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

Thu, 10/24/2024 - 11:48 — admin
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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Ph D. Thesis on multistage scenario tree generation for renewable energies.

Mon, 11/30/2020 - 19:40 — admin
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.

On optimal participation in the electricity markets of wind power plants with battery energy storage systems

Tue, 05/15/2018 - 16:25 — admin
Publication TypeJournal Article
Year of Publication2018
AuthorsF.-Javier Heredia; Marlyn D. Cuadrado; Cristina Corchero
Journal TitleComputers and Operations Research
Volume96
Pages316-329
Journal Date08/2018
PublisherElsevier
ISSN Number0305-0548
Key Wordsresearch; Battery energy storage systems; Electricity markets; Ancillary services market; Wind power generation; Virtual power plants; Stochastic programming; paper
AbstractThe recent cost reduction and technological advances in medium- to large-scale battery energy storage systems (BESS) makes these devices a true alternative for wind producers operating in electricity markets. Associating a wind power farm with a BESS (the so-called virtual power plant (VPP)) provides utilities with a tool that converts uncertain wind power production into a dispatchable technology that can operate not only in spot and adjustment markets (day-ahead and intraday markets) but also in ancillary services markets that, up to now, were forbidden to non-dispatchable technologies. What is more, recent studies have shown capital cost investment in BESS can be recovered only by means of such a VPP participating in the ancillary services markets. We present in this study a multi-stage stochastic programming model to find the optimal operation of a VPP in the day-ahead, intraday and secondary reserve markets while taking into account uncertainty in wind power generation and clearing prices (day-ahead, secondary reserve, intraday markets and system imbalances). A case study with real data from the Iberian electricity market is presented.
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DOI10.1016/j.cor.2018.03.004
Preprinthttp://hdl.handle.net/2117/118479
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On the optimal participation in electricity markets of wind power plants with battery energy storage systems

Mon, 07/18/2016 - 18:43 — admin
Publication TypeConference Paper
Year of Publication2016
AuthorsF.-Javier Heredia; Cristina Corchero; Marlyn D. Cuadrado
Conference Name28th European Conference on Operational Research
Series TitleConference Handbook
Pagination322
Conference Date3-6/07/2016
Conference LocationPoznan, Poland
Type of Workcontributed presentation.
Key Wordsresearch; VPP; wind generation; battery energy storage system; stochastic programming; electricity market; optimal bid
AbstractThe recent cost reduction and technologic advances in medium to large scale Battery Energy Storage Systems (BESS) makes these devices a real choice alternative for wind producers operating in electricity markets. The association of a wind power farm with a BESS (the so called Virtual Power Plant VPP) provides utilities with a tool to turn the uncertainty wind power production into a dispatchable technology enabled to operate not only in the spot and adjustment markets (day-ahead and intraday markets) but also in ancillary services markets that, up to now, was forbidden to non-dispatchable technologies. Even more, recent studies have shown that the capital cost investment in BESS can only be recovered through the participation of such a VPP in the ancillary services markets. We present in this study a stochastic programming model to find the optimal participation of a VPP to the day-ahead market and secondary reserve markets (the most relevant ancillary service market) where the uncertainty in wind power generation and markets prices (day-ahead ancillary services) has been considered. A case study with real data from the Iberian Electricity Market is presented.
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A stochastic programming model for the tertiary control of microgrids

Thu, 09/03/2015 - 10:25 — admin
Publication TypeProceedings Article
Year of Publication2015
AuthorsLeire Citores; Cristina Corchero; F.-Javier Heredia
Conference Name12th International Conference on the European Energy Market (EEM15)
Pagination1-6
Conference Start Date19-22/05/2015
PublisherIEEE
Conference LocationLisbon, Portugal.
ISBN Number978-1-4673-6691-5
Key WordsMicrogrids; Optimization; Production; Stochastic processes; Uncertainty; Wind power generation; Wind speed; energy system optimization; microgrid; scenario generation; stochastic programming; paper; research
AbstractIn this work a scenario-based two-stage stochastic programming model is proposed to solve a microgrid's tertiary control optimization problem taking into account some renewable energy resource's uncertainty as well as uncertain energy deviation prices in the electricity market. Scenario generation methods for wind speed realizations are also studied. Results show that the introduction of stochastic programming represents a significant improvement over a deterministic model.
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DOI10.1109/EEM.2015.7216761
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Economic analysis of battery electric storage systems operating in electricity markets

