IDEAS home Printed from https://ideas.repec.org/a/eco/journ2/2018-03-1.html
   My bibliography  Save this article

Spanish Energy Market: Overview Towards Price Forecast

Author

Listed:
  • Nicolas Perez-Mora

    (University of Balearic Islands, Palma of Majorca 07122, Spain,)

  • Miquel L. Alomar

    (University of Balearic Islands, Palma of Majorca 07122, Spain,)

  • Victor Martinez-Moll

    (University of Balearic Islands, Palma of Majorca 07122, Spain,)

Abstract

This paper aims to give an overview of the Spanish Electric Market. This energy market is liberalized and complex due the new and modified rules along time. Due these circumstances the hourly energy prices may vary tremendously. The goal of this work is to analyze in detail the generation technologies, their strategies and energy mix to gain awareness and knowledge to evaluate energy price fluctuations. Two methods are used to forecast in different time horizons: ARIMAX and NARX. Both methods are homologous, using historical energy prices and optionally an explanatory variable. Three options are studied: no explanatory, energy demand and competitive market. Once the models are developed and trained, the results achieved are helpful to understand further changes in the market. These energy forecasts are competent to schedule energy generation and/or consumption.

Suggested Citation

  • Nicolas Perez-Mora & Miquel L. Alomar & Victor Martinez-Moll, 2018. "Spanish Energy Market: Overview Towards Price Forecast," International Journal of Energy Economics and Policy, Econjournals, vol. 8(3), pages 1-7.
    • Handle: RePEc:eco:journ2:2018-03-1
    as

    Download full text from publisher

    File URL: https://www.econjournals.com/index.php/ijeep/article/download/6174/3670
    Download Restriction: no
    File URL: https://www.econjournals.com/index.php/ijeep/article/view/6174/3670
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Conejo, Antonio J. & Contreras, Javier & Espinola, Rosa & Plazas, Miguel A., 2005. "Forecasting electricity prices for a day-ahead pool-based electric energy market," International Journal of Forecasting, Elsevier, vol. 21(3), pages 435-462.
    2. Cassola, Federico & Burlando, Massimiliano, 2012. "Wind speed and wind energy forecast through Kalman filtering of Numerical Weather Prediction model output," Applied Energy, Elsevier, vol. 99(C), pages 154-166.
    3. Rubin, Ofir D. & Babcock, Bruce A., 2013. "The impact of expansion of wind power capacity and pricing methods on the efficiency of deregulated electricity markets," Energy, Elsevier, vol. 59(C), pages 676-688.
    4. Andrea Cervone & Ezio Santini & Sabrina Teodori & Donatella Zaccagnini Romito, 2014. "Electricity Price Forecast: a Comparison of Different Models to Evaluate the Single National Price in the Italian Energy Exchange Market," International Journal of Energy Economics and Policy, Econjournals, vol. 4(4), pages 744-758.
    5. Claudio Monteiro & Tiago Santos & L. Alfredo Fernandez-Jimenez & Ignacio J. Ramirez-Rosado & M. Sonia Terreros-Olarte, 2013. "Short-Term Power Forecasting Model for Photovoltaic Plants Based on Historical Similarity," Energies, MDPI, vol. 6(5), pages 1-20, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jackson, Emerson Abraham & Tamuke, Edmund, 2018. "Probability Forecast Using Fan Chart Analysis: A case of the Sierra Leone Economy," MPRA Paper 88853, University Library of Munich, Germany, revised 04 Sep 2018.
    2. Victor I. Espinosa & José Antonio Peña-Ramos & Fátima Recuero-López, 2021. "The Political Economy of Rent-Seeking: Evidence from Spain’s Support Policies for Renewable Energy," Energies, MDPI, vol. 14(14), pages 1-16, July.
    3. Heidarpanah, Mohammadreza & Hooshyaripor, Farhad & Fazeli, Meysam, 2023. "Daily electricity price forecasting using artificial intelligence models in the Iranian electricity market," Energy, Elsevier, vol. 263(PE).

