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Two new master thesis on optimal operation of microgrids in electricity markets.

Thu, 11/27/2014 - 16:52 — admin

Wind rose diagram ((c) Leire Citores)On June 2014 two new Master Thesis of the Master of Statistcs and Operations Research UPC-UB   was presented   

  • A stochastic programming model for the tertiary control of microgrids by Ms. Leire Cítores.
  • Energy Management System para una microrred domestica con participación en los servicios auxiliares de red by Ms. Irune Etxarri.

    • Dr. Cristina Corchero (IREC) and professor F.-Javier Heredia (GNOM) were the advisors of these two works developped at the facilities of the Catalonia Institute for Energy Research (IREC).

    A stochastic programming model for the tertiary control of microgrids

    Thu, 11/27/2014 - 16:48 — admin
    Publication TypeTesis de Grau i Màster // BSc and MSc Thesis
    Year of Publication2014
    AuthorsLeire Citores
    DirectorF.-Javier Heredia, Cristina Corchero
    Tipus de tesiMSc Thesis
    TitulacióMaster in Statistics and Operations research
    CentreFaculty of Mathematics and Statistics
    Data defensa27/06/2014
    Nota // mark10 MH (A with Honours)
    Key Wordsresearch; teaching; microgrids, stochastic programming; scenario generation; wind generation; day-ahead electricity market; imbalances; MSc Thesis
    AbstractIn this thesis 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 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 an improvement over a deterministic model.
    DOI / handlehttp://hdl.handle.net/2099.1/23235
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    Energy Management System para una microrred domestica con participación en los servicios auxiliares de red

    Thu, 11/27/2014 - 16:32 — admin
    Publication TypeTesis de Grau i Màster // BSc and MSc Thesis
    Year of Publication2014
    AuthorsIrune Etxarri Urtasun
    DirectorF.-Javier Heredia, Cristina Corchero
    Tipus de tesiMSc Thesis
    TitulacióMaster in Statistics and Operations Reseafrch
    CentreFaculty of Mathematics and Statistics
    Data defensa27/06/2014
    Nota // mark**
    Key Wordsteaching; research; microgrids; stochastic programming; electricity market; secondary reserve; MSc Thesis
    AbstractEn este proyecto se ha propuesto un modelo estocástico de dos etapas para la gestión de energía en una microrred doméstica, introduciendo la participación en el mercado de banda de regulación. El objetivo del modelo es determinar la potencia que se oferta al mercado diario, teniendo en cuenta la participación en el mercado de banda de regulación. Se ha introducido estocasticidad en los precios de este mercado y en los precios y probabilidades del requerimiento a subir y a bajar de la energía de regulación secundaria. Se han comparado los beneficios de la microrred en caso de participar o no en el mercado de banda de regulación, y se ha visto que la participación en dicho mercado produce grandes beneficios para sus usuarios.
    DOI / handlehttp://hdl.handle.net/2099.1/23233
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    Forecasting and optimization of wind generation in energy markets

    Sat, 07/19/2014 - 11:53 — admin
    Publication TypeFunded research projects
    Year of Publication2014
    AuthorsF.- Javier Heredia; Ma. Pilar Muñoz; Josep Anton Sánchez; Maria Dolores Márquez; Eugenio Mijangos; Marlyn Dayana Cuadrado Guevara
    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.

    Fri, 01/24/2014 - 10:18 — admin
    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 system, Research 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

    Sun, 11/24/2013 - 19:02 — admin
    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.

    Sun, 11/17/2013 - 19:22 — admin
    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

    Fri, 09/06/2013 - 15:58 — admin
    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

    Fri, 09/06/2013 - 14:58 — admin
    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.
    URLClick Here
    DOI10.1111/insr.12014
    Preprinthttp://hdl.handle.net/2117/3047
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    Stochastic optimal bid to electricity markets with environmental risk constraints

    Wed, 03/27/2013 - 11:21 — admin
    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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