Aineto, D.; Iranzo-Sánchez, J.; Lemus Zúñiga, LG.; Onaindia De La Rivaherrera, E.; Urchueguía Schölzel, JF. (2019). On the Influence of Renewable Energy Sources in Electricity Price Forecasting in the Iberian Market. Energies. 12(11):1-20. https://doi.org/10.3390/en12112082
Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/156254
Title:
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On the Influence of Renewable Energy Sources in Electricity Price Forecasting in the Iberian Market
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Author:
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Aineto, Diego
Iranzo-Sánchez, Javier
Lemus Zúñiga, Lenin Guillermo
Onaindia De La Rivaherrera, Eva
Urchueguía Schölzel, Javier Fermín
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UPV Unit:
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Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Universitat Politècnica de València. Departamento de Física Aplicada - Departament de Física Aplicada
Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors
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Issued date:
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Abstract:
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[EN] 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 ...[+]
[EN] 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.
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Subjects:
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Electricity market
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Electricity price forecasting
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Day-ahead market
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Recurrent neural networks
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Renewable energies
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Copyrigths:
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Reconocimiento (by)
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Source:
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Energies. (eissn:
1996-1073
)
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DOI:
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10.3390/en12112082
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Publisher:
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MDPI AG
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Publisher version:
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https://doi.org/10.3390/en12112082
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Project ID:
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MECYD/FPU16/03184
AEI/TIN2017-88476-C2-1-R
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Thanks:
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This work is supported by the Spanish MINECO project TIN2017-88476-C2-1-R. D. Aineto is partially supported by the FPU16/03184.
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Type:
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Artículo
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