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Wind power plant output power short-term prediction method

A technology for output power and short-term forecasting, applied in forecasting, instrumentation, data processing applications, etc., can solve problems such as low precision, achieve high precision, convenient calculation, and less sample data

Inactive Publication Date: 2017-03-15
STATE GRID CORP OF CHINA +2
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present invention proposes a short-term prediction method for wind farm output power in order to solve the problem of low accuracy of existing prediction methods

Method used

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  • Wind power plant output power short-term prediction method
  • Wind power plant output power short-term prediction method
  • Wind power plant output power short-term prediction method

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Experimental program
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Effect test

specific Embodiment approach 1

[0015] Specific implementation mode one: as figure 1 As shown, a short-term prediction method of wind farm output power includes the following steps:

[0016] Gray system theory defines gray derivatives and gray differential equations based on concepts such as associative space and smooth discrete functions, and then uses discrete data columns to establish a dynamic model in the form of differential equations, which is called Gray Model (GM for short). The gray model is a model that takes random variables as the research object, and regards random variables as a gray process that changes within a certain range and is related to time.

[0017] Step 1: Input the original sequence of historical data as input data; the original sequence of historical data is the historical power data of the wind farm;

[0018] Step 2: According to Step 1, generate an accumulation sequence and adjacent value generation sequence;

[0019] Step 3: Use the data generated in Step 2 to obtain the gray...

specific Embodiment approach 2

[0023] Specific implementation mode two: the difference between this implementation mode and specific implementation mode one is: the original sequence of numbers in the step one is:

[0024] x (0) =(X (0) (1),X (0) (2),...,X (0) (n)).

[0025] Other steps and parameters are the same as those in Embodiment 1.

specific Embodiment approach 3

[0026] Specific implementation mode three: the difference between this implementation mode and specific implementation mode one or two is that: the one-time accumulation sequence in the step two is specifically:

[0027] x (1) =(X (1) (1),X (1) (2),...,X (1) (n))

[0028] in

[0029] Other steps and parameters are the same as those in Embodiment 1 or Embodiment 2.

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Abstract

The invention relates to a wind power plant output power short-term prediction method, which is used to solve a problem of a conventional prediction method of low precision. The wind power plant output power short-term prediction method comprises steps that step 1, an original sequence of historical data is used as input data for input; step 2, a primary accumulative array and a neighborhood value generating array are generated according to the step 1; step 3, a grey differential equation is acquired by adopting the data generated according to the step 2; step 4, the parameter value of the grey differential equation is calculated by adopting a least square method; step 5, the parameter value acquired by the step 4 is introduced in the grey differential equation to acquire a white differential equation, and a prediction data value is acquired by solving the white differential equation; step 6, whether the prediction value meets a requirement is determined, and when the prediction value meets the requirement, a prediction power value is output; when the prediction value does not meet the requirement, repeated superposition calculation is carried out, until the prediction value meets the requirement, and then the value is output. The wind power plant output power short-term prediction method is suitable for the wind power generation field.

Description

technical field [0001] The invention relates to a short-term prediction method for output power of a wind farm. Background technique [0002] The randomness, volatility, and intermittency of wind power cause the grid-connected operation of large-scale wind farms to have an impact on the stability of the power system and the reliability of power supply. Accurate forecasting of wind power is beneficial to both wind farms and power grids. important meaning. [0003] Wind power forecasting can be divided into short-term, medium-term, and long-term forecasting. Short-term power forecasting refers to power forecasting within one hour in the future. Commonly used short-term prediction methods for wind power prediction include: Kalman filter method, fuzzy logic method, linear regression method, artificial neural network method, time series method, etc. Contents of the invention [0004] The invention proposes a short-term prediction method of wind farm output power in order to s...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06
Inventor 陈洪涛吴刚单小东孟祥辰陈艳孙振胜张海明李伟李军韩显华李冬梅黄树春赵强李一凡韩兆婷
Owner STATE GRID CORP OF CHINA
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