modeling languages
Thu, 10/24/2024 - 11:48 — admin
| Publication Type | Conference Paper |
| Year of Publication | 2024 |
| Authors | Albert Solà Vilalta, Marlyn Cuadrado, Ignasi Mañé, F.-Javier Heredia |
| Conference Name | ISMP2024, 25th International Symposium on Mathematical Programming |
| Conference Date | 21-26/07/2024 |
| Conference Location | Montréal, Canada. |
| Type of Work | Invited presentation |
| Key Words | energy communities; electricity markets; demand flexibility; prosumers; mathematical optimization; stochastic programming; research |
| Abstract | An 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 |
| URL | Click Here |
| Export | Tagged XML BibTex |
Thu, 10/24/2024 - 11:36 — admin
| Publication Type | Conference Paper |
| Year of Publication | 2024 |
| Authors | Albert Solà Vilalta, F.-Javier Heredia |
| Conference Name | EURO24, 33rd European Conference on Operational Research |
| Conference Date | 30/06-3/07/2024 |
| Conference Location | Technical University of Denmark (DTU), Copenhagen, Denmark. |
| Type of Work | Contributed presentation |
| Key Words | electricity markets; energy communities, mathematical optimization; stochastic programming; research |
| Abstract | An 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. |
| URL | Click Here |
| Export | Tagged XML BibTex |
Mon, 06/17/2024 - 18:57 — admin
Fri, 07/08/2022 - 12:10 — admin
Last July 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%.
Fri, 07/08/2022 - 11:26 — admin
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | F.-Javier Heredia; Ignasi Mañé; Marlyn Dayana Cuadrado Guevara |
| Conference Name | EURO 2022 |
| Conference Date | 03-06/07/2022 |
| Conference Location | Espoo, Finland. |
| Type of Work | Invited presentation |
| ISBN Number | 978-951-95254-1-9 |
| Key Words | research; multistage stochastic programming; virtual power plants; unit commitment |
| Abstract | In 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. |
| URL | Click Here |
| Export | Tagged XML BibTex |
Thu, 12/30/2021 - 13:20 — admin
| Publication Type | Tesis de Grau i Màster // BSc and MSc Thesis |
| Year of Publication | 2021 |
| Authors | Ignasi Mañé Bosch |
| Director | F-Javier Heredia |
| Tipus de tesi | MSc Thesis |
| Titulació | Master in Statistics and Operations Reseafrch |
| Centre | Facultat de matemàtiques i Estadística |
| Data defensa | 18/10/2021 |
| Nota // mark | 9.5 |
| Key Words | teaching; 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. |
| URL | Click Here |
| Export | Tagged XML BibTex |
Mon, 11/30/2020 - 19:17 — admin
| Publication Type | Thesis |
| Year of Publication | 2020 |
| Authors | Marlyn Dayana Cuadrado Guevara |
| Academic Department | Dept. of Statistics and Operations Research. Prof. F.-Javier Heredia, advisor. |
| Number of Pages | 194 |
| University | Universitat Politècnica de Catalunya |
| City | Barcelona |
| Degree | PhD Thesis |
| Key Words | research; Battery energy storage systems; Electricity markets; Ancillary services market; Wind power generation; Virtual power plants; Multistage Stochastic programming; phd thesis |
| Abstract | The 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. |
| URL | Click Here |
| Export | Tagged XML BibTex |
Tue, 07/21/2020 - 16:46 — admin
Tue, 05/15/2018 - 16:25 — admin
| Publication Type | Journal Article |
| Year of Publication | 2018 |
| Authors | F.-Javier Heredia; Marlyn D. Cuadrado; Cristina Corchero |
| Journal Title | Computers and Operations Research |
| Volume | 96 |
| Pages | 316-329 |
| Journal Date | 08/2018 |
| Publisher | Elsevier |
| ISSN Number | 0305-0548 |
| Key Words | research; Battery energy storage systems; Electricity markets; Ancillary services market; Wind power generation; Virtual power plants; Stochastic programming; paper |
| Abstract | The 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. |
| URL | Click Here |
| DOI | 10.1016/j.cor.2018.03.004 |
| Preprint | http://hdl.handle.net/2117/118479 |
| Export | Tagged XML BibTex |
Tue, 09/27/2016 - 09:19 — admin
| Publication Type | Tesis de Grau i Màster // BSc and MSc Thesis |
| Year of Publication | 2016 |
| Authors | Maksims Sisovs |
| Director | F.-Javier Heredia |
| Tipus de tesi | MSc Thesis |
| Titulació | "KIC InnoEnergy" Master of Science in Smart Electrical Networks and Systems |
| Centre | Escola Tècnica Superior d'Enginyeria Industrial de Barcelona (ETSEIB) |
| Data defensa | 16/09/2016 |
| Nota // mark | 10 MH (A+ with honours) |
| Key Words | teaching; BEES; battery energy storage systems; electrical vehicle; smart meters; retail energy market; MSc Thesis |
| Abstract | The main focus of this master thesis project is to evaluate the economic, technical and regulatory feasibility of distributed battery energy storage systems (BESS) and the potential opportunity of electricity companies to increase their pro ts through advanced operation in energy services, such as electric energy time-shift, ancillary or electric vehicle incentives in Spanish electricity market. To assess the feasibility, an optimization tool has been developed. This tool simulates energy trading between diff erent market participants with particular features extracted from data analysis and literature. Load consumption pro les had been developed from smart meter real data by applying several data mining techniques. This part had been guided by external collaborating entity Minsait. Electricity market analysis includes the overview of its functionality principles and regulatory side regarding storage adaptation and speci fic service applicability. Market historical prices were used for further electricity trading simulation. A brief technical insight explains current storage situation and tells about high-potential technologies in emerging markets. Benchmark analysis covers several products of battery manufacturers with relevant technical and price information. Spanish electricity market showed low adaptability to distributed BESS solutions: energy arbitrage incomes have resulted being insuficient. Ancillary services, despite promising economic gures, are to a large extent prohibited to be provided by distributed storage. Electric vehicle incentives, though, resulted being of a high interest due to absence of direct investment. |
| Export | Tagged XML BibTex |
|
The paper entitled Optimal Postponement in Supply Chain Network Design Under Uncertainty: An Application for Additive Manufacturing (preprint ) has been published in the International Journal of Production Research. This paper is the result of projects Strategical Models in Supply Chain Design, and Digitalizing Supply Chain Strategy with 3D Printing a successful collaboration between GNOM with Accenture Technology Labs (Silicon Valley), Accenture Analytics Innovation Center (Barcelona) and the Fundació CIM-UPC. This study This study presents a new two-stage stochastic programming decision model for assessing how to introduce some new manufacturing technology into any generic supply and distribution chain. It additionally determines the optimal degree of postponement, as represented by the so-called customer order decoupling point (CODP), while assuming uncertainty in demand for multiple products. Finally, it presents and analyses a case study for introducing additive manufacturing technologies.