@article{(Open Science Index):https://publications.waset.org/pdf/7156,
	  title     = {Power Forecasting of Photovoltaic Generation},
	  author    = {S. H. Oudjana and  A. Hellal and  I. Hadj Mahammed},
	  country	= {},
	  institution	= {},
	  abstract     = {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.},
	    journal   = {International Journal of Electrical and Computer Engineering},
	  volume    = {7},
	  number    = {6},
	  year      = {2013},
	  pages     = {627 - 631},
	  ee        = {https://publications.waset.org/pdf/7156},
	  url   	= {https://publications.waset.org/vol/78},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 78, 2013},