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Multistage Scenario Trees Generation for Renewable Energy Systems Optimization

Mon, 11/30/2020 - 19:17 — admin
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
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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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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Improving electricity market price scenarios by means of forecasting factor models

Fri, 05/06/2011 - 15:09 — admin
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.

Fri, 10/15/2010 - 17:49 — admin
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

Wed, 07/21/2010 - 15:14 — admin
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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Improving electricity market price scenarios by means of forecasting factor models

Tue, 09/01/2009 - 14:47 — admin
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

Tue, 09/01/2009 - 14:19 — admin
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.
URLClick Here
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