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Energy Management System para una microrred domestica con participación en los servicios auxiliares de red

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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A new paper published in IEEE Transactions on Smart Grids

ie3sgThe paper Optimal Energy Management for a Residential Microgrid Including Vehicle-to-Grid System has been published in IEEE Transactions on Smart Grids. This work, done in collaboration with the Energy Economics group of the Catalonian Institute for Energy Research (IREC), proposes an optimization model to manage a residential microgrid including a charging spot with a vehicle-to-grid system and renewable energy sources. A preprint version of the paper can be downloaded from http://hdl.handle.net/2117/20642

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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New national-funded research project

Wind farmThe research project Forecasting and optimization of wind generation in energy markets (FOWGEM) has been accepted for granting by the Spanish's National Program of R+D+i for the Challenges of the Society. This is a project coordinated by the Universitat Politècnica de Catalunya (the project leaders are prof. Ma. Pilar Muñoz and prof. F.-Javier Heredia) in collaboration with the Universidad Pontificia de Comillas (where the leader is leader prof. Andrés Ramos). Besides these two universities, several other universities and electrical utilities from Spain and abroad participate in the project: 

  • Universities: Universitat Autònoma de Barcelona (Catalonia, Spain); Euskal Herriko Unibersitatea (Basc Country, Spain); Universidade Paulista Júlia de Mesquita Filho (Brasil); North Carolina State University (USA).
  • Electrical Utilities and research centers: Iberdrola, Gas Natural - Fenosa, Catalonia Institute for Energy Research
Project 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 advanced large-scale optimization algorithms.

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; 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.

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.

Optimal energy management for a residential microgrid including a vehicle-to-grid system

Publication TypeReport
Year of Publication2013
AuthorsLucía Igualada; Cristina Corchero; Miguel Cruz-Zambrano; F.-Javier Heredia
Pages9
Date11/2013
ReferenceResearch report DR 2013/05, Dept. of Statistics and Operations Research. E-Prints UPC, http://hdl.handle.net/2117/20642. Universitat Politècnica de Catalunya
Prepared forPublished at IEEE Transactions on Smart Grids (DOI: 10.1109/TSG.2014.2318836)
Key Wordsresearch; optimal management; smart grids; vehicle-to-grid; renewable generation; microgrids
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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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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New paper published in the International Statistical Review.

 The paper Improving Electricity Market Price Forecasting with Factor Models for the Optimal Generation Bid has been recently published in the journal International Statistical Review (preprint available at http://hdl.handle.net/2117/3047 ).  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. This work is a partial result of the tasks developped in the research project DPI2008-02153 of the MINECO.

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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