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Wind generating set performance assessment method based on correlation analysis

A technology for wind turbines and correlation analysis, applied in wind turbines, wind turbine monitoring, engines, etc., can solve the problems of lack of comparison means, not reaching 180 billion kWh, and different wind conditions of wind turbines. Evaluate the effect of reliable results and exclusion of influence

Inactive Publication Date: 2016-08-24
HUADIAN ELECTRIC POWER SCI INST CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In 2014, the preliminary statistics of wind power generation was more than 150 billion kwh. However, under the premise that the grid-connected installed capacity reached the expected standard, it did not reach the expected 180 billion kwh.
Although the performance of wind turbines depends intuitively on the level of their power generation, in the actual evaluation process, there are various problems such as different wind conditions between wind turbines, lack of comparison means, complex structure and control system of wind turbines, etc. , it is difficult to evaluate the performance of wind turbines based solely on the level of power generation. At present, there is no good way to evaluate wind turbines that can comprehensively consider multiple factors, which makes it impossible to analyze the poor power generation of wind power. the reason and then rectify

Method used

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  • Wind generating set performance assessment method based on correlation analysis
  • Wind generating set performance assessment method based on correlation analysis
  • Wind generating set performance assessment method based on correlation analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0045] In this embodiment, the method for evaluating the performance of wind power generators based on correlation analysis includes the following steps:

[0046] S1. Collect data through the big data platform, the data is the wind speed, power, actual power generation, turbulence intensity, wind direction and average wind speed of different types of wind turbines in time sequence;

[0047] S2. Determine the generator set to be analyzed, and extract the wind speed, power, actual power generation, turbulence intensity, wind direction and average wind speed of all models of the generator set to be analyzed from the big data platform;

[0048] S3. Use the time-ordered wind speeds of different units to perform correlation analysis on the units that need to be determined:

[0049] S31. Suppose the wind speed sequence of the generator set to be analyzed in time order is x i , the wind speed sequence of the time-ordered unit that needs to determine the correlation is y i , then the...

Embodiment 2

[0079] The present embodiment is similar to embodiment 1, and its difference only lies in:

[0080] S5. Calculate the average value of the relative power generation. When the relative power generation of the generating set to be analyzed is lower than 80% of the average generating capacity, the performance of the generating set to be analyzed is not good and urgently needs rectification, wherein k is a constant.

[0081] In step S5, the calculation method of the average value of the relative power generation is as follows:

[0082]

[0083] Wherein, n is the number of generating units screened by S4, and in this embodiment, k=0.8, when the number of generating units to be analyzed , the performance of the unit to be analyzed is poor.

[0084] The larger the value of k, the stricter the evaluation of the unit, so when k is 0.8, the evaluation of the unit is more relaxed and not strict.

Embodiment 3

[0086] This embodiment is similar to embodiment 1 and / or embodiment 2, and its difference only lies in:

[0087] S5. Calculate the average value of the relative power generation. When the relative power generation of the generating set to be analyzed is lower than 90% of the average generating capacity, the performance of the generating set to be analyzed is not good, and rectification is urgently needed, wherein k is a constant.

[0088] In step S5, the calculation method of the average value of the relative power generation is as follows:

[0089]

[0090] Wherein, n is the number of generating units screened by S4, and in this embodiment, k=0.9, when the number of generating units to be analyzed , the performance of the unit to be analyzed is poor.

[0091] The larger the value of k, the stricter the evaluation of the unit, so when k is 0.9, the evaluation of the unit is stricter.

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Abstract

The invention relates to a wind generating set performance assessment method based on the correlation analysis. The method comprises the following steps that firstly, data are collected through a big-data platform; secondly, a generating set to be analyzed is determined; thirdly, the set in which correlation needs to be determined is subjected to the correlation analysis through different unit wind speeds with time as the sequence; fourthly, a correction unit is selected, and the relative power generating amounts of the correction unit are obtained; and fifthly, the average value of the relative power generating amounts is solved, when the relative power generating amount of the generating set to be analyzed is lower than the average power generating amount (k*100)%, the performance of the generating set to be analyzed is not good enough, and the generating set to be analyzed is in urgent need of rectification, wherein k is a constant. According to the wind generating set performance assessment method, a multi-level correlation and consistency analysis method is utilized, the related unit is determined, the influence of complex wind conditions on the performance assessment is eliminated, the relative power generating amount of the related unit is directly applied to serve as the assessment standard, the influence of good and bad wind resources on power generating is eliminated, and the assessment result is more reliable.

Description

technical field [0001] The invention relates to a method for evaluating the performance of a wind power generating set, in particular to a method for evaluating the performance of a wind generating set based on correlation analysis. Background technique [0002] Wind power has developed rapidly in recent years and has received widespread attention and support. The "Twelfth Five-Year Plan" clearly stated that by 2015, the installed capacity of wind power will reach 104 million kilowatts, and by 2020 this figure will increase to 200 million kilowatts. From the actual situation, the new installed capacity in 2014 was 23.3505 million kilowatts, an increase of 45.1% over 2013, and the cumulative installed capacity was 114.76339 million kilowatts, an increase of 25.5.% over 2013. In 2014, the preliminary statistics of wind power generation was more than 150 billion kwh. However, under the premise that the grid-connected installed capacity reached the expected standard, it did not...

Claims

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Application Information

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IPC IPC(8): F03D17/00
Inventor 叶小广刘庆超孔德同孙昊于文革王志雷阳付立
Owner HUADIAN ELECTRIC POWER SCI INST CO LTD
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