 2013/04, Dept. of Statistics and Operations Research. E-Prints UPC, http://hdl.handle.net/2117/20640. Universitat Politècnica de Catalunya
Prepared forsubmitted
Key Wordsresearch; OR in Energy; Stochastic Programming; Risk Management; Electricity market; Emission reduction
AbstractThere are many factors that influence the day-ahead market bidding strategies of a generation company (GenCo) in the current energy market framework. Environmental policy issues have become more and more important for fossil-fuelled power plants and they have to be considered in their management, giving rise to emission limitations. This work allows investigating the influence of the emission reduction plan, and the incorporation of the derivatives medium-term commitments in the optimal generation bidding strategy to the day-ahead electricity market. Two different technologies have been considered: the coal thermal units, high-emission technology, and the combined cycle gas turbine units, low-emission technology. The Iberian Electricity Market (MIBEL) and the Spanish National Emission Reduction Plan (NERP) defines the environmental framework to deal with by the day-ahead market bidding strategies. To address emission limitations, some of the standard risk management methodologies developed for financial markets, such as Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR), have been extended giving rise to the new concept of Conditional Emission-at-Risk (CEaR). This study offers to electricity generation utilities a mathematical model to determinate the individual optimal generation bid to the wholesale electricity market, for each one of their generation units that maximizes the long-run profits of the utility abiding by the Iberian Electricity Market rules, as well as the environmental restrictions set by the Spanish National Emissions Reduction Plan. The economic implications for a GenCo of including the environmental restrictions of this National Plan are analyzed, and the effect of the NERP in the expected profits and optimal generation bid are analyzed.
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A new optimal electricity market bid model solved through perspective cuts

Publication TypeReport
Year of Publication2011
AuthorsCristina Corchero; Eugenio Mijangos; F.-Javier Heredia
Pages25
Date11/2011
ReferenceResearch report DR 2011/04, Dept. of Statistics and Operations Research. E-Prints UPC, http://hdl.handle.net/2117/18368. Universitat Politècnica de Catalunya
Prepared forPublished by TOP
Key Wordsresearch; electricity market;
AbstractOn current electricity markets the electrical utilities are faced with very sophisticated decision making problems under uncertainty. Moreover, when focusing in the shortterm management, generation companies must include some medium-term products that directly influence their short-term strategies. In this work, the bilateral and physical futures contracts are included into the day-ahead market bid following MIBEL rules and a stochastic quadratic mixed-integer programming model is presented. The complexity of this stochastic programming problem makes unpractical the resolution of large-scale instances with general purpose optimization codes. Therefore, in order to gain efficiency, a polyhedral outer approximation of the quadratic objective function obtained by means of perspective cuts (PC) is proposed. A set of instances of the problem has been defined with real data and solved with the PC methodology. The numerical results obtained show the efficiency of this methodology compared with standard mixed quadratic optimization solvers.
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Optimal electricity market bidding strategies considering emission allowances

Publication TypeProceedings Article
Year of Publication2012
AuthorsCristina Corchero; F.-Javier Heredia; Julián Cifuentes
Conference Name2012 9th International Conference on the European Energy Market (EEM 2012)
Series TitleIEEE Conference Publications
Pagination1-8
Conference Start Date10/05/2012
PublisherIEEE
Conference LocationFlorence
EditorIEEE
ISSN Number-
ISBN Number978-1-4673-0834-2
Key Wordsresearch; elecriticy; markets; CO2 allowances; emissions limits; environment; stochastic programming; modeling languages; paper
AbstractThere are many factors that influence the day-ahead market bidding strategies of a GenCo in the current energy market framework. In this work we study the influence of both the allowances and emission reduction plan and the incorporation of the derivatives medium-term commitments in the optimal generation bidding strategy to the day-ahead electricity market. Two different technologies have been considered: the coal thermal units, high-emission technology, and the combined cycle gas turbine units, low-emission technology. The operational characteristics of both kinds of units are modeled in detail. We deal with this problem in the framework of the Iberian Electricity Market and the Spanish National Emissions and Allocation Plans. The economic implications for a GenCo of including the environmental restrictions of these National Plans are analyzed.
URLClick Here
DOI10.1109/EEM.2012.6254676
Preprinthttp://hdl.handle.net/2117/18691
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A new optimal electricity market bid model solved through perspective cuts

