Using artificial neural networks to estimate solar radiation in Kuwait

Renewable and Sustainable Energy Reviews

Volumn 72, Issue , 2017, Pages 434-438

  Bou Rabee, Mohammed ^a   Sulaiman, Shaharin A ^b   Saleh, Magdy Saad ^c   Marafi, Suhaila ^d  

^a Public Authority for Applied Education and Training   (Kuwait)

^b DEPARTMENT OF CHEMICAL ENGINEERING   (Malaysia)

^c Public Authority for Applied Education and Training   (Kuwait)

^d Ministry of Electricity and Water Kuwait   (Kuwait)

Author keywords

Electrical grid; Photovoltaic; Solar electricity generation; Solar radiation

Indexed keywords

ELECTRIC NETWORK PARAMETERS; ELECTRIC POWER TRANSMISSION NETWORKS; ENERGY POLICY; FOSSIL FUELS; NEURAL NETWORKS; SOLAR ENERGY; SOLAR ENERGY CONVERSION; SOLAR POWER GENERATION;

ELECTRIC GRIDS; ELECTRICAL GRIDS; ELECTRICITY-GENERATION; PENETRATION LEVEL; PHOTOVOLTAICS; RENEWABLE ENERGIES; RENEWABLE ENERGY SOURCE; SOLAR ELECTRICITY; SOLAR ELECTRICITY GENERATION; SUNSHINE HOUR;

SOLAR RADIATION;

EID: 85009461599     PISSN: 13640321     EISSN: 18790690     Source Type: Journal    
DOI: 10.1016/j.rser.2017.01.013     Document Type: Review

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