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http://hdl.handle.net/10071/20235
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Title: Electricity price forecasting utilizing machine learning in MIBEL
Authors: Januário, João Filipe Ferreira
Orientador: Nunes, Luís Miguel Martins
Silva, Nuno Pinho da
Keywords: Machine learning
Electricity
Clearing market
Prediction
Input variables
Eletricidade
Preços
Métodos de previsão
Issue Date: 4-Nov-2019
Citation: JANUÁRIO, João Filipe Ferreira - Electricity price forecasting utilizing machine learning in MIBEL [Em linha]. Lisboa: ISCTE-IUL, 2019. Dissertação de mestrado. [Consult. Dia Mês Ano] Disponível em www:<http://hdl.handle.net/10071/20235>.
Abstract: Short term electricity price forecasts have become increasingly important in the last few decades due to the rise of more competitive electricity markets throughout the globe. Accurate forecasts are now essential for market players to maximize their profits and hedge against risk, hence various forecasting methodologies have been applied to electricity price forecasting in the last few decades. This dissertation explores the main methodologies and how accurately can three popular machine learning models, SVR LSTM and XGBoost, predict prices in the Iberian market of electricity. Additionally, a study on input variables and their relationship with the final price is made.
Peer reviewed: yes
URI: http://hdl.handle.net/10071/20235
Thesis identifier: 202460177
Designation: Mestrado em Engenharia Informática
Appears in Collections:T&D-DM - Dissertações de mestrado

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