Pan-European CVaR-Constrained Stochastic Unit Commitment in Day-Ahead and Intraday Electricity Markets
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Asger Lunde & Peter R. Hansen, 2005.
"A forecast comparison of volatility models: does anything beat a GARCH(1,1)?,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(7), pages 873-889.
- Asger Lunde & Peter Reinhard Hansen, 2001. "A Forecast Comparison of Volatility Models: Does Anything Beat a GARCH(1,1)?," Working Papers 2001-04, Brown University, Department of Economics.
- Christopher Kath, 2019. "Modeling Intraday Markets under the New Advances of the Cross-Border Intraday Project (XBID): Evidence from the German Intraday Market," Energies, MDPI, vol. 12(22), pages 1-35, November.
- Wang, Peng & Zareipour, Hamidreza & Rosehart, William D., 2011. "Characteristics of the prices of operating reserves and regulation services in competitive electricity markets," Energy Policy, Elsevier, vol. 39(6), pages 3210-3221, June.
- Alison L. Gibbs & Francis Edward Su, 2002. "On Choosing and Bounding Probability Metrics," International Statistical Review, International Statistical Institute, vol. 70(3), pages 419-435, December.
- John Bower & Derek W. Bunn, 2000. "Model-Based Comparisons of Pool and Bilateral Markets for Electricity," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 1-29.
- Eduardo Schwartz & James E. Smith, 2000. "Short-Term Variations and Long-Term Dynamics in Commodity Prices," Management Science, INFORMS, vol. 46(7), pages 893-911, July.
- Jan Abrell & Friedrich Kunz, 2015.
"Integrating Intermittent Renewable Wind Generation - A Stochastic Multi-Market Electricity Model for the European Electricity Market,"
Networks and Spatial Economics, Springer, vol. 15(1), pages 117-147, March.
- Jan Abrell & Friedrich Kunz, 2013. "Integrating Intermittent Renewable Wind Generation: A Stochastic Multi-Market Electricity Model for the European Electricity Market," Discussion Papers of DIW Berlin 1301, DIW Berlin, German Institute for Economic Research.
- Morales, Juan M. & Zugno, Marco & Pineda, Salvador & Pinson, Pierre, 2014. "Electricity market clearing with improved scheduling of stochastic production," European Journal of Operational Research, Elsevier, vol. 235(3), pages 765-774.
- Antonio J. Conejo & Miguel Carrión & Juan M. Morales, 2010. "Decision Making Under Uncertainty in Electricity Markets," International Series in Operations Research and Management Science, Springer, number 978-1-4419-7421-1.
- Fürsch, Michaela & Malischek, Raimund & Lindenberger, Dietmar, 2012. "Der Merit-Order-Effekt der erneuerbaren Energien - Analyse der kurzen und langen Frist," EWI Working Papers 2012-14, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
- Müller, C. & Hoffrichter, A. & Wyrwoll, L. & Schmitt, C. & Trageser, M. & Kulms, T. & Beulertz, D. & Metzger, M. & Duckheim, M. & Huber, M. & Küppers, M. & Most, D. & Paulus, S. & Heger, H.J. & Schnet, 2019. "Modeling framework for planning and operation of multi-modal energy systems in the case of Germany," Applied Energy, Elsevier, vol. 250(C), pages 1132-1146.
- Matthias Nowak & Werner Römisch, 2000. "Stochastic Lagrangian Relaxation Applied to Power Scheduling in a Hydro-Thermal System under Uncertainty," Annals of Operations Research, Springer, vol. 100(1), pages 251-272, December.
- Gneiting, Tilmann & Raftery, Adrian E., 2007. "Strictly Proper Scoring Rules, Prediction, and Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 359-378, March.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Despoina I. Makrygiorgou & Nikos Andriopoulos & Ioannis Georgantas & Christos Dikaiakos & George P. Papaioannou, 2020. "Cross-Border Electricity Trading in Southeast Europe Towards an Internal European Market," Energies, MDPI, vol. 13(24), pages 1-18, December.
- Yuya Tanigawa & Narayanan Krishnan & Eitaro Oomine & Atushi Yona & Hiroshi Takahashi & Tomonobu Senjyu, 2023. "Clustering Method for Load Demand to Shorten the Time of Annual Simulation," Energies, MDPI, vol. 16(5), pages 1-22, February.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Tomás Marinozzi, 2023. "Forecasting Inflation in Argentina: A Probabilistic Approach," Ensayos Económicos, Central Bank of Argentina, Economic Research Department, vol. 1(81), pages 81-110, May.
- Fabian Krüger & Ingmar Nolte, 2011. "Disagreement, Uncertainty and the True Predictive Density," Working Paper Series of the Department of Economics, University of Konstanz 2011-43, Department of Economics, University of Konstanz.
- Simon Hirsch & Florian Ziel, 2022. "Simulation-based Forecasting for Intraday Power Markets: Modelling Fundamental Drivers for Location, Shape and Scale of the Price Distribution," Papers 2211.13002, arXiv.org.
- Russo, Marianna & Kraft, Emil & Bertsch, Valentin & Keles, Dogan, 2022.
"Short-term risk management of electricity retailers under rising shares of decentralized solar generation,"
Energy Economics, Elsevier, vol. 109(C).
