spot price forecasting

Multistage Scenario Trees Generation for Renewable Energy Systems Optimization

Publication TypeThesis
Year of Publication2020
AuthorsMarlyn Dayana Cuadrado Guevara
Academic DepartmentDept. of Statistics and Operations Research. Prof. F.-Javier Heredia, advisor.
Number of Pages194
UniversityUniversitat Politècnica de Catalunya-BarcelonaTech
CityBarcelona
DegreePhD Thesis
Key Wordsresearch; Battery energy storage systems; Electricity markets; Ancillary services market; Wind power generation; Virtual power plants; Multistage Stochastic programming; phd thesis
AbstractThe presence of renewables in energy systems optimization have generated a high level of uncertainty in the data, which has led to a need for applying stochastic optimization to modelling problems with this characteristic. The method followed in this thesis is Multistage Stochastic Programming (MSP). Central to MSP is the idea of representing uncertainty (which, in this case, is modelled with a stochastic process) using scenario trees. In this thesis, we developed a methodology that starts with available historical data; generates a set of scenarios for each random variable of the MSP model; defines individual scenarios that are used to build the initial stochastic process (as a fan or an initial scenario tree); and builds the final scenario trees that are the approximation of the stochastic process.
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A Multistage Stochastic Programming Model for the Optimal Bid of Wind-BESS Virtual Power Plants to Electricity Markets

Publication TypeConference Paper
Year of Publication2017
AuthorsF.-Javier Heredia; Marlyn D. Cuadrado; J.-Anton Sánchez
Conference Name4th International Conference on Optimization Methods and Software 2017
Conference Date16-21/12/2017
Conference LocationLa Havana
Type of WorkInvited presentation
Key Wordsmultistage; VSS; wind-BESS VPP; wind power; energy storage; battery; research
AbstractOne of the objectives of the FOWGEN project (https://fowgem.upc.edu) was to study the economic feasibility and optimal operation of a wind-BESS Virtual Power Plant (VPP): In [1] an ex-post economic analysis shows the economic viability of a wind-BESS VPP thanks to the optimal operation in day-ahead and ancillary electricity markets; In [2] a new multi-stage stochastic programming model (WBVPP)for the optimal bid of a wind producer both in spot and ancillary services electricity markets is developed. The work presented here extends the study in [2] with a new methodology to treat the uncertainty, based in forecasting models, and the study of the quality of the stochastic solution. [1] F-Javier Heredia et al. Economic analysis of battery electric storage systems operating in electricity markets 12th International Conference on the European Energy Market (EEM15), 2015 DOI: 10.1109/EEM.2015.7216739. [2] F-Javier Heredia et al. On optimal participation in the electricity markets of wind power plants with battery energy storage system. Submitted, under second revision. 2017.
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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
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
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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Improving electricity market price scenarios by means of forecasting factor models

Publication TypeProceedings Article
Year of Publication2009
AuthorsM.Pilar Muñoz; Cristina Corchero; F.-Javier Heredia
Conference Name57^th Session of the International Statistical Institute
Key Wordsresearch; DPI2008-02153; electricity markets; TSFA; spot price scenarios; paper
AbstractIn liberalized electricity markets, Generation Companies must build an hourly bid that is sent to the market operator. The price at which the energy will be paid is unknown during the bidding process and has to be forecast. In this work we apply forecasting factor models to this framework and study its suitability.
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DOIhttp://hdl.handle.net/2117/3047
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Electricity Market Optimization: finding the best bid through stochastic programming.

Publication TypeConference Paper
Year of Publication2010
AuthorsF.-Javier Heredia; Cristina Corchero; M.-Pilar Muñoz; Eugenio Mijangos
Conference NameConference on Numerical Optimization and Applications in Engineering (NUMOPEN-2010)
Conference Date13-15/10/2010
Conference LocationCentre de Recerca Matemàtica. UAB. Barcelona, Spain.
Type of WorkInvited presentation
Key Wordsresearch; electricity markets; stochastic programming; perspective cuts; TSFA; DPI2008-02153
AbstractThe participation in national and international electricity markets has became a very complex decision making process. Electrical utilities participating in such liberalized market have to decide daily the operation, generation scheduling and optimal bid of each one of their generation units in several consecutives day-ahead markets. In the talk, we will describe the operation rules of the Iberian Electricity Market (MIBEL), how this operation can be mathematically modelled with the help of stochastic programming into large scale nonlinear integer problems and how these difficult optimization problems can be solved with specialised algorithms. Finally, the results found for several cases with real data of Spanish utilities and MIBEL market prices will be shown.
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Optimal day-ahead bidding strategy with futures and bilateral contracts. Scenario generation through factor models

