Influence of Increasing Renewable Power Penetration on the Long-Term Iberian Electricity Market Prices
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Ciarreta, Aitor & Nasirov, Shahriyar & Silva, Carlos, 2016. "The development of market power in the Spanish power generation sector: Perspectives after market liberalization," Energy Policy, Elsevier, vol. 96(C), pages 700-710.
- Newbery, David, 2016.
"Missing money and missing markets: Reliability, capacity auctions and interconnectors,"
Energy Policy, Elsevier, vol. 94(C), pages 401-410.
- David Newbery, 2015. "Missing Money and Missing Markets: Reliability, Capacity Auctions and Interconnectors," Cambridge Working Papers in Economics 1513, Faculty of Economics, University of Cambridge.
- David Newbery, 2015. "Missing Money and Missing Markets: Reliability, Capacity Auctions and Interconnectors," Working Papers EPRG 1508, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
- Povh, Martin & Fleten, Stein-Erik, 2009. "Modeling long-term electricity forward prices," MPRA Paper 13162, University Library of Munich, Germany.
- Gelabert, Liliana & Labandeira, Xavier & Linares, Pedro, 2011. "An ex-post analysis of the effect of renewables and cogeneration on Spanish electricity prices," Energy Economics, Elsevier, vol. 33(S1), pages 59-65.
- Weron, Rafał, 2014.
"Electricity price forecasting: A review of the state-of-the-art with a look into the future,"
International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
- Rafal Weron, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," HSC Research Reports HSC/14/07, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
- Yang, Haolin & Schell, Kristen R., 2021. "Real-time electricity price forecasting of wind farms with deep neural network transfer learning and hybrid datasets," Applied Energy, Elsevier, vol. 299(C).
- Ciarreta, Aitor & Espinosa, Maria Paz & Pizarro-Irizar, Cristina, 2017. "Has renewable energy induced competitive behavior in the Spanish electricity market?," Energy Policy, Elsevier, vol. 104(C), pages 171-182.
- Azofra, D. & Martínez, E. & Jiménez, E. & Blanco, J. & Saenz-Díez, J.C., 2014. "Comparison of the influence of biomass, solar–thermal and small hydraulic power on the Spanish electricity prices by means of artificial intelligence techniques," Applied Energy, Elsevier, vol. 121(C), pages 28-37.
- Umut Ugurlu & Ilkay Oksuz & Oktay Tas, 2018. "Electricity Price Forecasting Using Recurrent Neural Networks," Energies, MDPI, vol. 11(5), pages 1-23, May.
- Azofra, D. & Martínez, E. & Jiménez, E. & Blanco, J. & Azofra, F. & Saenz-Díez, J.C., 2015. "Comparison of the influence of photovoltaic and wind power on the Spanish electricity prices by means of artificial intelligence techinques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 532-542.
- Zaiyong Tang & Paul A. Fishwick, 1993. "Feedforward Neural Nets as Models for Time Series Forecasting," INFORMS Journal on Computing, INFORMS, vol. 5(4), pages 374-385, November.
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.- Ribó-Pérez, David & Van der Weijde, Adriaan H. & Álvarez-Bel, Carlos, 2019. "Effects of self-generation in imperfectly competitive electricity markets: The case of Spain," Energy Policy, Elsevier, vol. 133(C).
- Arcos-Vargas, A. & Nuñez, F. & Román-Collado, R., 2020. "Short-term effects of PV integration on global welfare and CO2 emissions. An application to the Iberian electricity market," Energy, Elsevier, vol. 200(C).
- Kolb, Sebastian & Dillig, Marius & Plankenbühler, Thomas & Karl, Jürgen, 2020. "The impact of renewables on electricity prices in Germany - An update for the years 2014–2018," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
- Ghimire, Sujan & Deo, Ravinesh C. & Casillas-Pérez, David & Sharma, Ekta & Salcedo-Sanz, Sancho & Barua, Prabal Datta & Rajendra Acharya, U., 2024. "Half-hourly electricity price prediction with a hybrid convolution neural network-random vector functional link deep learning approach," Applied Energy, Elsevier, vol. 374(C).
- Zoran Vojinovic & Vojislav Kecman & Rainer Seidel, 2001. "A data mining approach to financial time series modelling and forecasting," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 10(4), pages 225-239, December.
- Andrea Bucci, 2020.
"Realized Volatility Forecasting with Neural Networks,"
Journal of Financial Econometrics, Oxford University Press, vol. 18(3), pages 502-531.
