NDLI: PV power forecasting using different Artificial Neural Networks strategies

Content Provider	IEEE Xplore Digital Library
Author	Sansa, I. Missaoui, S. Boussada, Z. Bellaaj, N.M. Ahmed, E.M. Orabi, M.
Copyright Year	2014
Description	Author affiliation: Lab. de Syst. Electr., Univ. de Tunis El Manar, Tunis, Tunisia (Sansa, I.; Missaoui, S.; Boussada, Z.; Bellaaj, N.M.) \|\| Aswan Fac. of Eng., Aswan Univ. APEARC, Aswan, Egypt (Ahmed, E.M.; Orabi, M.)
Abstract	The integration of photovoltaic (PV), intermittent and uncontrollable power, into the electrical grid has become one of the major challenges for power system operators. Therefore the PV power forecasting can be beneficial in system planning and balancing energies. In this paper the PV power forecasting of a real generator [1] is presented. Different Artificial Neural Networks (ANN) strategies are used to forecast the PV power from meteorological variables, the radiation and the temperature. Simulation results corresponding to each ANN strategy are presented, discussed and compared. The dynamic ANN chosen in this work is the Nonlinear Auto Regressive models with eXogenous input (NARX model). Its performances have proved in the different time frame PV power forecasting. The impact of season's type on the efficiency of PV power forecasting is presented in the second part of this paper.
Starting Page	54
Ending Page	59
File Size	1158350
Page Count	6
File Format	PDF
e-ISBN	9781479936021
DOI	10.1109/ICGE.2014.6835397
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-03-25
Publisher Place	Tunisia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	ANN Biological system modeling Weather forecasting NARX model Artificial neural networks Model identification Predictive models PV power forecasting Mathematical model Forecasting Equations
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
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