Power Generation Technology ›› 2020, Vol. 41 ›› Issue (6): 617-624.DOI: 10.12096/j.2096-4528.pgt.19126

• New and Renewable Energy • Previous Articles     Next Articles

Analysis of the Influence of Atmospheric Pressure Difference on Spatial Correlation Prediction of Wind Speed

Zhengling YANG1(), Ruxue WAGN1(), Jian QIAO1(), Xi ZHANG1, Zhao YANG1, Jun ZHANG2   

  1. 1 School of Electrical and Information Engineering, Tianjin University, Nankai District, Tianjin 300072, China
    2 Key Laboratory of Process Measurement and Control(Tianjin University), Nankai District, Tianjin 300072, China
  • Received:2020-06-29 Published:2020-12-31 Online:2021-01-12
  • Supported by:
    National Natural Science Foundation of China-State Grid Corporation of China Joint Fund Project(U1766210)

Abstract:

Spatial correlation prediction of wind speed is an effective method for wind power prediction. In order to improve the effect of spatial correlation prediction of wind speed, the basic equations of atmospheric motion in dynamic meteorology were analyzed, and pressure gradient force, Earth gravity force and the friction force are the basic forces of atmospheric motion. In the time scale of short-term and super-short-term wind power prediction, gravity and friction of the earth can usually be regarded as known quantities or invariants, so pressure gradient force is the primary force causing wind. The value of development spatial correlation and prediction was quantitative analyzed on the southeastern coast of China. It shows that the spatial correlation of monsoon region in China is obviously higher than that in Europe and America, and the southeast coast of offshore wind power are significantly higher than the land, especially suitable for spatial correlation prediction. The spatial correlation of atmospheric pressure prediction is one of the reliable basics methods for prediction of monsoon wind power in China.

Key words: wind power prediction, wind speed, atmospheric pressure, pressure difference, spatial correlation

CLC Number: