A user-friendly and accurate machine learning tool for the evaluation of the worldwide yearly photovoltaic electricity production

A user-friendly and accurate machine learning tool for the evaluation of the worldwide yearly photovoltaic electricity production

While traditional methods for modelling the thermal and electrical behaviour of photovoltaic (PV) modules rely on analytical and empirical techniques, machine learning is gaining interest as a way to reduce the time, expertise, and tools required by designers or experts while maintaining high accura...

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Bibliographic Details
Main Authors: Domenico Mazzeo, Sonia Leva, Nicoletta Matera, Karolos J. Kontoleon, Shaik Saboor, Behrouz Pirouz, Mohamed R. Elkadeem
Format: Article
Language:English
Published: Elsevier 2023-12-01
Series:Energy Reports
Subjects:
Photovoltaic module
Electricity
Machine learning
Artificial neural network
PV forecasting
Validation
Online Access:http://www.sciencedirect.com/science/article/pii/S2352484723009654

Internet

http://www.sciencedirect.com/science/article/pii/S2352484723009654

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