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Wind turbine generator power characteristic evaluation method based on cloud model and optimal combination empowerment

A wind turbine, optimal combination technology, applied in the direction of instruments, complex mathematical operations, data processing applications, etc., can solve problems such as volatility, power grid configuration and control difficulties, and randomness of wind power generation

Pending Publication Date: 2020-07-28
HUNAN UNIV
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] (2) Wind power generation has significant randomness and volatility, which poses a challenge to the original dispatching mode of the power system
With the large-scale integration of wind farms into the grid, it is becoming more and more difficult to configure and control backup in grid operation scheduling

Method used

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  • Wind turbine generator power characteristic evaluation method based on cloud model and optimal combination empowerment
  • Wind turbine generator power characteristic evaluation method based on cloud model and optimal combination empowerment
  • Wind turbine generator power characteristic evaluation method based on cloud model and optimal combination empowerment

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Experimental program
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Embodiment 1

[0161] The following will combine Figure 1-Figure 3 The technical scheme of the present invention is described in further detail.

[0162] In step S1, the Thompsontau-quartile method is used to identify and clean the abnormal wind speed-power operation data of the wind turbine to obtain a normal wind speed-power data set.

[0163] Step S2, according to the wind speed-power normal data scatter diagram, the annual power generation of the computer group, the average value of the power standard deviation below the rated wind speed, the average value of the power standard deviation above the rated wind speed, and the maximum value of the power coefficient below the rated wind speed.

[0164] Taking a wind turbine with a rated power of 1500kw as an example, the following are the measured data and related parameters of the wind turbine.

[0165] Table 1 The evaluation index parameters of wind turbines

[0166]

[0167] Step S3, using the entropy weight method and the comparativ...

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Abstract

The invention discloses a wind turbine generator power characteristic evaluation method based on a cloud model and optimal combination empowerment. The method comprises the steps: 1, acquiring a normal wind speed-power data set; 2, according to the wind speed-power normal data set, determining an evaluation factor set of the power characteristics of the wind turbine generator, wherein the evaluation factor set comprises annual power generation capacity of the wind turbine generator, a power standard deviation average value below the rated wind speed, a power standard deviation average value above the rated wind speed and a power coefficient maximum value below the rated wind speed; and 3, obtaining a comprehensive evaluation result. The method is easy to implement, and scientific, effective and reasonable operation of the wind power plant is guaranteed.

Description

technical field [0001] The invention relates to a method for evaluating the power characteristics of wind turbines based on cloud models and optimal combination weighting. Background technique [0002] With the increasing installed capacity of wind power and the continuous expansion of the installed capacity of a single wind farm, as well as the structure and characteristics of wind power itself, the impact of wind farms on the power grid will become more and more obvious. Wind turbines are faced with problems such as harsh operating environment and high maintenance costs. Timely and accurate monitoring and evaluation of the operating status of the unit to effectively avoid failures is of great importance for the optimal maintenance of wind farms and the safe grid connection of large-scale wind farms. significance. Due to the long-term work of wind turbines under the action of alternating loads and the harsh working environment, it is inevitable that the units will fail dur...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06Q50/06G06F17/16G06F17/18
CPCG06Q10/06393G06Q50/06G06F17/16G06F17/18Y04S10/50Y02E40/70
Inventor 高云鹏邹同华伊慧娟吴聪夏睿曹一家滕召胜黎灿兵朱彦卿王娜
Owner HUNAN UNIV
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