Publication TypeJournal Article
Year of Publication2013
AuthorsCristina Corchero; Eugenio Mijangos; F.-Javier Heredia
Journal TitleTOP
Volume21
Issue1
Pages25
Start Page84
Journal Date04/2013
Short TitleA new optimal electricity market bid model
PublisherSpringer
ISSN Number1134-5764
Key Wordsresearch; paper; electricity market; day-ahead; bilateral contracts; future contracts; Optimal bid; Stochastic programming; Perspective cuts; mixed integer nonlinear programming; DPI2008-02153; Q3
AbstractOn current electricity markets the electrical utilities are faced with very sophisticated decision making problems under uncertainty. Moreover, when focusing in the short-term management, generation companies must include some medium-term products that directly influence their short-term strategies. In this work, the bilateral and physical futures contracts are included into the day-ahead market bid following MIBEL rules and a stochastic quadratic mixed-integer programming model is presented. The complexity of this stochastic programming problem makes unpractical the resolution of large-scale instances with general-purpose optimization codes. Therefore, in order to gain efficiency, a polyhedral outer approximation of the quadratic objective function obtained by means of perspective cuts (PC) is proposed. A set of instances of the problem has been defined with real data and solved with the PC methodology. The numerical results obtained show the efficiency of this methodology compared with standard mixed quadratic optimization solvers.
URLClick Here
DOI10.1007/s11750-011-0240-6
Preprinthttp://hdl.handle.net/2117/18368
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A multistage stochastic programming model for the optimal multimarket electricity bid problem

Publication TypeConference Paper
Year of Publication2011
AuthorsF.-Javier Heredia; Cristina Corchero
Conference NameOptimization, Theory, Algorithms and Applications in Economics (OPT 2011)
Conference Date24-28/10/2011
Conference LocationCentre de Recerca Matemàtica. Barcelona, Spain.
Type of WorkInvited presentation
Key Wordsresearch; optimal bid; day-ahead electricity market; multimarket; perspective cuts; bilateral contracts; futures contracts; stochastic programming; DPI2008-02153
AbstractShort-term electricity market is made up of a sequence of markets, that is, it is a multimarket enviroment. In the case of the Iberian Energy Market the sequence of major short-term electricity markets are the day-ahead market, the ancillary service market or secondary reserve market (henceforth reserve market), and a set of six intraday markets. Generation Companies (GenCos) that participate in the electricity market could increase their benefits by jointly optimizing their participation in this sequence of electricity markets. This work proposes a stochastic programming model that gives the GenCo the optimal bidding strategy for the day-ahead market (DAM), which considers the benefits and costs of participating in the subsequent markets and which includes both physical futures contracts and bilateral contracts. Numerical results are reported and discussed.
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25th IFIP TC7 Conference on System Modeling and Optimization

 The International Federation for Information Processing Technical Committee 7 - System Modeling and Optimization - arranges in a cycle of two years highly regarded conferences to several topics of Applied Optimization such as  Optimal Control of Ordinary and Partial Differential Equations, Modeling and Simulation, Nonlinear, Discrete, and Stochastic Optimization and Industrial Applications. This year the conference was celebrated in the Berlin Institute of Technology, and I participated with a contributed talk entitled "Solving electric market quadratic problems by Branch and Fix Coordination methods "

Solving electricity market quadratic problems by Branch and Fix Coordination methods

Publication TypeConference Paper
Year of Publication2011
AuthorsF.-Javier Heredia; Cristina Corchero; Eugenio Mijangos
Conference Name25th IFIP TC7 Conference on System Modeling and Optimization
Conference Date12-16/09/2011
Conference LocationBerlin
Type of Workcontributed presentation
Key Wordsresearch; optimal bid; day-ahead electricity market; branch and fix coordination; perspective cuts; bilateral contracts; futures contracts; stochastic programming
AbstractThe electric market regulation in Spain (MIBEL) establishes the rules for bilateral contracts in the day-ahead optimal bid problem. Our 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 optimal sale bids for the thermal units observing the MIBEL regulation. The uncertainty of the spot prices is represented through scenario sets. We solve this model on the framework of the Branch and Fix Coordination metodology as a quadratic, two-stage stochastic problem. Numerical results are reported.
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