Energy management is a current topic due to the rising of costs, and climate change. This paper aims to study Artificial Intelligence (AI) to make energy consumption predictions. A deep literature review was carried out using Scopus database, clustering papers on short-and long-Term forecast. Moreover, sustainability is a major concern and energy forecasting in both short and long periods can be successfully made with Machine Learning, Neural Network, Deep Learning, and Grey models. Therefore, AI models improve energy consumption forecast and energy allocation, reducing cost and carbon emissions.

Literature Review on AI for Energy Forecasting

Briatore F.;
2024-01-01

Abstract

Energy management is a current topic due to the rising of costs, and climate change. This paper aims to study Artificial Intelligence (AI) to make energy consumption predictions. A deep literature review was carried out using Scopus database, clustering papers on short-and long-Term forecast. Moreover, sustainability is a major concern and energy forecasting in both short and long periods can be successfully made with Machine Learning, Neural Network, Deep Learning, and Grey models. Therefore, AI models improve energy consumption forecast and energy allocation, reducing cost and carbon emissions.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1272223
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