Forecasting electricity consumption of OECD countries: A global machine learning modeling approach

Electricity is a critical utility for social growth. Accurate estimation of its consumption plays a vital role in economic development. A database that included past electricity consumption data from all OECD countries was prepared. Since national trends may be transferable from one country to anoth...

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Veröffentlicht in:Utilities policy 2021-06, Vol.70, p.101222, Article 101222
Hauptverfasser: Sen, Doruk, Tunç, K.M. Murat, Günay, M. Erdem
Format: Artikel
Sprache:eng
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Zusammenfassung:Electricity is a critical utility for social growth. Accurate estimation of its consumption plays a vital role in economic development. A database that included past electricity consumption data from all OECD countries was prepared. Since national trends may be transferable from one country to another, the entire database was modeled and simulated via machine learning techniques to forecast the energy consumption of each country. Understanding similarities among the profiles of different countries could increase predictive accuracy and improve associated public policies. [Display omitted] •A database of 936 entries was built on electricity consumption of OECD countries.•A global modeling approach was applied on database based on machine learning tools.•Electricity consumption of all OECD countries were predicted for the next ten years.•Machine learning extracts any likelihood in energy profiles of different countries.
ISSN:0957-1787
1878-4356
DOI:10.1016/j.jup.2021.101222