Zahare, Syazwani and Sulaiman, Shahril Irwan
(2014)
Solar irradiance forecasting model using Artificial Neural Network (ANN): article.
Abstract
This paper presents the Artificial Neural Network (ANN) model for predicting solar irradiance. The inputs of the ANN are the solar irradiance values for previous five one-minute intervals while the output of the ANN is the solar irradiance of the sixth-minute interval. The solar irradiance data were obtained from a weather monitoring station at Green Energy Research Centre (GERC) at Universiti Teknologi MARA, Malaysia. During testing, the ANN produced a low mean absolute percentage error (MAPE) of 10.5796% and high coefficient of determination, R2 of 0.8925.
Metadata
| Item Type: | Article |
|---|---|
| Creators: | Creators Email / ID Num. Zahare, Syazwani UNSPECIFIED Sulaiman, Shahril Irwan UNSPECIFIED |
| Subjects: | T Technology > T Technology (General) T Technology > TK Electrical engineering. Electronics. Nuclear engineering |
| Divisions: | Universiti Teknologi MARA, Shah Alam > Faculty of Electrical Engineering |
| Keywords: | Artificial Neural Network (ANN), Solar Irradiance (SI), Coefficient of Determination (R2), Mean Absolute Percentage Error (MAPE), Prediction. |
| Date: | January 2014 |
| URI: | https://ir.uitm.edu.my/id/eprint/126800 |
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