electricity market

Article sobre la crisi dels preus de l'electricitat al blog 5centims.cat

L'encariment dels costos de producció de l'energia elèctrica justifiquen realment el període de preus sense control de l'electricitat que estem observant durant els darrers mesos de 2021? I quin és el paper que juguen les regles de mercat i les centrals hidroelèctriques en aquesta tendència alcista dels preus? Intentem respondre a aquestes preguntes a l'article Costos de producció: causa o excusa de la crisi de preus de l'electricitat? publicat a 5centims.cat,  blog de debat econòmic creat el 2021 al si de la Societat Catalana d'Economia (SCE).

Multistage stochastic bid model for a wind-thermal power producer

Publication TypeTesis de Grau i Màster // BSc and MSc Thesis
Year of Publication2021
AuthorsIgnasi Mañé Bosch
DirectorF-Javier Heredia
Tipus de tesiMSc Thesis
TitulacióMaster in Statistics and Operations Reseafrch
CentreFacultat de matemàtiques i Estadística
Data defensa18/10/2021
Nota // mark9.5
Key Wordsteaching; electricity markets; multistage stochastic programming
Abstract For many political and economic reasons, over the last decades, electricity markets in developed countries have been liberalised. Markets regulated by governments in which prices were set by the competent authority are now the exception. In this new setting, electricity agents, both consumers and producers, compete to maximise their pro tability in a series of auctions designed to efficiently match supply and demand. Many energy producers manage together wind and thermal generation units to meet their contractual obligations such as bilateral contracts, as well as bid on the electric market to sell their production capacity. This master thesis explore different multi-stage stochastic programming models for generation companies to nd optimal bid functions in electric spot markets. The explored models not only capture the uncertainty of electric prices of different markets and financial products, but also couples together wind and thermal generation units, offering producers that combine both technologies a more suitable approach to nd their best possible bidding strategy among the space of possible actions.
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Master Thesis on electricity markets.

On November 2021 Mr. Ignasi Mañé presented the MsC thesis dissertation Multistage stochastic bid model for a wind-thermal power producer to opt for the master's degree in Statistics and Operations Research (UPC-UB), advised by prof. F.-Javier Heredia. This master thesis explores different multi-stage stochastic programming models for generation companies to find optimal bid functions in electric spot markets capturing the uncertainty of electric prices of different markets and financial products, and coupling together wind and thermal generation unit

Participation in the 31st European Conference on Operational Research.

Last July 21th, the work "Multistage Scenario Trees Generation for Electricity Markets Optimization" was presentated at the 31st European Conference on Operational Research  in an invited session of the stream "Stochastic and Robust Optimization". This study is a result of the PH.D. Thesis of Ms. Marlyn D. Cuadrado on scenarios trees generation for multistage stochastic programming in optimal electricity bid problems.

Multistage Scenario Trees Generation for Electricity Markets Optimization

Publication TypeConference Paper
Year of Publication2021
AuthorsMarlyn Dayana Cuadrado Guevara; F.-Javier Heredia
Conference Name31st European Conference on Operational Research.
Conference Date11-14/07/2021
Conference LocationAthens
Type of WorkInvited presentation
ISBN NumberISBN 978-618-85079-1-3
Key Wordsresearch; multistage stochastich programming; virtual power plants; electricity markets; scenarios tree generation
AbstractThe presence of renewables in electricity markets optimization have generated a high level of uncertainty in the data, which has led to a need for applying stochastic optimization to model this kind of problems. In this work, we apply Multistage Stochastic Programming (MSP) using scenario trees to represent energy prices and wind power generation. We developed a methodology of two phases where, in the first phase, a procedure to predict the next day for each random parameter of the MSP models is used, and, in the second phase, a set of scenario trees are built through Forward Tree Construction Algorithm (FTCA) and a modified Dynamic Tree Generation with a Flexible Bushiness Algorithm (DTGFBA). This methodology was used to generate scenario trees for the Multistage Stochastic Wind Battery Virtual Power Plant model (MSWBVPP model), which were based on MIBEL prices and wind power generation of a real wind farm in Spain. In addition, we solved three di erent case studies corresponding to three di erent hypotheses on the virtual power plant’s participation in electricity markets. Finally, we study the relative performance of the FTCA and DTGFBA scenario trees, analysing the value of the stochastic solution through the Forecasted Value of the Stochastic Solution (FVSS) and the classical VSS for the 366 daily instances of the MSWBVPP problem spanning a complete year.
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Ph D. Thesis on multistage scenario tree generation for renewable energies.

