Convergence of Photovoltaic Power Forecasting and Deep Learning: State-of-Art Review

Convergence of Photovoltaic Power Forecasting and Deep Learning: State-of-Art Review

<p>Deep learning (DL)-based PV Power Forecasting (PVPF) emerged nowadays as a promising research direction to intelligentize energy systems. With the massive smart meter integration, DL takes advantage of the large-scale and multi-source data representations to achieve a spectacular performanc...

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Bibliographic Details
Main Author: Mohamed Massaoudi (16888710) (author)
Other Authors: Ines Chihi (16888713) (author), Haitham Abu-Rub (16855500) (author), Shady S. Refaat (16864269) (author), Fakhreddine S. Oueslati (16888716) (author)
Published: 2021
Subjects:
Engineering
Electrical engineering
Information and computing sciences
Artificial intelligence
Machine learning
Big data
Biological system modeling
Data models
Discriminative learning
Deep learning
Deep reinforcement learning
Generative adversarial networks
Generative learning
Feature extraction
Forecasting
Photovoltaic power forecasting
Predictive models
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