Hybrid solar forecasting method uses satellite imaging and ground telemetry as inputs to ANNs

Solar Energy

Volumn 92, Issue , 2013, Pages 176-188

  Marquez, Ricardo ^a   Pedro, Hugo T C ^b   Coimbra, Carlos F M ^b  

^a University of California   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Artificial neural networks; Hybrid methods; Remote sensing; Solar forecasting; Stochastic learning

Indexed keywords

FORECASTING SKILL; HYBRID METHOD; SAN JOAQUIN VALLEY; SATELLITE IMAGE ANALYSIS; SATELLITE IMAGING; SOLAR FORECASTING; SOLAR IRRADIANCES; STOCHASTIC LEARNING;

IMAGE PROCESSING; NEURAL NETWORKS; REMOTE SENSING; SATELLITES; SOLAR RADIATION; STOCHASTIC SYSTEMS;

FORECASTING;

ARTIFICIAL NEURAL NETWORK; FORECASTING METHOD; GEOGRAPHICAL DISTRIBUTION; GROUND-BASED MEASUREMENT; IMAGE PROCESSING; IRRADIANCE; LEARNING; REMOTE SENSING; SATELLITE DATA; SATELLITE IMAGERY; SOLAR RADIATION; STOCHASTICITY;

CALIFORNIA; SAN JOAQUIN VALLEY; UNITED STATES;

EID: 84876344167     PISSN: 0038092X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.solener.2013.02.023     Document Type: Article

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