Method for constructing joint probability distribution function of output of a plurality of wind power plants

A joint probability distribution and cumulative distribution function technology is applied in the field of wind power distribution to achieve the effect of improving prediction accuracy, improving economy and improving operation level

Active Publication Date: 2013-02-27
HUAZHONG UNIV OF SCI & TECH
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[0003] In view of the defects of the prior art, the purpose of the present invention is to provide a method for constructing a joint probability distribution func

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  • Method for constructing joint probability distribution function of output of a plurality of wind power plants
  • Method for constructing joint probability distribution function of output of a plurality of wind power plants
  • Method for constructing joint probability distribution function of output of a plurality of wind power plants

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[0032] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0033] refer to figure 1 As shown, the present invention provides a method for constructing a joint probability distribution function of multiple wind farm output, which specifically includes the following steps:

[0034] (1) Determine the probability distribution function of each wind farm output, the calculation method is as follows:

[0035] let x i (i=1, 2, ..., N) is a historical data sample of wind farm output, and the probability density function f(x) and cumulative distribution function F at any point x are calculated according to formulas (1)-(4) (x); f ( ...

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Abstract

The invention discloses a method for constructing a joint probability distribution function of output of a plurality of wind power plants. The method comprises calculating a probability density function, a cumulative distribution function and a cumulative distribution function value of output of M wind power plants according to output samples of the wind power plants; obtaining a copula function through a maximum likelihood method; determining each copula function according to parameters; obtaining an experience copula function value according to the cumulative distribution function and the cumulative distribution function value; calculating a copula function value corresponding to the cumulative distribution function according to each copula function; obtaining an Euclidean space distance between the copula function value and the experience copula function value according to the copula function value and the experience copula function value; determining the copula function corresponding to a minimum Euclidean distance to describe dependency of output of the wind power plants; and calculating the joint probability distribution function and the joint probability density distribution function of output of the plurality of wind power plants according to the selected copula function.

Description

technical field [0001] The invention belongs to the technical field of wind power generation and distribution, and more specifically relates to a method for constructing a joint probability distribution function of the output of multiple wind farms. Background technique [0002] With the large-scale development and utilization of wind energy in my country, wind power has developed rapidly and installed capacity has grown rapidly. The uncertainty of wind resources makes the output power of wind farms intermittent and fluctuating. The connection of large-scale wind power will inevitably bring difficulties to the safe and stable operation of the power system. The difficulty of wind power grid integration has become a focus of attention. Mastering the random probability distribution characteristics of wind farm output and the joint probability distribution characteristics of multiple wind farm outputs is of great significance to improve the prediction accuracy of wind farm outpu...

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Application Information

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IPC IPC(8): G06F17/10
Inventor 黎静华文劲宇程时杰
Owner HUAZHONG UNIV OF SCI & TECH
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