electricity market

Forecasting and optimization of wind generation in energy markets

Publication TypeFunded research projects
Year of Publication2014
AuthorsF.- Javier Heredia; Ma. Pilar Muñoz; Josep Anton Sánchez; Maria Dolores Márquez; Eugenio Mijangos
Type of participationPrincipal Investigator (IP)
Duration01/2014-12/2016
CallPROGRAMA ESTATAL DE INVESTIGACIÓN, DESARROLLO E INNOVACIÓN ORIENTADA A LOS RETOS DE LA SOCIEDAD
Funding organizationMinistry of Economy and Competitivity, Government of Spain
PartnersUniversitat Politècnica de Catalunya; Universitat Autònoma de Barcelona (Catalonia) Euskal Herriko Unibersitatea (Basc Country) Universidad Pontificia de Comillas (Madrid) Universidade Paulista Júlia de Mesquita Filho (Brasil) North Carolina State University (USA) Electrical Utilities: Iberdrola, Gas Natural - Fenosa. Research centers: Catalonia Institute for Energy Research.
Full time researchers4,5
Budget49.000€
Project codeMTM2013-48462-C2-1-R
Key Wordsresearch; MTM2013-48462; forecasting, optimization, wind generation, energy markets; mineco; competitive; public; project; energy
Abstract

The coordinated project " Forecasting and Optimization of Wind Generation in Energy Markets" ( FOWGEM) aims at aplying a global approach to the problem of the optimal integration of the wind-enery generation of a generation company in the wholesale electricity market through the combination of statistical forecasting models, mathematical programming models for electricity markets and optimization algorithms. In the framework of the Spanish Strategy for Science and Technology and Innovation 2013-2020 this project contributes fundamentally to challenge 3, " safe, sustainable and clean energy ." Indeed, the forecasting and optimization models and procedures that will be developed in this project, are the necessary mechanisms to allow the competitive and safe integration of wind-energy generation in the multiple-markets based wholesale national energy production system. The FOWGEM project adopts an original and global approach to this problem that combines advanced methodologies in the area of statistics, mathematical modeling of energy markets and theoretical and computatitonal optimization that were developed in several previous projects of the Plan Nacional by the groups of the Universidad Politècnica de Catalunya and the Universidad Pontificia de Comillas . The main objecives of the project are:

  1. To develop forecasting models for wind-enregy generation and electricity prices for the spot and ancillary electricity markets as a base for the optimal planning of a generation companys production.
  2. To develop mathematical programming models for the optimal integration of wind-energy production of the generation companies in the wholesale spot and ancillary services electricity market based on the results of the forecasting models for the wind-energy generation and market prices.
  3. To develop and implement efficient optimization algorithms for the large scale mixed linear and quadratic programming problems arising in real instances of the models for the integration of wind-energy production.
Regarding the social and economic impact of this project, the predictive models for wind-energy generation and market prices, together with the optimization models for the optimal integration of the wind-energy, will indicate power companies how to optimally coordinate their dispatchable generation with the estocastic wind-energy generation. As a result, the expected cost of the total production will be minimized (which means less fossil fuel consumption with the consequent positive impact on the environment ) and also the wind-energy spillage will be minimized. From the point of view of scientific and technical impact , the main feature of this project is its global an multidiciplinar approach through a methodological cycle that combines statistical methods, mathematical modeling of electricity markets and optimization techniques, in order to tackle with an actual problem concerning generation companies with real impacts on the national economy and environment. It is to mention the collaboration as EPO of two of the major Spanish gneration companies, Gas Natural Fenosa and Iberdrola, together with  the Institute for Energy Research (IREC ), the major research institution in Catalonia in the field of energy.
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New research reports on energy markets and smartgrids.

