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Short term photovoltaic power generation forecasting using neural network

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3 Author(s)
Oudjana, S.H. ; Unite of Appl. Res. in Renewable Energy, URAER, Ghardaïa, Algeria ; Hellal, A. ; Mahamed, I.H.

Short-term photovoltaic power generation forecasting is an important task in renewable energy power system planning and operating. This paper explores the application of neural networks (NN) to study the design of photovoltaic power generation forecasting systems for one week ahead using weather databases include the global irradiance, and temperature of Ghardaia city (south of Algeria) using a data acquisition system. Simulations were run and the results are discussed showing that neural networks Technique is capable to decrease the photovoltaic power generation forecasting error.

Published in:

Environment and Electrical Engineering (EEEIC), 2012 11th International Conference on

Date of Conference:

18-25 May 2012