day-ahead market

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.
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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.
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DOI10.1109/EEM.2015.7216761
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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.
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DOI10.1109/EEM.2015.7216739
Preprinthttp://hdl.handle.net/2117/82524
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Parallel Proximal Bundle Methods for Stochastic Electricity Market Problems

Publication TypeConference Paper
Year of Publication2015
AuthorsF.-Javier Heredia; Antonio Rengifo
Conference Name27th European Conference on Operational Research
Conference Date12-15/07/2015
Conference LocationGlasgow, UK.
Type of Workinvited
Key Wordsresearch; MTM2013-48462-C2-1; mixed-integer nonlinear programming; proximal bundle methods; multimarket electricity problems; parallelism
AbstractThe use of stochastic programming to solve real instances of optimal bid problems in electricity market usually implies the solution of large scale mixed integer nonlinear optimization problems that can't be tackled with the available general purpose commercial optimisation software. In this work we show the potential of proximal bundle methods to solve large scale stochastic programming problems arising in electricity markets. Proximal bundle methods was used in the past to solve deterministic unit commitment problems and are extended in this work to solve real instances of stochastic optimal bid problems to the day-ahead market (with embedded unit commitment) with thousands of scenarios. A parallel implementation of the proximal bundle method has been developed to take profit of the separability of the lagrangean problem in as many subproblems as generation bid units. The parallel proximal bundle method (PPBM) is compared against general purpose commercial optimization software as well as against the perspective cuts algorithm, a method specially conceived to deal with quadratic objective function over semi-continuous domains. The reported numerical results obtained with a workstation with 32 threads show that the commercial software can’t find a solution beyond 50 scenarios and that the execution times of the proposed PPBM are as low as a 15% of the execution time of the perspective cut approach for problems beyond 800 scenarios.
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A stochastic programming model for the tertiary control of microgrids

Publication TypeConference Paper
Year of Publication2015
AuthorsLeire Citores; Cristina Corchero; F.-Javier Heredia
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; microgrid; stochastic programming; scenario generation; wind power
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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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.
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Stochastic Optimal Bid to Electricity Markets with Emission Risk Constraints

Publication TypeConference Paper
Year of Publication2014
AuthorsF.-Javier Heredia; Julián Cifuentes; Cristina Corchero
Conference NameIFORS2014: 20th Conference of the International Federation of Operational Research Societies
Conference Date13-18/07/2014
Conference LocationBarcelona
Type of WorkInvited presentation
Key Wordsresearch; emission limits; risk; stochastic programming; day-ahead electricity market; combined cycle units
AbstractThis work allows investigating the influence of the emission reduction plan, and the incorporation of the derivatives medium-term commitments in the optimal generation bidding strategy to the day-ahead electricity market. Two different technologies have been considered: the coal thermal units, high-emission technology, and the combined cycle gas turbine units, low-emission technology. The Iberian Electricity Market (MIBEL) and the Spanish National Emission Reduction Plan (NERP) defines the environmental framework to deal with by the day-ahead market bidding strategies. To address emission limitations, some of the standard risk management methodologies developed for financial markets, such as Value-at-Risk (VaR) and Conditional Valueat- Risk (CVaR), have been extended giving rise to the new concept of Conditional Emission at Risk (CEaR). The economic implications for a GenCo of including the environmental restrictions of this National Plan are analyzed, and the effect of the NERP in the expected profits and optimal generation bid are analyzed.
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A stochastic programming model for the tertiary control of microgrids

Publication TypeTesis de Grau i Màster // BSc and MSc Thesis
Year of Publication2014
AuthorsLeire Citores
DirectorF.-Javier Heredia, Cristina Corchero
Tipus de tesiMSc Thesis
TitulacióMaster in Statistics and Operations research
CentreFaculty of Mathematics and Statistics
Data defensa27/06/2014
Nota // mark10 MH (A with Honours)
Key Wordsresearch; teaching; microgrids, stochastic programming; scenario generation; wind generation; day-ahead electricity market; imbalances; MSc Thesis
AbstractIn this thesis 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 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 an improvement over a deterministic model.
DOI / handlehttp://hdl.handle.net/2099.1/23235
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Optimal energy management for a residential microgrid including a vehicle-to-grid system

Publication TypeReport
Year of Publication2013
AuthorsLucía Igualada; Cristina Corchero; Miguel Cruz-Zambrano; F.-Javier Heredia
Pages9
Date11/2013
ReferenceResearch report DR 2013/05, Dept. of Statistics and Operations Research. E-Prints UPC, http://hdl.handle.net/2117/20642. Universitat Politècnica de Catalunya
Prepared forPublished at IEEE Transactions on Smart Grids (DOI: 10.1109/TSG.2014.2318836)
Key Wordsresearch; optimal management; smart grids; vehicle-to-grid; renewable generation; microgrids
AbstractAn optimization model is proposed to manage a residential microgrid including a charging spot with a vehicle-to-grid system and renewable energy sources. In order to achieve a realistic and convenient management, we take into account: (1) the household load split into three different profiles depending on the characteristics of the elements considered; (2) a realistic approach to owner behavior by introducing the novel concept of range anxiety; (3) the vehicle battery management considering the mobility profile of the owner and (4) different domestic renewable energy sources. We consider the microgrid operated in grid-connected mode. The model is executed one-day-ahead and generates a schedule for all components of the microgrid. The results obtained show daily costs in the range of 2.82€ to 3.33€; the proximity of these values to the actual energy costs for Spanish households validate the modeling. The experimental results of applying the designed managing strategies show daily costs savings of nearly 10%.
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Stochastic optimal generation bid to electricity markets with emission risk constraints.

Publication TypeReport
Year of Publication2013
AuthorsF.-Javier Heredia; Julian Cifuentes; Cristina Corchero
Pages21
Date09/2013
ReferenceResearch report DR 2013/04, Dept. of Statistics and Operations Research. E-Prints UPC, http://hdl.handle.net/2117/20640. Universitat Politècnica de Catalunya
Prepared forsubmitted
Key Wordsresearch; OR in Energy; Stochastic Programming; Risk Management; Electricity market; Emission reduction
AbstractThere are many factors that influence the day-ahead market bidding strategies of a generation company (GenCo) in the current energy market framework. Environmental policy issues have become more and more important for fossil-fuelled power plants and they have to be considered in their management, giving rise to emission limitations. This work allows investigating the influence of the emission reduction plan, and the incorporation of the derivatives medium-term commitments in the optimal generation bidding strategy to the day-ahead electricity market. Two different technologies have been considered: the coal thermal units, high-emission technology, and the combined cycle gas turbine units, low-emission technology. The Iberian Electricity Market (MIBEL) and the Spanish National Emission Reduction Plan (NERP) defines the environmental framework to deal with by the day-ahead market bidding strategies. To address emission limitations, some of the standard risk management methodologies developed for financial markets, such as Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR), have been extended giving rise to the new concept of Conditional Emission-at-Risk (CEaR). This study offers to electricity generation utilities a mathematical model to determinate the individual optimal generation bid to the wholesale electricity market, for each one of their generation units that maximizes the long-run profits of the utility abiding by the Iberian Electricity Market rules, as well as the environmental restrictions set by the Spanish National Emissions Reduction Plan. The economic implications for a GenCo of including the environmental restrictions of this National Plan are analyzed, and the effect of the NERP in the expected profits and optimal generation bid are analyzed.
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