    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.
    1. 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.
    2. Jichun Liu & Yangfang Yang & Yue Xiang & Junyong Liu, 2019. "A Power Exchange Strategy for Multiple Areas with Hydro Power and Flexible Loads," Energies, MDPI, vol. 12(6), pages 1-17, March.
    3. Barrow, Devon & Kourentzes, Nikolaos, 2018. "The impact of special days in call arrivals forecasting: A neural network approach to modelling special days," European Journal of Operational Research, Elsevier, vol. 264(3), pages 967-977.
    4. Angelica Gianfreda & Francesco Ravazzolo & Luca Rossini, 2023. "Large Time‐Varying Volatility Models for Hourly Electricity Prices," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 545-573, June.
    5. Diongue, Abdou Kâ & Guégan, Dominique & Vignal, Bertrand, 2009. "Forecasting electricity spot market prices with a k-factor GIGARCH process," Applied Energy, Elsevier, vol. 86(4), pages 505-510, April.
    6. Shao, Zhen & Zheng, Qingru & Yang, Shanlin & Gao, Fei & Cheng, Manli & Zhang, Qiang & Liu, Chen, 2020. "Modeling and forecasting the electricity clearing price: A novel BELM based pattern classification framework and a comparative analytic study on multi-layer BELM and LSTM," Energy Economics, Elsevier, vol. 86(C).
    7. Sinha, Pankaj & Mathur, Kritika, 2016. "Empirical Analysis of Developments in the Day Ahead Electricity Markets in India," MPRA Paper 72969, University Library of Munich, Germany.
    8. Billé, Anna Gloria & Gianfreda, Angelica & Del Grosso, Filippo & Ravazzolo, Francesco, 2023. "Forecasting electricity prices with expert, linear, and nonlinear models," International Journal of Forecasting, Elsevier, vol. 39(2), pages 570-586.
    9. Heo, SungKu & Byun, Jaewon & Ifaei, Pouya & Ko, Jaerak & Ha, Byeongmin & Hwangbo, Soonho & Yoo, ChangKyoo, 2024. "Towards mega-scale decarbonized industrial park (Mega-DIP): Generative AI-driven techno-economic and environmental assessment of renewable and sustainable energy utilization in petrochemical industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    10. Fang, Ping & Fu, Wenlong & Wang, Kai & Xiong, Dongzhen & Zhang, Kai, 2022. "A compositive architecture coupling outlier correction, EWT, nonlinear Volterra multi-model fusion with multi-objective optimization for short-term wind speed forecasting," Applied Energy, Elsevier, vol. 307(C).
    11. Thao Pham & Killian Lemoine, 2020. "Impacts of subsidized renewable electricity generation on spot market prices in Germany : Evidence from a GARCH model with panel data," Working Papers hal-02568268, HAL.
    12. Tang, Yugui & Yang, Kuo & Zhang, Shujing & Zhang, Zhen, 2024. "Wind power forecasting: A temporal domain generalization approach incorporating hybrid model and adversarial relationship-based training," Applied Energy, Elsevier, vol. 355(C).
    13. Rafal Weron & Adam Misiorek, 2006. "Short-term electricity price forecasting with time series models: A review and evaluation," HSC Research Reports HSC/06/01, Hugo Steinhaus Center, Wroclaw University of Technology.
    14. Ahmed, R. & Sreeram, V. & Mishra, Y. & Arif, M.D., 2020. "A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
    15. Marie Bessec & Julien Fouquau & Sophie Meritet, 2016. "Forecasting electricity spot prices using time-series models with a double temporal segmentation," Applied Economics, Taylor & Francis Journals, vol. 48(5), pages 361-378, January.
    16. Simon Pezzutto & Gianluca Grilli & Stefano Zambotti & Stefan Dunjic, 2018. "Forecasting Electricity Market Price for End Users in EU28 until 2020—Main Factors of Influence," Energies, MDPI, vol. 11(6), pages 1-18, June.
    17. Karakatsani, Nektaria V. & Bunn, Derek W., 2008. "Forecasting electricity prices: The impact of fundamentals and time-varying coefficients," International Journal of Forecasting, Elsevier, vol. 24(4), pages 764-785.
    18. Goodarzi, Shadi & Perera, H. Niles & Bunn, Derek, 2019. "The impact of renewable energy forecast errors on imbalance volumes and electricity spot prices," Energy Policy, Elsevier, vol. 134(C).
    19. Rana Muhammad Adnan & Zhongmin Liang & Xiaohui Yuan & Ozgur Kisi & Muhammad Akhlaq & Binquan Li, 2019. "Comparison of LSSVR, M5RT, NF-GP, and NF-SC Models for Predictions of Hourly Wind Speed and Wind Power Based on Cross-Validation," Energies, MDPI, vol. 12(2), pages 1-22, January.
    20. Marcjasz, Grzegorz & Uniejewski, Bartosz & Weron, Rafał, 2019. "On the importance of the long-term seasonal component in day-ahead electricity price forecasting with NARX neural networks," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1520-1532.

    More about this item

    Keywords

    Energy Market; Forecasting; Time Series;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance

    Statistics

    Access and download statistics

    Corrections

    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:eco:journ2:2018-03-1. 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: Ilhan Ozturk (email available below). General contact details of provider: http://www.econjournals.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.