The following three research reports on energy markets and smartgrids has been recently submitted for publication:

  • Residential microgrid (from Igualada et. al hdl.handle.net/2117/20642)Simona Sacripante, F.-Javier Heredia, Cristina Corchero, Stochastic optimal sale bid for a wind power producer,Research Report DR 2013/06 Dept. of Statistics and Operations Research. E-Prints UPC, Universitat Politècnica de Catalunya, 2013.
  • F.-Javier Heredia, Julian Cifuentes, Cristina Corchero, Stochastic optimal generation bid to electricity markets with emission risk constraints, Research Report DR 2013/05 Dept. of Statistics and Operations Research. E-Prints UPC, http://hdl.handle.net/2117/20640. Universitat Politècnica de Catalunya, 2013.
  • Lucia Igualada, Cristina Corchero, Miguel Cruz-Zambrano, F.-Javier Heredia, Optimal energy management for a residential microgrid including a vehicle-to-grid systemResearch Report DR 2013/04 Dept. of Statistics and Operations Research. E-Prints UPC, http://hdl.handle.net/2117/20642 . Universitat Politècnica de Catalunya, 2013.

Stochastic optimal sale bid for a wind power producer

Publication TypeReport
Year of Publication2013
AuthorsSimona Sacripante; F.-Javier Heredia; Cristina Corchero
Pages17
Date11/2013
ReferenceResearch report DR 2013/06, Dept. of Statistics and Operations Research. E-Prints UPC, Universitat Politècnica de Catalunya
Prepared forSubmitted
Key Wordsresearch; electricity markets; wind generator; stochastic programming
AbstractWind power generation has a key role in Spanish electricity system since it is a native source of energy that could help Spain to reduce its dependency on the exterior for the production of electricity. Apart from the great environmental benefits produced, wind energy reduce considerably spot energy price, reaching to cover 16,6 % of peninsular demand. Although, wind farms show high investment costs and need an efficient incentive scheme to be financed. If on one hand, Spain has been a leading country in Europe in developing a successful incentive scheme, nowadays tariff deficit and negative economic conjunctures asks for consistent reductions in the support mechanism and demand wind producers to be able to compete into the market with more mature technologies. The objective of this work is to find an optimal commercial strategy in the production market that would allow wind producer to maximize their daily profit. That can be achieved on one hand, increasing incomes in daily and intraday markets, on the other hand, reducing deviation costs due to error in generation predictions. We will previously analyze market features and common practices in use and then develop our own sale strategy solving a two-stage linear stochastic optimization problem. The first stage variable will be the sale bid in the day–ahead market while second stage variables will be the offers to the six sessions of intraday market. The model is implemented using real data from a wind producer leader in Spain.
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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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Improving Electricity Market Price Forecasting with Factor Models for the Optimal Generation Bid

Publication TypeJournal Article
Year of Publication2013
AuthorsM.Pilar Muñoz; Cristina Corchero; F.-Javier Heredia
Journal TitleInternational Statistical Review
Volume81
Issue2
Pages18 (289-306)
Start Page289
Journal DateAugust 2013
PublisherWiley
ISSN Number1751-5823
Key Wordsresearch; paper; electricity market prices; short-term forecasting; stochastic programming; factor models; price scenarios; Q2
AbstractIn liberalized electricity markets, the electricity generation companies usually manage their production by developing hourly bids that are sent to the day-ahead market. As the prices at which the energy will be purchased are unknown until the end of the bidding process, forecasting of spot prices has become an essential element in electricity management strategies. In this article, we apply forecasting factor models to the market framework in Spain and Portugal and study their performance. Although their goodness of fit is similar to that of autoregressive integrated moving average models, they are easier to implement. The second part of the paper uses the spot-price forecasting model to generate inputs for a stochastic programming model, which is then used to determine the company's optimal generation bid. The resulting optimal bidding curves are presented and analyzed in the context of the Iberian day-ahead electricity market.
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DOI10.1111/insr.12014
Preprinthttp://hdl.handle.net/2117/3047
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Stochastic optimal bid to electricity markets with environmental risk constraints

