energy and power systems

Participation in the 12th International Conference on the European Energy Market

 The International Conference on the European Energy Market  is the premier forum for the exchange of ideas and to discuss the development of the energy markets in Europe. It has achieved a huge success during the past eleven editions covering the electricity and gas markets policies and experiences, climate change impacts on the sector and developments at the European level. In 2015, the EEM was hosted by ISEL - Instituto Superior de Engenharia de Lisboa in cooperation with the Technical University of Lodz. I contributed to this conference with the presentation of the following two works:

A stochastic programming model for the tertiary control of microgrids

Publication TypeConference Paper
Year of Publication2015
AuthorsLeire Citores; Cristina Corchero; F.-Javier Heredia
Conference Name12th International Conference on the European Energy Market
Conference Date19-22/05/2015
Conference LocationLisbon, Portugal
Type of Workcontributed presentation
Key Wordsresearch; MTM2013-48462-C2-1; microgrid; stochastic programming; scenario generation; wind power
AbstractIn this work a scenario-based two-stage stochastic programming model is proposed to solve a microgrid’s tertiary control optimization problem taking into account some renewable energy resource’s uncertainty as well as uncertain energy deviation prices in the electricity market. Scenario generation methods for wind speed realizations are also studied. Results show that the introduction of stochastic programming represents a significant improvement over a deterministic model.
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Economic analysis of battery electric storage systems operating in electricity markets

Publication TypeConference Paper
Year of Publication2015
AuthorsF.-Javier Heredia; Jordi Riera; Montserrat Mata; Joan Escuer; Jordi Romeu
Conference Name12th International Conference on the European Energy Market
Conference Date19-22/05/2015
Conference LocationLisbon, Portugal
Type of Workcontributed presentation
Key Wordsresearch; MTM2013-48462-C2-1; battery electricity storage systems; electricity markets; day-ahead market; secondary reserve market; SAS/OR; wind power plants; energy economy; virtual power plant
AbstractBattery electric storage systems (BESS) in the range of 1-10 MWh is a key technology allowing a more efficient operation of small electricity market producer. The aim of this work is to assess the economic viability of Li-ion based BESS systems for small electricity producers. The results of the ex-post economic analysis performed with real data from the Iberian Electricity Market shows the economic viability of a Li-ion based BESS thanks to the optimal operation in day-ahead and ancillary electricity markets.
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Participation in the 20th Conference of the International Federation of Operational Research Societies (IFORS2014)

 On July 2014 Barcelona hosted the 20th Conference of the International Federation of Operational Research Societies (IFORS2014), one the most important meetings of the international OR community. The 20th edition of this conference was organized by the OR community in the different universities of Catalonia, under the leadership of prof. Elena Fernández, from the UNiversitat Politècnica de Catalunya-BarcelonaTech. I had the opportunity to contribute to this event as a member of the Organizing Committee as well as organizing a very successfull stream on Optimization Models and Algorithms in Energy Industry (28 contributions), together with my friend and colleague Dr. Cristina Corchero (Catalonian Institute for Energy Research, IREC). I also presented the work Stochastic Optimal Bid to Electricity Markets with Emission Risk Constraints, co-authored with Julián Cifuentes , a former student of the Master in Statistics and Operations Research, and Dr. Cristina Corchero.

Optimal Energy Management for a Residential Microgrid Including a Vehicle-to-Grid System

Publication TypeJournal Article
Year of Publication2014
AuthorsLucia Igualada; Cristina Corchero; Miguel Cruz; F-.Javier Heredia
Journal TitleIEEE Transactions on Smart Grid
Volume5
Issue4
Pages2163-2172
Journal Date07/2014
PublisherIEEE
ISSN Number1949-3053
Key Wordsresearch; paper; smart grids; vehicle- to-grid (V2G); renewable generation; microgrids; smartgrids; modeling
AbstractAn optimization model is proposed to manage a residential microgrid including a charging spot with a vehicle-to-grid system and renewable energy sources. In order to achieve a realistic and convenient management, we take into account: (1) the household load split into three different profiles depending on the characteristics of the elements considered; (2) a realistic approach to owner behavior by introducing the novel concept of range anxiety; (3) the vehicle battery management considering the mobility profile of the owner and (4) different domestic renewable energy sources. We consider the microgrid operated in grid-connected mode. The model is executed one-day-ahead and generates a schedule for all components of the microgrid. The results obtained show daily costs in the range of 2.82 to 3.33 ; the proximity of these values to the actual energy costs for Spanish households validate the modeling. The experimental results of applying the designed managing strategies show daily costs savings of nearly 10%.
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DOI10.1109/TSG.2014.2318836
Preprinthttp://hdl.handle.net/2117/20642
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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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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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