modeling languages

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.
URLClick Here
ExportTagged XML BibTex

A multi-objective approach to infrastructure planning in the early stages of EV introduction

Publication TypeTesis de Grau i Màster // BSc and MSc Thesis
Year of Publication2014
AuthorsAndina Rosalia Brown
DirectorF.-Javier Heredia; Cristina Corchero
Tipus de tesiMSc Thesis
TitulacióMaster in Statistics and Operations Research
CentreFaculty of Mathematics and Statistics
Data defensa27/01/2014
Nota // mark9.0
Key WordsMulti-objective Optimisation; Facility Location; Electric Vehicle; Fast Charging Stations; MSc Thesis
AbstractThis study approaches the problem from the perspective of a central planner wishing to install fast charging stations. A multi-objective approach is used to simultaneously consider two conflicting objectives in the optimisation problem. The first objective is to minimise the distance that potential consumers would need to deviate from their normal journeys in order to reach their nearest fast charging station, and thus minimise the associated inconvenience. The second objective is to minimise the set up costs associated with the installation of the stations, which differ according to the number of facilities installed and their location. These objectives are normalised using a function transformation and then combined into a single objective function. A mathematical model is formulated and implemented using GAMS to obtain results for the case study of Barcelona, building on the existing literature. Using the weighted sums method, multiple Pareto optimal solutions are found by solving for different relative weights combinations applied to the two objectives. These solutions are used to depict the Pareto front, offering insight into the nature of the trade-offs between the objectives and aiding the decision making process. This study develops the existing methodology used for the EV infrastructure problem, and shows how the application of a multi-objective formulation can offer useful insight to decision makers, particularly when preferences are unclear a priori.
DOI / handlehttp://hdl.handle.net/2099.1/20851
URLClick Here
ExportTagged XML BibTex

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.
URLClick Here
ExportTagged XML BibTex

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.
ExportTagged XML BibTex

Optimal sizing of microgrids: a fast charging station case

Publication TypeProceedings Article
Year of Publication2012
AuthorsCristina Corchero; M. Cruz; F.-Javier Heredia; J.-I. Cairo; L. Igualada; A. Romero
Conference Name2012 9th International Conference on the European Energy Market (EEM 2012)
Series TitleIEEE Conference Publications
Pagination1-6
Conference Start Date10/05/2012
PublisherIEEE
Conference LocationFlorence, Italy
EditorIEEE
ISBN Number978-1-4673-0834-2
Key Wordsresearch; electrical vehicle; smartgrids; charging station; microgrid; queuing system; paper
AbstractIn this work we focus on the optimal design of electric vehicle charging stations. We consider investment, operational costs, physical constraints and different electricity pricing strategies. The size of the various components in the microgrid architecture and the suitability of the storage system are analysed. The electric vehicle charging demand is modelled through a queuing system.
URLClick Here
DOI10.1109/EEM.2012.6254677
ExportTagged XML BibTex

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
ExportTagged XML BibTex

Optimal electricity market bidding strategies considering emission allowances

Publication TypeConference Paper
Year of Publication2012
AuthorsCristina Corchero; F.-Javier Heredia; Julián Cifuentes
Conference Name9th International Conference on the European Energy Market (EEM12)
Conference Date10-12/05/2012
Conference LocationFlorence, Italy
Type of WorkContributed presentation
Key Wordsresearch; elecriticy; markets; CO2 allowances; emissions limits; environment; stochastic programming; modeling languages
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
ExportTagged XML BibTex

Optimal sale bid for a wind producer in Spanish electricity market

Publication TypeTesis de Grau i Màster // BSc and MSc Thesis
Year of Publication2011
AuthorsSimona Sacripante
DirectorF.-Javier Heredia
Tipus de tesiMSc Thesis
TitulacióMaster in Statistics and Operations Research
CentreFaculty of Mathematics and Statistics
Data defensa10/11/2011
Nota // mark9 / 10
Key Wordsteaching; renewebable energy; electricity market; optimal bid; wind generators; wind; intraday market; wind producer; MSc Thesis
AbstractThe 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 day-ahead and intraday markets, on the other hand, reducing deviation costs due to error in generation predictions.
DOI / handlehttp://hdl.handle.net/2099.1/13914
URLClick Here
ExportTagged XML BibTex

Management Science Optimization Modeling with SAS/OR

 Els próxims dies 12, 13 i 14 de juliol participaré al V Summer School del Màster Interuniversitari d'Estadística i Investigació Operativa UP/UB impartint el curs  Management Science Optimization Modeling with SAS/OR , en col·laboració amb la professora Crisitina Corchero, investigadora de l'IREC i GNOM. Els objectius del curs son:

"This course is focused on the possibilities of the SAS/OR package to implement and solve some optimization models that are in the core of the so called Analytic Consulting which represents the application of the MS methodology to the consulting Activity. Although commonly considered as software for data management, SAS also includes through his SAS/OR package (OR for Operations Research) a broad list of procedures to implement and solve any kind of optimization problems. The course will give basic skills to the participants for the efficiency formulation, implementation, solution and analysis of several management science optimization problems with SAS/OR."

Podeu consultar els detalls del curs en aquest enllaç .

Efficient Solution of Optimal Multimarket Electricity Bid Models

Publication TypeProceedings Article
Year of Publication2011
AuthorsCristina Corchero; F.-Javier Heredia; Eugenio Mijangos
Conference Name8th International Conference on the European Energy Market (EEM11)
Series TitleTo be published in the IEEEXplore
Pagination244-249
Conference Start Date25/05/2011
PublisherInstitute of Electrical and Electronics Engineers, Inc.
Conference LocationZagreb, Croatia
EditorMarko Delimar
ISBN Number978-1-61284-286-8/11
Key Wordsspot electricity markets; financial electricity markets; Iberian Electricity Market; stochastic programming; perspective cuts; research; DPI2008-02153; paper
AbstractShort-term electricity market is made up of a sequence of markets, that is, it is a multimarket enviroment. In the case of the Iberian Energy Market the sequence of major short-term electricity markets are the day-ahead market, the ancillary service market or secondary reserve market (henceforth reserve market), and a set of six intraday markets. Generation Companies (GenCos) that participate in the electricity market could increase their benefits by jointly optimizing their participation in this sequence of electricity markets. This work proposes a stochastic programming model that gives the GenCo the optimal bidding strategy for the day-ahead market (DAM), which considers the benefits and costs of participating in the subsequent markets and which includes both physical futures contracts and bilateral contracts.
URLClick Here
DOI10.1109/EEM.2011.5953017
ExportTagged XML BibTex
Syndicate content