Modeling climate parameters for renewable energy applications in the UAE using neural networks

2009 CIGRE/IEEE PES Joint Symposium Integration of Wide-Scale Renewable Resources into the Power Delivery System, CIGRE/PES 2009

Volumn , Issue , 2009, Pages

  El Chaar, L ^a   Lamont, L A ^a   Karkoub, M ^a  

^a KHALIFA UNIVERSITY   (United Arab Emirates)

Author keywords

Empirical models; Feedforward neural network; Meteorological; Neural networks; Prediction methods; Solar energy; Solar radiation; Wind energy

Indexed keywords

ABU DHABI; CLIMATE PARAMETERS; EMPIRICAL MODELS; FEED-FORWARD BACK PROPAGATION; GLOBAL SOLAR RADIATION; METEOROLOGICAL; NEURAL NETWORK TECHNIQUES; PHOTOVOLTAICS; PREDICTION METHODS; PREDICTION MODEL; RENEWABLE ENERGY APPLICATIONS; UNITED ARAB EMIRATES; WIND ENERGY; WIND SPEED;

ARTIFICIAL INTELLIGENCE; DIELECTRIC PROPERTIES; ELECTRIC POWER TRANSMISSION; ELECTROMAGNETIC WAVES; POTENTIAL ENERGY; POTENTIAL ENERGY SURFACES; SOLAR ENERGY; SOLAR RADIATION; SUN; WIND POWER;

FEEDFORWARD NEURAL NETWORKS;

EID: 70449368550     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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