PV array output power forecasting based on similar day and RBFNN

Dianli Zidonghua Shebei/Electric Power Automation Equipment

Volumn 33, Issue 1, 2013, Pages

  Wang, Xiaolan ^a,b   Ge, Pengjiang ^a  

^a LANZHOU UNIVERSITY OF TECHNOLOGY   (China)

^b KEY LABORATORY OF GANSU ADVANCED CONTROL FOR INDUSTRIAL PROCESSES   (China)

Author keywords

Forecasting; Models; Neural networks; Output power; PV array; Radial basis function networks; Similar day

Indexed keywords

AIR TEMPERATURE; FEATURE VECTORS; FORECASTING MODELS; INPUT VARIABLES; MEAN ABSOLUTE PERCENTAGE ERROR; NORTHWEST CHINA; OUTPUT POWER; PV ARRAYS; RBFNN(RADIAL BASIS FUNCTION NEURAL NETWORK); ROOT MEAN SQUARE ERRORS; SIMILAR DAY; SOLAR RADIATION INTENSITY; STRONG CORRELATION;

FORECASTING; MEAN SQUARE ERROR; MODELS; NEURAL NETWORKS; RADIAL BASIS FUNCTION NETWORKS; SOLAR RADIATION; SUN;

PHOTOVOLTAIC CELLS;

EID: 84874001291     PISSN: 10066047     EISSN: None     Source Type: Journal    
DOI: 10.3969/j.issn.1006-6047.2013.01.019     Document Type: Article

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