期刊
SOLAR ENERGY
卷 98, 期 -, 页码 226-235出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.solener.2013.10.002
关键词
Photovoltaic systems; Produced power; Forecasting; SARIMA; SVM; Hybrid SARIMA-SVM model
资金
- TWAS [Ref.09-108 RG/REN/AF/AC_C: UNESCO FR: 3240231224]
In this work, a new hybrid model for short-term power forecasting of a grid-connected photovoltaic plant is introduced. The new model combines two well-known methods: the seasonal auto-regressive integrated moving average method (SARIMA) and the support vector machines method (SVMs). An experimental database of the power produced by a small-scale 20 kWp GCPV plant is used to develop and verify the effectiveness of the proposed model in short-term forecasting. Hourly forecasts of the power produced by the plant were carried out for a few days showing a quite good accuracy. A comparative study has also been introduced showing that the developed hybrid model performs better than both the SARIMA and the SVM model. (C) 2013 Elsevier Ltd. All rights reserved.
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