Publication TypeTesis de Grau i Màster // BSc and MSc Thesis
Year of Publication2012
AuthorsJulian Cifuentes Rubiano
DirectorF.-Javier Heredia
Tipus de tesiMSc Thesis
TitulacióMaster in Statistics and Operations Research
CentreFaculty of Mathematics and Statistics
Data defensa21/12/2012
Nota // mark9.5/10
Key Wordsteaching; stochastic programming; electricity markets; CO2 allowances; environment; emission limits; emission risk; CVaR; CEaR; modeling languages; MSc Thesis
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 to investigate 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 Iberian Electricity Market and the Spanish National Emissions and Allocation Plans are the framework to deal with the environmental issues in 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. 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, the environmental restrictions set by the EU Emission Trading Scheme, as well as the restrictions set by the Spanish National Emissions Reduction Plan. The economic implications for a GenCo of including the environmental restrictions of these National Plans are analyzed and the most remarkable results will be presented.. The problem to be solved in this project will provide generationutilities with a mathematical tool to find the individual optimal generation bid for each one of theirgeneration units that maximizes the long-run profits of the utility abiding by the Iberian ElectricityMarket rules, the environmental restrictions of the EU Emission Trading Scheme and also by theSpanish National Emissions Reduction Plan
DOI / handlehttp://hdl.handle.net/2099.1/17485
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Solving Electric Market Quadratic Problems by Branch and Fix Coordination Methods

Publication TypeProceedings Article
Year of Publication2013
AuthorsF. -Javier Heredia; Cristina Corchero; Eugenio Mijangos
Conference Name25th IFIP TC 7 Conference, CSMO 2011
Series TitleIFIP Advances in Information and Communication Technology
Volume391
Pagination511-520
Conference Start Date12/09/2011
PublisherSpringer Berlin Heidelberg
Conference LocationBerlin
ISSN Number1868-4238
ISBN Number978-3-642-36062-6
Key WordsLiberalized Electricity Market; Optimal Bid Stochastic Programming; Quadratic Branch-and-Fix Coordination; research; paper; DPI2008-02153
AbstractThe electric market regulation in Spain (MIBEL) establishes the rules for bilateral and futures 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 and futures 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. In order to gain computational efficiency, we use scenario clusters and propose to use perspective cuts. Numerical results are reported.
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DOI10.1007/978-3-642-36062-6_51
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Optimal Management of Microgrids

Publication TypeTesis de Grau i Màster // BSc and MSc Thesis
Year of Publication2012
AuthorsLucia Igualada González
DirectorF.-Javier Heredia; Cristina Corchero
Tipus de tesiTesi Final Màster // MSc Thesis
TitulacióMaster in Statistics and Operations Research
CentreFaculty of Mathematics and Statistics
Data defensa04/07/2012
Nota // mark10 MH // 10/10
Key Wordsresearch; teaching; smartgrids; microgrid; migrogrid central controller; electric vehicle; MSc Thesis
AbstractSmart grids and microgrids are the key in the near future where a decentralization of energy generation is expected. From the point of view of microgrid energy management, economic scheduling for generation devices, storage systems and loads is a crucial problem. Performance an optimization process is necessary to minimize the operating costs while several operational constraints are taken into account. Energy management is carried out by MCC (Microgrid Central Controller) in three steps: tertiary, secondary and primary controls. Tertiary control is executed one day-ahead and has two objectives. The first is an economic optimization using a program based on an Economic Dispatch and an Unit Commitment problem. The second objective is to improve the por tability of the supply and demand balance by interacting with the grid and taking advantage of the V2G (vehicle-to-grid) capability of the charging spot, and to generate a schedule over all components of the microgrid. The secondary control receives the scheduling plan created by tertiary control and taking into account current data, corrects the power outputs of generation units. Exchanged power with the grid and storage states of charge programmed by the tertiary control are ensured. This Energy Management System has been tested over different scenarios. One of them is based on a smart house with a photovoltaic module, a micro wind turbine and one electric vehicle charging spot. The other scenario is based on a large building where one micro gas turbine and one storage device have been added to the rest of units. After analysing the results, several conclusions have been deduced such as a change in curve of load and a lower cost for the user. Generally, the consumption over peak periods is decreased or is almost zero in some test cases, while the demand overnight is increased.
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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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