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
energy economy
Master Thesis on electricity markets.
Wed, 12/01/2021 - 13:35 — adminMultistage Scenario Trees Generation for Electricity Markets Optimization
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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Multistage Scenario Trees Generation for Renewable Energy Systems Optimization
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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Stochastic optimal generation bid to electricity markets with emissions risk constraints.
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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A multistage stochastic programming model for the optimal management of wind-BESS virtual power plants
Fri, 07/07/2017 - 10:16 — admin| Publication Type | Conference Paper |
| Year of Publication | 2017 |
| Authors | F.-Javier Heredia; Marlyn D. Cuadrado |
| Conference Name | WindFarms 2017 |
| Conference Date | 31/05-02/06/2017 |
| Conference Location | Madrid, Spain |
| Type of Work | Invited presentation |
| Key Words | research; wind farms; Ion-Li battery; multistage stochastic programming; stochastic programming |
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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 Type | Conference Paper |
| Year of Publication | 2016 |
| Authors | F.-Javier Heredia; Cristina Corchero; Marlyn D. Cuadrado |
| Conference Name | 28th European Conference on Operational Research |
| Series Title | Conference Handbook |
| Pagination | 322 |
| Conference Date | 3-6/07/2016 |
| Conference Location | Poznan, Poland |
| Type of Work | contributed presentation. |
| Key Words | research; VPP; wind generation; battery energy storage system; stochastic programming; electricity market; optimal bid |
| Abstract | The 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 Type | Proceedings Article |
| Year of Publication | 2015 |
| Authors | Leire Citores; Cristina Corchero; F.-Javier Heredia |
| Conference Name | 12th International Conference on the European Energy Market (EEM15) |
| Pagination | 1-6 |
| Conference Start Date | 19-22/05/2015 |
| Publisher | IEEE |
| Conference Location | Lisbon, Portugal. |
| ISBN Number | 978-1-4673-6691-5 |
| Key Words | Microgrids; Optimization; Production; Stochastic processes; Uncertainty; Wind power generation; Wind speed; energy system optimization; microgrid; scenario generation; stochastic programming; paper; research |
| Abstract | In 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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| DOI | 10.1109/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 Type | Proceedings Article |
| Year of Publication | 2015 |
| Authors | F.-Javier Heredia; Jordi Riera; Montserrat Mata; Joan Escuer; Jordi Romeu |
| Conference Name | 12th International Conference on the European Energy Market (EEM15) |
| Pagination | 1- 5 |
| Conference Start Date | 19/05/2015 |
| Publisher | IEEE |
| Conference Location | Lisbone, Portugal. |
| ISBN Number | 978-1-4673-6692-2/15 |
| Key Words | virtual power plants; energy economy; battery energy storage systems; electricity markets; SAS/OR; wind power; research; paper |
| Abstract | Battery 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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| DOI | 10.1109/EEM.2015.7216739 |
| Preprint | http://hdl.handle.net/2117/82524 |
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Economic analysis of battery electric storage systems operating in electricity markets
Wed, 06/24/2015 - 13:06 — admin| Publication Type | Conference Paper |
| Year of Publication | 2015 |
| Authors | F.-Javier Heredia; Jordi Riera; Montserrat Mata; Joan Escuer; Jordi Romeu |
| Conference Name | 12th International Conference on the European Energy Market |
| Conference Date | 19-22/05/2015 |
| Conference Location | Lisbon, Portugal |
| Type of Work | contributed presentation |
| Key Words | research; MTM2013-48462-C2-1; battery electricity storage systems; electricity markets; day-ahead market; secondary reserve market; SAS/OR; wind power plants; energy economy; virtual power plant |
| Abstract | Battery 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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