energy economy

Multistage Scenario Trees Generation for Electricity Markets Optimization

Publication TypeConference Paper
Year of Publication2021
AuthorsMarlyn Dayana Cuadrado Guevara; F.-Javier Heredia
Conference Name31st European Conference on Operational Research.
Conference Date11-14/07/2021
Conference LocationAthens
Type of WorkInvited presentation
ISBN NumberISBN 978-618-85079-1-3
Key Wordsresearch; multistage stochastich programming; virtual power plants; electricity markets; scenarios tree generation
AbstractThe 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.
URLClick Here
ExportTagged XML BibTex

Multistage Scenario Trees Generation for Renewable Energy Systems Optimization

Publication TypeThesis
Year of Publication2020
AuthorsMarlyn Dayana Cuadrado Guevara
Academic DepartmentDept. of Statistics and Operations Research. Prof. F.-Javier Heredia, advisor.
Number of Pages194
UniversityUniversitat Politècnica de Catalunya-BarcelonaTech
CityBarcelona
DegreePhD Thesis
Key Wordsresearch; Battery energy storage systems; Electricity markets; Ancillary services market; Wind power generation; Virtual power plants; Multistage Stochastic programming; phd thesis
AbstractThe 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.
URLClick Here
ExportTagged XML BibTex

Stochastic optimal generation bid to electricity markets with emissions risk constraints.

Publication TypeJournal Article
Year of Publication2018
AuthorsF.-Javier Heredia; Julián Cifuentes-Rubiano; Cristina Corchero
Journal TitleJournal of Environmental Management
Volume207
Issue1
Pages12
Start Page432
Journal DateFebruary 2018
PublisherElsevier
ISSN Number0301-4797
Key Wordsresearch; OR in Energy; Stochastic Programming; Risk Management; Electricity market; Emissions reduction; paper
AbstractThere 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.
URLClick Here
DOI10.1016/j.jenvman.2017.11.010
Preprinthttp://hdl.handle.net/2117/114024
ExportTagged XML BibTex

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

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.
URLClick Here
ExportTagged XML BibTex

A stochastic programming model for the tertiary control of microgrids

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.
URLClick Here
DOI10.1109/EEM.2015.7216761
ExportTagged XML BibTex

Economic analysis of battery electric storage systems operating in electricity markets

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.
URLClick Here
DOI10.1109/EEM.2015.7216739
Preprinthttp://hdl.handle.net/2117/82524
ExportTagged XML BibTex

Economic analysis of battery electric storage systems operating in electricity markets

Publication TypeConference Paper
Year of Publication2015
AuthorsF.-Javier Heredia; Jordi Riera; Montserrat Mata; Joan Escuer; Jordi Romeu
Conference Name12th International Conference on the European Energy Market
Conference Date19-22/05/2015
Conference LocationLisbon, Portugal
Type of Workcontributed presentation
Key Wordsresearch; 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
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.
URLClick Here
ExportTagged XML BibTex
Syndicate content