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On the Influence of Renewable Energy Sources in Electricity Price Forecasting in the Iberian Market

Diego Aineto (), Javier Iranzo-Sánchez (), Lenin G. Lemus-Zúñiga (), Eva Onaindia () and Javier F. Urchueguía ()
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Diego Aineto: Departamento de Sistemas Informáticos y Computación, Universitat Politècnica de València, 46022 Valencia, Spain
Javier Iranzo-Sánchez: Departamento de Sistemas Informáticos y Computación, Universitat Politècnica de València, 46022 Valencia, Spain
Lenin G. Lemus-Zúñiga: ITACA, Universitat Politècnica de València, 46022 Valencia, Spain
Eva Onaindia: Departamento de Sistemas Informáticos y Computación, Universitat Politècnica de València, 46022 Valencia, Spain
Javier F. Urchueguía: ITACA, Universitat Politècnica de València, 46022 Valencia, Spain

Energies, 2019, vol. 12, issue 11, 1-1

Abstract: The mainstream of EU policies is heading towards the conversion of the nowadays electricity consumer into the future electricity prosumer (producer and consumer) in markets in which the production of electricity will be more local, renewable and economically efficient. One key component of a local short-term and medium-term planning tool to enable actors to efficiently interact in the electric pool markets is the ability to predict and decide on forecast prices. Given the progressively more important role of renewable production in local markets, we analyze the influence of renewable energy production on the electricity price in the Iberian market through historical records. The dependencies discovered in this analysis will serve to identify the forecasts to use as explanatory variables for an electricity price forecasting model based on recurrent neural networks. The results will show the wide impact of using forecasted renewable energy production in the price forecasting.

Keywords: electricity market; electricity price forecasting; day-ahead market; recurrent neural networks; renewable energies (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
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