Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications
Online ISSN : 2188-4749
Print ISSN : 2188-4730
第47回ISCIE「確率システム理論と応用」国際シンポジウム(2015年12月, ホノルル)
Dynamic time warping-based cluster analysis and support vector machine-based prediction of solar irradiance at multi-points in a wide area
Yukiya TanakaMasaki Takahashi
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ジャーナル フリー

2016 年 2016 巻 p. 210-215

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Predicting short-term solar irradiance is important to introduce solar power in an electric power system. Considering that large quantities of solar power will be introduced across wide areas in the future, this paper addresses multi-point predictions of solar irradiance. Support vector machines (SVMs) perform well for predicting solar irradiance, but involve relatively high computational complexity. In addition, prediction models should be updated regularly to adapt to the season. Here, we introduce a multi-point prediction system that reduces the amount of calculation. Rather than constructing prediction models at all grid points, this system creates certain clusters based on the dynamic time warping (DTW) distance, and then constructs a small number of models representing each cluster. Mathematically, this consists of three algorithms, DTW, cluster analysis and SVM.
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© 2016 ISCIE Symposium on Stochastic Systems Theory and Its Applications
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