Thu, 09/03/2015 - 10:14 — admin
Publication TypeProceedings Article
Year of Publication2015
AuthorsF.-Javier Heredia; Jordi Riera; Montserrat Mata; Joan Escuer; Jordi Romeu
Conference Name12th International Conference on the European Energy Market (EEM15)
Pagination1- 5
Conference Start Date19/05/2015
PublisherIEEE
Conference LocationLisbone, Portugal.
ISBN Number978-1-4673-6692-2/15
Key Wordsvirtual power plants; energy economy; battery energy storage systems; electricity markets; SAS/OR; wind power; research; paper
AbstractBattery electric storage systems (BESS) in the range of 1-10 MWh is a key technology allowing a more efficient operation of small electricity market producer. The aim of this work is to assess the economic viability of Li-ion based BESS systems for small electricity producers. The results of the ex-post economic analysis performed with real data from the Iberian Electricity Market shows the economic viability of a Li-ion based BESS thanks to the optimal operation in day-ahead and ancillary electricity markets.
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DOI10.1109/EEM.2015.7216739
Preprinthttp://hdl.handle.net/2117/82524
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Forecasting and optimization of wind generation in energy markets

Sat, 07/19/2014 - 11:53 — admin
Publication TypeFunded research projects
Year of Publication2014
AuthorsF.- Javier Heredia; Ma. Pilar Muñoz; Josep Anton Sánchez; Maria Dolores Márquez; Eugenio Mijangos; Marlyn Dayana Cuadrado Guevara
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; energy
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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Optimal sale bid for a wind producer in Spanish electricity market

Wed, 10/26/2011 - 13:56 — admin
Publication TypeTesis de Grau i Màster // BSc and MSc Thesis
Year of Publication2011
AuthorsSimona Sacripante
DirectorF.-Javier Heredia
Tipus de tesiMSc Thesis
TitulacióMaster in Statistics and Operations Research
CentreFaculty of Mathematics and Statistics
Data defensa10/11/2011
Nota // mark9 / 10
Key Wordsteaching; renewebable energy; electricity market; optimal bid; wind generators; wind; intraday market; wind producer; MSc Thesis
AbstractThe objective of this work is to find an optimal commercial strategy in the production market that would allow wind producer to maximize their daily profit. That can be achieved on one hand, increasing incomes in day-ahead and intraday markets, on the other hand, reducing deviation costs due to error in generation predictions.
DOI / handlehttp://hdl.handle.net/2099.1/13914
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Collaboration agreement with Fersa Energías Renovables

Thu, 01/13/2011 - 08:39 — admin
Professors Narcis Nabona and F.-Javier Heredia visited the headquarters of Fersa Energías Renovables at Barcelona. Fersa Energías Renovables is the first independent company to be quoted in the Spanish stock market and one of the first in Europe dedicated exclusively to the development of clean energy. As a result of the meeting, Fersa and GNOM agreed to engage a collaboration to study the optimal integration of renewable energies in the energy production systems, and to incorporate Ms. Simona Scripante, electricity market analist of Fersa and student of the Master in Statistics and Operations Research of the UPC-BarcelonaTech, as a member of the GNOM's energy team.

Collaboration agreement with the Catalonia Institute for Energy Research

Tue, 12/28/2010 - 20:01 — admin

Last December 15 I visited, together with the members of the energy team of the GNOM research group, the headquarters of the Catalonia Institute for Energy Research. The board of this institution is comprised by representatives of the Spanish and Catalonian governments, catalonian universities and private sector companies, and its mission is to promote the research in the energy field and the dissemination of this research in collaboration with several major Spanish energy utilities.

The objective of the meeting was to undertake common research projects related the integration of renewevable energies in the electricity production system, specifically in the optimal management of microgrids and the design of the transmission network of offshore wind farm.

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