Weather Impact on Solar Farm Performance: A Comparative Analysis of Machine Learning Techniques

Ajith Gopi; Prabhakar Sharma; Kumarasamy Sudhakar; Wai Keng Ngui; Irina Kirpichnikova; Erdem Cuce

doi:10.3390/su15010439

Weather Impact on Solar Farm Performance: A Comparative Analysis of Machine Learning Techniques

Ajith Gopi
, Prabhakar Sharma
, Kumarasamy Sudhakar^*
, Wai Keng Ngui
, Irina Kirpichnikova
, Erdem Cuce

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

84 Citations (SciVal)

Original language	English
Article number	439
Journal	Sustainability (Switzerland)
Volume	15
Issue number	1
DOIs	https://doi.org/10.3390/su15010439
Publication status	Published (VoR) - Jan 2023

Funding

The authors are grateful for the financial support of the Universiti Malaysia Pahang (www.ump.edu.my) through grant PGRS210349. The authors are also thankful to the Russian Science Foundation grant no. 22-19-20011 support of South Ural state university.

Funders	Funder number
South Ural State University
Universiti Malaysia Pahang	PGRS210349
Russian Science Foundation	22-19-20011

Keywords

artificial intelligence
energy generation
forecasting
neuro-fuzzy
solar irradiance
solar plant

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10.3390/su15010439

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title = "Weather Impact on Solar Farm Performance: A Comparative Analysis of Machine Learning Techniques",

keywords = "artificial intelligence, energy generation, forecasting, neuro-fuzzy, solar irradiance, solar plant",

author = "Ajith Gopi and Prabhakar Sharma and Kumarasamy Sudhakar and Ngui, \{Wai Keng\} and Irina Kirpichnikova and Erdem Cuce",

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T2 - A Comparative Analysis of Machine Learning Techniques

AU - Gopi, Ajith

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AU - Ngui, Wai Keng

AU - Kirpichnikova, Irina

AU - Cuce, Erdem

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KW - artificial intelligence

KW - energy generation

KW - forecasting

KW - neuro-fuzzy

KW - solar irradiance

KW - solar plant

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U2 - 10.3390/su15010439

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Weather Impact on Solar Farm Performance: A Comparative Analysis of Machine Learning Techniques

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Keywords

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