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Reseach Article

Solar Power Forecasting: A Review

by D. K. Chaturvedi, Isha
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 145 - Number 6
Year of Publication: 2016
Authors: D. K. Chaturvedi, Isha
10.5120/ijca2016910728

D. K. Chaturvedi, Isha . Solar Power Forecasting: A Review. International Journal of Computer Applications. 145, 6 ( Jul 2016), 28-50. DOI=10.5120/ijca2016910728

@article{ 10.5120/ijca2016910728,
author = { D. K. Chaturvedi, Isha },
title = { Solar Power Forecasting: A Review },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2016 },
volume = { 145 },
number = { 6 },
month = { Jul },
year = { 2016 },
issn = { 0975-8887 },
pages = { 28-50 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume145/number6/25284-2016910728/ },
doi = { 10.5120/ijca2016910728 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:48:05.621700+05:30
%A D. K. Chaturvedi
%A Isha
%T Solar Power Forecasting: A Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 145
%N 6
%P 28-50
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The increasing demand for energy is one of the biggest reasons behind the integration of solar energy into the electric grids or networks. To ensure the efficient use of energy PV systems it becomes important to forecast information reliably. The accurate prediction of solar irradiance variation can enhance the quality of service. This integration of solar energy and accurate prediction can help in better planning and distribution of energy. Here in this paper, a deep review of methods which are used for solar irradiance forecasting is presented. These methods help in selecting the appropriate forecast technique according to the needs or requirements. This paper also presents the metrics that are used for evaluating the performance of a forecast model.

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Index Terms

Computer Science
Information Sciences

Keywords

Solar forecasting physical method statistical method hybrid method evaluation metrics.