Publication TypeConference Paper
Year of Publication2010
AuthorsCristina Corchero; F.-Javier Heredia; M.-Pilar Muñoz
Conference Name24th European Conference on Operational Research
Conference Date11-14/07/2010
Conference LocationLisboa
Type of WorkInvited Presentation
Key Wordsresearch; electrical markets; stochastic programming; forecasting
AbstractWe propose a stochastic programming model that gives the optimal bidding, bilateral (BC) and futures contracts (FC) nomination strategy for a price-taker generation company in the MIBEL. The objective of the study is to decide the optimal economic dispatch of the physical FC and BC among the thermal units, the optimal bidding at day-ahead market (DAM) abiding by the MIBEL rules and the optimal unit commitment that maximizes the expected profits from the DAM. For the uncertainty characterization, we apply the methodology of factors models to forecast market prices in a short-term horizon.
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Optimal Bidding Strategies for Thermal and Generic Programming Units in the Day-Ahead Electricity Market

Publication TypeJournal Article
Year of Publication2010
AuthorsHeredia, F.-J; Rider, M.-Julio; Corchero, C.
Journal TitleIEEE Transactions on Power Systems
Volume25
Issue3
Pages1504-1518
Start Page1504
Journal DateAug. 2010
PublisherIEEE Power & Energy Society
ISSN Number0885-8950
Key Wordsresearch; paper; bilateral contracts; electricity spot market; optimal bidding strategies; short-term electricity generation planning; stochastic programming; virtual power plant auctions
AbstractThis study has developed a stochastic programming model that integrates the day-ahead optimal bidding problem with the most recent regulation rules of the Iberian Electricity Market (MIBEL) for bilateral contracts (BC), with a special consideration for the new mechanism to balance the competition of the production market, namely virtual power plant (VPP) auctions. The model allows a price-taking generation company (GenCo) to decide on the unit commitment of the thermal units, the economic dispatch of the BCs between the thermal units and the generic programming unit (GPU), and the optimal sale/purchase bids for all units (thermal and generic), by observing the MIBEL regulation. The uncertainty of the spot prices has been represented through scenario sets built from the most recent real data using scenario reduction techniques. The model has been solved using real data from a Spanish generation company and spot prices, and the results have been reported and analyzed.
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DOI10.1109/TPWRS.2009.2038269
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Improving electricity market price scenarios by means of forecasting factor models

Publication TypeConference Paper
Year of Publication2009
AuthorsM.-Pilar Muñoz; Cristina Corchero; F.-Javier Heredia
Conference NameThe 57th Session of the International Statistical Institute
Conference Date16-22/08/2009
PublisherInternational Statistical Institute
Conference LocationDurban, South Africa
Type of WorkPlenary session
Key Wordsresearch; spot price forecasting; scenario generation; MIBEL
AbstractIn liberalized electricity markets, Generation Companies must build an hourly bid that is sent to the market operator. The price at which the energy will be paid is unknown during the bidding process and has to be forecast. In this work we apply forecasting factor models to this framework and study its suitability.
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Improving electricity market price scenarios by means of forecasting factor models

Publication TypeReport
Year of Publication2009
AuthorsM.-Pilar Muñoz; Cristina Corchero; F.-Javier Heredia
Pages12
Date09/2009
ReferenceResearch Report DR 2009/06, Dept. of Statistics and Operations Research, E-Prints UPC http://hdl.handle.net/2117/3047. Universitat Politècnica de Catalunya.
Prepared forPlenary session on the 57th Session of the International Statistical Institute, Durban, South Africa. Accepted for publication at International Statistical Review.
CityBarcelona.
Key Wordsresearch; spot price forecasting; scenario generation; MIBEL
AbstractIn liberalized electricity markets, Generation Companies must build an hourly bid that is sent to the market operator. The price at which the energy will be paid is unknown during the bidding process and has to be forecast. In this work we apply forecasting factor models to this framework and study its suitability.
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