Irregular distribution of wind power prediction

• Main Authors: Kun YUAN, Kaifeng ZHANG, Yaxian ZHENG, Dawei LI, Ying WANG, Zhenglin YANG
• Format: Article
• Language: English
• Published: IEEE 2018-09-01
• Series: Journal of Modern Power Systems and Clean Energy
• Subjects: Wind power prediction; Normal distribution; Irregular distribution; Distribution model
• Online Access: http://link.springer.com/article/10.1007/s40565-018-0446-9

Abstract Wind power is volatile and uncertain, which makes it difficult to establish an accurate prediction model. How to quantitatively describe the distribution of wind power output is the focus of this paper. First, it is assumed that wind speed is a random variable that satisfies the normal distribution. Secondly, based on the nonlinear relationship between wind speed and wind power, the distribution model of wind power prediction is established from the viewpoint of the physical mechanism. The proposed model successfully shows the complex characteristics of the wind power prediction distribution. The results show that the distribution of wind power prediction varies significantly with the point forecast of the wind speed.