A 24-h forecast of solar irradiance using artificial neural network: Application for performance prediction of a grid-connected PV plant at Trieste, Italy

Solar Energy

Volumn 84, Issue 5, 2010, Pages 807-821

  Mellit, Adel ^a   Pavan, Alessandro Massi ^b  

^a UNIVERSITY OF JIJEL   (Algeria)

^b UNIVERSITY OF TRIESTE   (Italy)

Author keywords

Forecasting; Grid connected PV plant; MLP; Solar irradiance

Indexed keywords

AIR TEMPERATURE; ARTIFICIAL NEURAL NETWORK; CHARGE CONTROLLERS; CLOUDY DAYS; CONTROL ALGORITHMS; CORRELATION COEFFICIENT; CROSS VALIDATION; EXPERIMENTAL DATABASE; GENERALIZATION CAPABILITY; GRID-CONNECTED; GRID-CONNECTED PV; MLP; MULTI LAYER PERCEPTRON; PERFORMANCE PREDICTION; PHOTOVOLTAIC PLANT; POWER DISPATCHING; PRACTICAL METHOD; PRESENT VALUE; RENEWABLE ENERGIES; SOLAR IRRADIANCES; STAND -ALONE; TRIESTE;

ALGORITHMS; ATMOSPHERIC TEMPERATURE; ELECTRIC LOAD FORECASTING; HYBRID SYSTEMS; NEURAL NETWORKS; SOLAR POWER GENERATION; SOLAR RADIATION;

SOLAR ENERGY;

AIR TEMPERATURE; ALGORITHM; ARTIFICIAL NEURAL NETWORK; DATABASE; ELECTRICITY GENERATION; ENERGY PLANNING; FORECASTING METHOD; IRRADIANCE; NUMERICAL MODEL; PHOTOVOLTAIC SYSTEM; POWER PLANT; RENEWABLE RESOURCE; SOLAR POWER;

FRIULI-VENEZIA GIULIA; ITALY; TRIESTE [FRIULI-VENEZIA GIULIA];

EID: 77949876934     PISSN: 0038092X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.solener.2010.02.006     Document Type: Article

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