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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
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    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.
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    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).

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    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

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