- Andrea Bucci, 0. "Realized Volatility Forecasting with Neural Networks," Journal of Financial Econometrics, Oxford University Press, vol. 18(3), pages 502-531.
- Bucci, Andrea, 2019. "Realized Volatility Forecasting with Neural Networks," MPRA Paper 95443, University Library of Munich, Germany.
- Espinosa, María Paz & Pizarro-Irizar, Cristina, 2018. "Is renewable energy a cost-effective mitigation resource? An application to the Spanish electricity market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 902-914.
- Emil Kraft & Dogan Keles & Wolf Fichtner, 2020. "Modeling of frequency containment reserve prices with econometrics and artificial intelligence," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(8), pages 1179-1197, December.
- Russo, Marianna & Bertsch, Valentin, 2020.
"A looming revolution: Implications of self-generation for the risk exposure of retailers,"
Energy Economics, Elsevier, vol. 92(C).
- Russo, Marianna & Bertsch, Valentin, 2018. "A looming revolution: Implications of self-generation for the risk exposure of retailers," Papers WP597, Economic and Social Research Institute (ESRI).
- Sander van der Hoog, 2017. "Deep Learning in (and of) Agent-Based Models: A Prospectus," Papers 1706.06302, arXiv.org.
- Bell, William Paul & Wild, Phillip & Foster, John & Hewson, Michael, 2017. "Revitalising the wind power induced merit order effect to reduce wholesale and retail electricity prices in Australia," Energy Economics, Elsevier, vol. 67(C), pages 224-241.
- Nadia Ayed & Khemaies Bougatef, 2024. "Performance Assessment of Logistic Regression (LR), Artificial Neural Network (ANN), Fuzzy Inference System (FIS) and Adaptive Neuro-Fuzzy System (ANFIS) in Predicting Default Probability: The Case of," Computational Economics, Springer;Society for Computational Economics, vol. 64(3), pages 1803-1835, September.
- Daniel Manfre Jaimes & Manuel Zamudio López & Hamidreza Zareipour & Mike Quashie, 2023. "A Hybrid Model for Multi-Day-Ahead Electricity Price Forecasting considering Price Spikes," Forecasting, MDPI, vol. 5(3), pages 1-23, July.
- Gianfreda, Angelica & Ravazzolo, Francesco & Rossini, Luca, 2020.
"Comparing the forecasting performances of linear models for electricity prices with high RES penetration,"
International Journal of Forecasting, Elsevier, vol. 36(3), pages 974-986.
- Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2018. "Comparing the Forecasting Performances of Linear Models for Electricity Prices with High RES Penetration," Working Papers No 2/2018, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
- Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2018. "Comparing the Forecasting Performances of Linear Models for Electricity Prices with High RES Penetration," Papers 1801.01093, arXiv.org, revised Nov 2019.
- Andrea Bucci, 2020.
"Cholesky–ANN models for predicting multivariate realized volatility,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 865-876, September.
- Bucci, Andrea, 2019. "Cholesky-ANN models for predicting multivariate realized volatility," MPRA Paper 95137, University Library of Munich, Germany.
- Lago, Jesus & Marcjasz, Grzegorz & De Schutter, Bart & Weron, Rafał, 2021.
"Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark,"
Applied Energy, Elsevier, vol. 293(C).
- Jesus Lago & Grzegorz Marcjasz & Bart De Schutter & Rafa{l} Weron, 2020. "Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark," Papers 2008.08004, arXiv.org, revised Dec 2020.
- Ehsani, Behdad & Pineau, Pierre-Olivier & Charlin, Laurent, 2024. "Price forecasting in the Ontario electricity market via TriConvGRU hybrid model: Univariate vs. multivariate frameworks," Applied Energy, Elsevier, vol. 359(C).
- Angelica Gianfreda & Derek Bunn, 2018. "A Stochastic Latent Moment Model for Electricity Price Formation," BEMPS - Bozen Economics & Management Paper Series BEMPS46, Faculty of Economics and Management at the Free University of Bozen.
- Simshauser, Paul, 2018. "On intermittent renewable generation & the stability of Australia's National Electricity Market," Energy Economics, Elsevier, vol. 72(C), pages 1-19.
- Thibaut Th'eate & Antonio Sutera & Damien Ernst, 2023. "Matching of Everyday Power Supply and Demand with Dynamic Pricing: Problem Formalisation and Conceptual Analysis," Papers 2301.11587, arXiv.org.
More about this item
Keywords
renewable energy; electricity market prices; missing money problem; long-term forecast; artificial neural networks;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:16:y:2023:i:3:p:1054-:d:1039827. 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.