day-ahead market
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. |
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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. |
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Tue, 07/13/2021 - 10:51 — admin
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Marlyn Dayana Cuadrado Guevara; F.-Javier Heredia |
| Conference Name | 31st European Conference on Operational Research. |
| Conference Date | 11-14/07/2021 |
| Conference Location | Athens |
| Type of Work | Invited presentation |
| ISBN Number | ISBN 978-618-85079-1-3 |
| Key Words | research; multistage stochastich programming; virtual power plants; electricity markets; scenarios tree generation |
| Abstract | The 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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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. |
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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 |
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Tue, 01/30/2018 - 21:12 — admin
| Publication Type | Journal Article |
| Year of Publication | 2018 |
| Authors | F.-Javier Heredia; Julián Cifuentes-Rubiano; Cristina Corchero |
| Journal Title | Journal of Environmental Management |
| Volume | 207 |
| Issue | 1 |
| Pages | 12 |
| Start Page | 432 |
| Journal Date | February 2018 |
| Publisher | Elsevier |
| ISSN Number | 0301-4797 |
| Key Words | research; OR in Energy; Stochastic Programming; Risk Management; Electricity market; Emissions reduction; paper |
| Abstract | There are many factors that influence the day-ahead market bidding strategies of a generation company (GenCo) within the framework of the current energy market. Environmental policy issues are giving rise to emission limitation that are becoming more and more important for fossil-fueled power plants, and these must be considered in their management. This work investigates the influence of the emissions reduction plan and the incorporation of the medium-term derivative commitments in the optimal generation bidding strategy for the day-ahead electricity market. Two different technologies have been considered: the high-emission technology of thermal coal units and the low-emission technology of combined cycle gas turbine units. The Iberian Electricity Market (MIBEL) and the Spanish National Emissions Reduction Plan (NERP) defines the environmental framework for dealing with the day-ahead market bidding strategies. To address emission limitations, we have extended some of the standard risk management methodologies developed for financial markets, such as Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR), thus leading to the new concept of Conditional Emission at Risk (CEaR). This study offers electricity generation utilities a mathematical model for determining the unit’s optimal generation bid to the wholesale electricity market such that it maximizes the long-term profits of the utility while allowing it to abide by the Iberian Electricity Market rules as well as the environmental restrictions set by the Spanish National Emissions Reduction Plan. We analyze the economic implications for a GenCo that includes the environmental restrictions of this National Plan as well as the NERP’s effects on the expected profits and the optimal generation bid. |
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| DOI | 10.1016/j.jenvman.2017.11.010 |
| Preprint | http://hdl.handle.net/2117/114024 |
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Sat, 12/16/2017 - 00:00 — admin
| Publication Type | Conference Paper |
| Year of Publication | 2017 |
| Authors | F.-Javier Heredia; Marlyn D. Cuadrado; J.-Anton Sánchez |
| Conference Name | 4th International Conference on Optimization Methods and Software 2017 |
| Conference Date | 16-21/12/2017 |
| Conference Location | La Havana |
| Type of Work | Invited presentation |
| Key Words | multistage; VSS; wind-BESS VPP; wind power; energy storage; battery; research |
| Abstract | One of the objectives of the FOWGEN project (https://fowgem.upc.edu) was to study the economic feasibility and optimal operation of a wind-BESS Virtual Power Plant (VPP): In [1] an ex-post economic analysis shows the economic viability of a wind-BESS VPP thanks to the optimal operation in day-ahead and ancillary electricity markets; In [2] a new multi-stage stochastic programming model (WBVPP)for the optimal bid of a wind producer both in spot and ancillary services electricity markets is developed.
The work presented here extends the study in [2] with a new methodology to treat the uncertainty, based in forecasting models, and the study of the quality of the stochastic solution.
[1] F-Javier Heredia et al. Economic analysis of battery electric storage systems operating in electricity markets 12th International Conference on the European Energy Market (EEM15), 2015 DOI: 10.1109/EEM.2015.7216739.
[2] F-Javier Heredia et al. On optimal participation in the electricity markets of wind power plants with battery energy storage system. Submitted, under second revision. 2017. |
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Fri, 07/07/2017 - 10:16 — admin
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. |
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