 On November 30th 2020 took place the defense of the Ph.D. Thesis entittled "Multistage Scenario Trees Generation for Renewable Energy Systems Optimization", authored by Ms. Marlyn D. Cuadrado Guevara and advised by prof. F.-Javier Heredia. In this thesis a new methodology to generate and validate probability scenario trees for multistage stochastic programming problems arising in two different energy systems with renewables are proposed. The first problem corresponds to the optimal bid to electricity markets of a virtual power plant that consists on a wind-power plant plus a battery storage energy systems. The second one is the optimal operation of a distribution grid with some photovoltaic production.

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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New paper published in Applied Energy

 The paper entittled Critical evaluation of European balancing markets to enable the participation of Demand Aggregators has been published in Applied Energy This paper has been done in collaboration with the Institute for Energy Research of Catalonia (IREC). This study analyzes barriers and enablers of four European electricity markets and proposes a new market framework that would enhance Demand Aggregators' participation. Main barriers for Demand Aggregators have been identified and analyzed and a regulation scheme is proposed to enable Demand Aggregators participation. According to our results, small tertiary building aggregation is still not economic viable but existing municipal retailers could consider to extend their operations to Demand Aggregation.

 

Critical evaluation of European balancing markets to enable the participation of Demand Aggregators

Publication TypeJournal Article
Year of Publication2020
AuthorsMattia Barbero; Cristina Corchero; Lluc Canals; Lucia Igualada; F.-Javier Heredia
Journal TitleApplied Energy
Volume264
Journal Date04/2020
PublisherElsevier
ISSN Number0306-2619/
Key WordsDemand Aggregator; Regulatory framework; Ancillary Services; Demand Response; Tertiary building management; research; paper
AbstractEuropean Directives are incentivizing consumers to play an active role in the electricity system and to collaborate to maintain its stability, which has been historically provided by large generation power plants. However, it is not easy for the System Operator to handle the coexistence of consumers and generators in the same markets. Under these circumstances, a new actor allows small residential and commercial consumers to participate in flexibility markets: The Demand Aggregator. However, balancing markets opened to Demand Aggregators still present several barriers that do not allow their practical participation. This study analyzes barriers and enablers of four European electricity markets and proposes a new market framework that would enhance Demand Aggregators’ participation. To validate the proposed market and to understand the economic potentials of aggregated small tertiary buildings, a Demand Aggregator is simulated using real building’s consumption data. Results show that technical requirements to participate in balancing markets such as the minimum bid size, the symmetricity of the offer and the product resolution strongly affect incomes for Demand Aggregators. However, neither in the proposed market, the creation of a Demand Aggregator whose business model is focused on small tertiary buildings does not seem realistic due to low incomes in comparison to the fixed costs necessary to enable Demand Response, especially if only the air conditioning system is considered.
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DOI10.1016/j.apenergy.2020.114707
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Generació d’arbres d’escenaris per a problemes d’oferta òptima en mercats d’electricitat

Publication TypeTesis de Grau i Màster // BSc and MSc Thesis
Year of Publication2019
AuthorsRoger Serra Castilla
DirectorF.- Javier Heredia; Marlyn D. Cuadrado
Tipus de tesiBSc Thesis
TitulacióGrau en Estadística
CentreFacultat de matemàtiques i Estadística
Data defensa01/2019
Nota // mark9.0
Key Wordsteaching; scenario generation; scenario trees; electricity markets; BSc Thesis
AbstractThe electricity markets (EM) is a regulated system which allows producers and consumers to sell and buy energy at a given price that is fixed through an auction mechanism. Thanks to the tasks done by this system, the safe generation, transportation and distribution of electricity needed to satisfy the demand of the national population is assured. The electricity markets is made up of several markets, that can be considered either spot markets (day-ahead and intraday markets, whose trading commodity is energy) or ancillary services markets (the commodity negotiated is energy used to assure the stability of the energy delivering). On the other hand, interacting with the EM there is a wind power plant (WPP) which is in charge of the wind power energy production. A battery energy storage system (BESS) is usually associated to the WPP. The union of the WPP and the BESS is called virtual power plant (VPP). In this context, an optimization model can be presented: the WBVPP model (WPP+BESS Virtual Power Plant). The aim of this optimization model is the maximization of the expected value of the total profit of the VPP. To calculate this value, it is necessary to quantify the amount of wind power energy that fluctuates between the VPP and the EM, as well as the clearing prices of the auctions. The main purpose of this project is to obtain scenario trees using a dynamic generation algorithm in order to satisfy the need to solve, in a reasonable period of time, complex optimization problems of optimal supply of wind power plants in electricity markets. The scenarios trees that are going to be obtained include information regarding the production of wind power energy and the clearing prices of the auctions of the different studied electricity markets. In this study a scenario tree generation algorithm is presented, together with all the theoretical background needed to understand and assure a correct implementation of it, as well as the definition of the different agents that perform in the context of electricity markets. In addition to that, some data will be applied to this algorithm in order to obtain a representation of the scenario trees and to understand the interpretation of them.
DOI / handlehttp://hdl.handle.net/2445/128065
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