A wind power quality trend prediction method

A power quality and trend forecasting technology, applied in forecasting, instrumentation, data processing applications, etc., can solve problems such as lack of research on power quality trend forecasting at power quality monitoring points, avoid further deterioration, reduce economic losses, and improve safety and reliability. Effect

Inactive Publication Date: 2016-03-09
SOUTHEAST UNIV
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Problems solved by technology

[0003] At present, the research on power quality mainly focuses on data acquisition methods or the basic processing of collected data. These researches mainly include power quality monitoring devices and methods, and power quality evaluation. Lack of research on the prediction of power quality trends at grid-connected points of interference sources

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  • A wind power quality trend prediction method
  • A wind power quality trend prediction method
  • A wind power quality trend prediction method

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Embodiment Construction

[0042] The technical solution of the present invention will be further described below in conjunction with the accompanying drawings. The overall flow of wind power quality trend prediction method is as follows: figure 1 shown.

[0043] 1) Establish wind power quality trend prediction index system. Firstly, analyze the characteristics of power quality problems caused by the operating characteristics of wind turbines and changes in operating conditions. Due to changes in wind speed and inherent characteristics of wind turbines (wind shear, tower shadow effect, blade gravity deviation and yaw error, etc.) Point of Common Coupling (Point of Common Coupling, point of common connection, that is, grid-connected point, referred to as PCC point) voltage fluctuation; at the same time, the power electronic device in the wind turbine will cause a large number of harmonics in the power grid during operation. Based on the above analysis, combined with my country's power quality standards...

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Abstract

The invention discloses a wind power quality trend predicting method. The wind power quality trend predicting method includes steps of 1), establishing a power quality trend predicting index system; 2) acquiring data; 3), establishing 'corresponding working condition relation table' of a probability density distribution model of historical monitoring data of power quality trend prediction indexes and wind speed / wind direction data corresponding to the probability density distribution model; 4) matching and analyzing working conditions; and 5) predicting power quality trends of power quality trend prediction indexes of wind power public connecting points in a certain future time and storing prediction results of power quality of various prediction indexes into a database. The wind power quality trend predicting method can predict trend of power quality of key power quality indexes of the wind power public connecting points by means of historical power quality monitoring data.

Description

technical field [0001] The invention belongs to the technical field of power quality monitoring, and relates to a power quality monitoring method for power systems and power users. Background technique [0002] Power quality can be simply defined as: the degree to which the voltage and current indicators related to the normal operation (or operation) of power supply, power consumption system and equipment deviate from the specified range. From this we can see the importance of power quality. [0003] At present, the research on power quality mainly focuses on data acquisition methods or the basic processing of collected data. These researches mainly include power quality monitoring devices and methods, and power quality evaluation. The research on the power quality trend prediction of the grid-connected point of the interference source is lacking. With the vigorous promotion of the national "Twelfth Five-Year Plan", renewable energy power generation and rail transit usher ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q50/06
Inventor 顾伟张帅袁晓冬李群王元凯
Owner SOUTHEAST UNIV
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