- Russo, Marianna & Kraft, Emil & Bertsch, Valentin & Keles, Dogan, 2021. "Short-term risk management for electricity retailers under rising shares of decentralized solar generation," Working Paper Series in Production and Energy 57, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
- Atakan, Semih & Gangammanavar, Harsha & Sen, Suvrajeet, 2022. "Towards a sustainable power grid: Stochastic hierarchical planning for high renewable integration," European Journal of Operational Research, Elsevier, vol. 302(1), pages 381-391.
- Fabian Krüger & Sebastian Lerch & Thordis Thorarinsdottir & Tilmann Gneiting, 2021. "Predictive Inference Based on Markov Chain Monte Carlo Output," International Statistical Review, International Statistical Institute, vol. 89(2), pages 274-301, August.
- Didier Nibbering & Coos van Buuren & Wei Wei, 2021. "Real Options Valuation of Wind Energy Based on the Empirical Production Uncertainty," Monash Econometrics and Business Statistics Working Papers 19/21, Monash University, Department of Econometrics and Business Statistics.
- T. -N. Nguyen & M. -N. Tran & R. Kohn, 2020. "Recurrent Conditional Heteroskedasticity," Papers 2010.13061, arXiv.org, revised Jan 2022.
- Bjørndal, Endre & Bjørndal, Mette & Midthun, Kjetil & Tomasgard, Asgeir, 2018. "Stochastic electricity dispatch: A challenge for market design," Energy, Elsevier, vol. 150(C), pages 992-1005.
- Neil A. Wilmot, 2019. "Heavy Metals: Might as Well Jump," IJFS, MDPI, vol. 7(2), pages 1-14, June.
- Andrew J. Patton & Yasin Simsek, 2023. "Generalized Autoregressive Score Trees and Forests," Papers 2305.18991, arXiv.org.
- Park, Jungyeon & Alvarenga, Estêvão & Jeon, Jooyoung & Li, Ran & Petropoulos, Fotios & Kim, Hokyun & Ahn, Kwangwon, 2024. "Probabilistic forecast-based portfolio optimization of electricity demand at low aggregation levels," Applied Energy, Elsevier, vol. 353(PB).
- Ricardo Crisóstomo & Lorena Couso, 2018.
"Financial density forecasts: A comprehensive comparison of risk‐neutral and historical schemes,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(5), pages 589-603, August.
- Ricardo Crisóstomo & Lorena Couso, 2017. "Financial density forecasts: A comprehensive comparison of risk-neutral and historical schemes," CNMV Working Papers CNMV Working Papers no. 6, CNMV- Spanish Securities Markets Commission - Research and Statistics Department.
- Ricardo Crisostomo & Lorena Couso, 2018. "Financial density forecasts: A comprehensive comparison of risk-neutral and historical schemes," Papers 1801.08007, arXiv.org, revised May 2018.
- Narajewski, Michał & Ziel, Florian, 2020. "Ensemble forecasting for intraday electricity prices: Simulating trajectories," Applied Energy, Elsevier, vol. 279(C).
- Garcia-Gonzalez, Javier & Parrilla, Ernesto & Mateo, Alicia, 2007. "Risk-averse profit-based optimal scheduling of a hydro-chain in the day-ahead electricity market," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1354-1369, September.
- Todd E. Clark & Francesco Ravazzolo, 2012.
"The macroeconomic forecasting performance of autoregressive models with alternative specifications of time-varying volatility,"
Working Paper
2012/09, Norges Bank.
- Todd E. Clark & Francesco Ravazzolo, 2012. "The macroeconomic forecasting performance of autoregressive models with alternative specifications of time-varying volatility," Working Papers (Old Series) 1218, Federal Reserve Bank of Cleveland.
- Hua, Jian & Manzan, Sebastiano, 2013. "Forecasting the return distribution using high-frequency volatility measures," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4381-4403.
- Lima, Ricardo M. & Novais, Augusto Q. & Conejo, Antonio J., 2015. "Weekly self-scheduling, forward contracting, and pool involvement for an electricity producer. An adaptive robust optimization approach," European Journal of Operational Research, Elsevier, vol. 240(2), pages 457-475.
- Micha{l} Narajewski, 2022. "Probabilistic forecasting of German electricity imbalance prices," Papers 2205.11439, arXiv.org.
- Costa, Alexandre Bonnet R. & Ferreira, Pedro Cavalcanti G. & Gaglianone, Wagner P. & Guillén, Osmani Teixeira C. & Issler, João Victor & Lin, Yihao, 2021.
"Machine learning and oil price point and density forecasting,"
Energy Economics, Elsevier, vol. 102(C).
- Alexandre Bonnet R. Costa & Pedro Cavalcanti G. Ferreira & Wagner P. Gaglianone & Osmani Teixeira C. Guillén & João Victor Issler & Yihao Lin, 2021. "Machine Learning and Oil Price Point and Density Forecasting," Working Papers Series 544, Central Bank of Brazil, Research Department.
More about this item
Keywords
benders decomposition; conditional value at risk; forecasting errors; intraday markets; Lagrangian relaxation; stochastic mixed integer programming; unit commitment;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:13:y:2020:i:9:p:2339-:d:355332. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.