stochastic programming

A stochastic programming model for the tertiary control of microgrids

Publication TypeProceedings Article
Year of Publication2015
AuthorsLeire Citores; Cristina Corchero; F.-Javier Heredia
Conference Name12th International Conference on the European Energy Market (EEM15)
Pagination1-6
Conference Start Date19-22/05/2015
PublisherIEEE
Conference LocationLisbon, Portugal.
ISBN Number978-1-4673-6691-5
Key WordsMicrogrids; Optimization; Production; Stochastic processes; Uncertainty; Wind power generation; Wind speed; energy system optimization; microgrid; scenario generation; stochastic programming; paper; research
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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DOI10.1109/EEM.2015.7216761
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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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Contribution to the 27th European Conference on Operational Research


EURO2015The 27th European Conference on Operational Research  was held in Glasgow, hosted by the University of Strathclyde, during 12-15 July 2015. I participated in the sessions with the following two works:

The first one, Parallel Proximal Bundle Methods for Stochastic Electricity Market Problems  in collaboration with Mr. Antonio Rengifo, a former student of our Master in Statistics and Operations Research.

The second one, entitled A multi-objective approach to infrastructure planning in the early stages of EV introduction  in collaboration with the Energy Economy group of the Catalonia Institute for Energy Reseach.

In the photography, me (right) with two of the coauthors of the last paper, Dr. Cristina Corchero (left) and Ms. Andina Brown (center).

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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Visit of prof. Eugenio Mijangos to UPC-BarcelonaTech

 Professor Eugenio Mijangos was visiting prof. F.-Javier Heredia at the UPC-BarcelonaTech research gropu GNOM during November 27 to 28 to start-up the tasks related with the research project FOWGEM . As a result, they are going to undertake the application of the implementation of the BFC algorithm developped by professor Mijangos to solve the multistage stochastic programming model for the multimarket optimal generation bid formulated by prof. Heredia and Dr. Corchero described in the work Efficient solution of optimal multimarket electricity bid models (Corchero, Heredia, Mijangos, DOI: 10.1109/EEM.2011.5953017). This is a previous step for the resolution of the IOGET model.

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

 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

    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

    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

    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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