TED2021-131365B-C44

Optimal Participation of Energy Communities in Electricity Markets under Uncertainty. A Multi-Stage Stochastic Programming Approach

Publication TypeConference Paper
Year of Publication2024
AuthorsAlbert Solà Vilalta, Marlyn Cuadrado, Ignasi Mañé, F.-Javier Heredia
Conference NameISMP2024, 25th International Symposium on Mathematical Programming
Conference Date21-26/07/2024
Conference LocationMontréal, Canada.
Type of WorkInvited presentation
Key Wordsenergy communities; electricity markets; demand flexibility; prosumers; mathematical optimization; stochastic programming; research
AbstractAn energy community is a legal figure, recently coined by the European Union, that creates a framework to encourage active participation of citizens and local entities in the energy transition to net-zero. In this work, we study the optimal participation of energy communities in day-ahead, reserve, and intraday electricity markets. where energy communities cannot meet their internal demand, and periods where they generate excess electricity. This is because the electricity they generate often comes from variable renewable resources like solar and wind. Electricity market participation is a natural way to ensure they meet their internal demand at all times, and, simultaneously, make the most of the excess electricity. We propose a multi-stage stochastic programming model that captures variable renewable and electricity price uncertainty. The multi-stage aspect models the di¿erent times at which variable renewable generation is considered to be known and electricity prices from di¿erent markets are revealed. This results in a very large scenario tree with 34 stages, and hence a very large optimization problem. Scenario reduction techniques are applied to make the problem tractable. Case studies with real data are discussed, considering di¿erent energy community configurations, to analyse proposed regulatory frameworks in Europe. The added value of considering stochasticity in this problem is also analysed. The motivation to do so is that there are time periods
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Optimal Participation of Energy Communities in Electricity Markets under Uncertainty. A Multi-Stage Stochastic Programming Approach

Publication TypeConference Paper
Year of Publication2024
AuthorsAlbert Solà Vilalta, F.-Javier Heredia
Conference NameEURO24, 33rd European Conference on Operational Research
Conference Date30/06-3/07/2024
Conference LocationTechnical University of Denmark (DTU), Copenhagen, Denmark.
Type of WorkContributed presentation
Key Wordselectricity markets; energy communities, mathematical optimization; stochastic programming; research
AbstractAn energy community is a legal figure, recently coined by the European Union, that creates a framework to encourage active participation of citizens and local entities in the energy transition to net-zero. In this work, we study the optimal participation of energy communities in day-ahead, reserve, and intraday electricity markets. The motivation to do so is that there are time periods where energy communities cannot meet their internal demand, and periods where they generate excess electricity. This is because most of the electricity they generate comes from variable renewable resources like solar and wind. Electricity market participation is a natural way to ensure they meet their internal demand at all times, and, simultaneously, make the most of the excess electricity. We propose a multi-stage stochastic programming model that captures variable renewable and electricity price uncertainty. The multi-stage aspect models the di erent times at which variable renewable generation is considered to be known and electricity prices from di erent markets are revealed. This results in a very large scenario tree with 34 stages, and hence a very large optimization problem. Scenario reduction techniques are applied to make the problem tractable. Case studies with real data are discussed, considering di erent energy community configurations, to analyse proposed regulatory frameworks in Europe. The added value of considering stochasticity in this problem is also analysed.
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Open post-doc position on mathematical optimization in energy communities

DESCRIPTION

The Group on Numerical Optimization and Modelling (GNOM) at the Universitat Politècnica de Catalunya - BarcelonaTech  (Barcelona, Spain), is looking for a postdoctoral research associate in mathematical optimization of energy systems to join the project Unified multi-market participation of energy communities in energy markets. This contract is scheduled to start in April 1st 2023 and will last until November 30st 2024, with a possible extension of one year. Applications will be accepted until March 15st, 2023.

REQUIREMENTS

  • Candidates should have a PhD in Operations Research,Mathematics, Computer Science, Electrical or a related discipline, with a strong mathematical optimization background.
  • Priority will be given to candidates with expertise in optimization models for energy systems and electricity markets, stochastic programming and algebraic modelling languages.
  • Expertise in mathematical optimization modelling languages and
    solvers.
  • Fluency in English and communication skills

CONTRACT DETAILS, CALL AND APPLICATIONS

ADDITIONAL INFORMATION

OptiREC: Unified multi-market participation of energy communities in energy markets

 On January 2023 the project "Unified multi-market participation of energy communities in energy markets" (OptiREC) started. This is a coordinated project in collaboration with IREC, Universitat de Girona and Universidad Comillas, granted by the Agencia Estatal de Investigación within the call Proyectos de Transición Ecológica y Transición Digital 2021. This is a coordinated project in collaboration with the IREC, the Universitat de Girona and Universidad Comillas. The work to be done by the UPC is the development of a multi-stage stochastic programming model to optimize the bid of energy communities to the wholesale electricity market.
 
ATTENTION: POST-DOC POSITION (closed)   
 
 

Unified multi-market participation of energy communities in energy markets (OptiREC)

Publication TypeFunded research projects
Year of Publication2022
AuthorsF.-Javier Heredia; Albert Solà Vilalta; Marlyn Dayana Cuadrado Guevara
Type of participationLeader
Duration01/23-12/24
CallPROYECTOS DE TRANSICIÓN ECOLÓGICA Y TRANSICIÓN DIGITAL 2021
Funding organizationMINISTERIO DE CIENCIA E INNOVACIÓN
PartnersIREC, Universitat de Girona, Universidad Comillas.
Full time researchers2,5
Budget149.500€
Project codeTED2021-131365B-C44
Key Wordsresearch; TED2021-131365B-C44; energy communities; electricity markets; bilevel stochastic programming
AbstractThe general purpose of this subproject is to study the participation of energy communities in the multimarket structure of the wholesale electricity market in order to develop mathematical models and computational tools for the optimal bid to wholesale markets. From the point of view of the wholesale electricity market, all the complexity of the inner structure of energy communities (dispatchable and nondispatchable generation, storage, demand,) can be conceptually understood as a single virtual programming unit ( a Community Virtual Programming Unit, CVPU) that participate in the wholesale electricity multimarket structure (spot and ancillary-services markets). The final goal of this project is to develop a multi-stage stochastic-programming model for the Multimarket Optimal Bid of Energy Communities (MOBEC) problem that will be validated with real data from the Iberian Electricity Market (MIBEL). Conceptually speaking, energy communities are a complex energy system comprising dispatchable and non-dispatchable generation, energy storage systems and an own demand, that participate in the wholesale electricity market. Based on the experience of previous studies the extension of stochastic programming models to energy communities is a fairly natural and a sounded research methodology. First, the participation of energy communities in spot markets will be analysed. Spot markets (day and intraday) are the most important one in terms of the amount of energy traded. A CVPU will be defined allowing the energy community to submit bids to the single day ahead and to the multiple intraday markets, according to the MIBEL rules. Second, the participation of energy communities in ancillary services markets will be studied. Dispatchable generation units (thermal) together with storage devices and demand flexibility provide the energy community with reserve capabilities that can be bid to the secondary reserve market. The reserve of the CVPU will be defined, formulated and integrated in the (MOBEC) optimization model. The resulting model will be implemented and validated with real data from the real energy communities and the MIBEL. Multi-stage stochastic programming optimal bid models have been successfully developed so far for generation+storage units and will be extended in this project and adapted to the specific features of an energy community through a CVPU that participates in the wholesale electricity market as a single programming unit.
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