A Novel Hybrid Model for Short-Term Forecasting in PV Power Generation
Joint Authors
Abdul Rahman, H.
Wu, Yuan-Kang
Chen, Chao-Rong
Source
International Journal of Photoenergy
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-06-30
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
The increasing use of solar power as a source of electricity has led to increased interest in forecasting its power output over short-time horizons.
Short-term forecasts are needed for operational planning, switching sources, programming backup, reserve usage, and peak load matching.
However, the output of a photovoltaic (PV) system is influenced by irradiation, cloud cover, and other weather conditions.
These factors make it difficult to conduct short-term PV output forecasting.
In this paper, an experimental database of solar power output, solar irradiance, air, and module temperature data has been utilized.
It includes data from the Green Energy Office Building in Malaysia, the Taichung Thermal Plant of Taipower, and National Penghu University.
Based on the historical PV power and weather data provided in the experiment, all factors that influence photovoltaic-generated energy are discussed.
Moreover, five types of forecasting modules were developed and utilized to predict the one-hour-ahead PV output.
They include the ARIMA, SVM, ANN, ANFIS, and the combination models using GA algorithm.
Forecasting results show the high precision and efficiency of this combination model.
Therefore, the proposed model is suitable for ensuring the stable operation of a photovoltaic generation system.
American Psychological Association (APA)
Wu, Yuan-Kang& Chen, Chao-Rong& Abdul Rahman, H.. 2014. A Novel Hybrid Model for Short-Term Forecasting in PV Power Generation. International Journal of Photoenergy،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1037178
Modern Language Association (MLA)
Wu, Yuan-Kang…[et al.]. A Novel Hybrid Model for Short-Term Forecasting in PV Power Generation. International Journal of Photoenergy No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-1037178
American Medical Association (AMA)
Wu, Yuan-Kang& Chen, Chao-Rong& Abdul Rahman, H.. A Novel Hybrid Model for Short-Term Forecasting in PV Power Generation. International Journal of Photoenergy. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1037178
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1037178