Analysis of Wind Turbine Output Power Characteristic Based on Cloud Model

doi:10.3901/JME.2017.22.198

Abstract

Abstract: The performance of the wind turbine has a direct impact on the safety production and economic benefit of the wind farm. The output power is one of the most important and representative performance indexes of the wind turbine. The wind power curve is the most direct expression of its electricity-generating capacity. Using the output power and wind speed as the data source, the characteristic value of cloud model is adopted to study the fluctuation characteristics of output power, which is beneficial to learning the production status of the wind turbine. Based on the data sieving of the wind speed and power data collected by wind turbine SCADA system, a scatter plot is drawn to describe the wind speed and power in the normal working state of the wind turbine, and the actual wind power curve of wind turbine is established by method of bins. The overall power cloud of different units can be obtained through the statistical analysis of the output power of different wind speed ranges and the output power cloud model of different wind speeds that is constructed by the reverse cloud generator. The output power size, the fluctuation range and the degree of dispersion are quantitatively analyzed through comparing the characteristic value of the power cloud. At the same time, the correlation coefficients of wind speed and power are calculated to reflect and evaluate the sensitivity of the wind turbine response. The application of cloud model allows the evaluation of unit state to develop from a qualitative one to a quantitative one, from a comprehensive macro assessment to a precise assessment based on different wind speed range segments. In this way, it improves the accuracy and comprehensiveness of wind turbine performance analysis. Lastly, an applied example is used to prove the effectiveness and reliability of the algorithm.

Key words: cloud model, output power, performance analysis, sensitivity, volatility, wind turbine

CLC Number:

TM614

DONG Xinghui, ZHANG Xinmiao, ZHANG Guang, WANG Shuai. Analysis of Wind Turbine Output Power Characteristic Based on Cloud Model[J]. Journal of Mechanical Engineering, 2017, 53(22): 198-205.

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