electricity market

Presentation at the EURO 2022 conference in Finland.

Last Julty 4 2022 I was invited at the EURO 2022 conference , Aalto University, Espoo, near Helsinki, to present the work Multistage stochastic programming for the optimal bid of a wind-thermal power production pool with battery storage, which is a continuation of the MSc  and PhD thesis of Mr. Ignasi Manyé and Ms. Marlyn D. Cuadrado respectively. This work tackles with an extensive study along a complete timespan of on year analyzing the benefits of a joint operation of a wind and thermal generation system in the elecrticity markets and bilateral contracts. Numerical results show that the total profit increases by  13% in average, but that it can be as high as 77%, with a reduction of the thermal operation costs of 61%.

Multistage stochastic programming for the optimal bid of a wind-thermal power production pool with battery storage.

Publication TypeConference Paper
Year of Publication2022
AuthorsF.-Javier Heredia; Ignasi Mañé; Marlyn Dayana Cuadrado Guevara
Conference NameEURO 2022
Conference Date03-06/07/2022
Conference LocationEspoo, Finland.
Type of WorkInvited presentation
ISBN Number978-951-95254-1-9
Key Wordsresearch; multistage stochastic programming; virtual power plants; unit commitment
AbstractIn this study we present a multistage stochastic programming model to find the joint optimal bid to electricity markets of a pool of dispatchable (thermal) and non-dispatchable (wind) production units with battery storage facilities. The assumption is that these programming units are operated by the same utility that, previous to the market clearing, has to dispatch some bilateral contracts with the joint production of the production pool. The multistage model mimics the multimarket bidding process in the Iberian Electricity Market (MIBEL). First, the utility has to decide how to cover the energy of the bilateral contracts with the available units. Second, the production capacity of each unit, not allocated to the bilateral contracts, must be offered to the seven consecutives spot markets (day-ahead and six intraday markets) plus the secondary reserve market (the most relevant ancillary services market). The stochasticity of the electricity clearing prices and the hourly generation of the wind-power units is considered. The stochastic process associated to this multistage decision-making process is modelled through multistage scenario trees with thirty-four stages that are built from forecasting models based on real data of the Iberian Electricity Market. The numerical results show the advantage of the joint operation of the pool of production units with an increase of the overall expected profits, mainly due to a strong reduction of the operational costs.
URLClick Here
ExportTagged XML BibTex

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.
URLClick Here
ExportTagged XML BibTex

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.
URLClick Here
ExportTagged XML BibTex

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.
URLClick Here
ExportTagged XML BibTex

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.

 

Syndicate content