Method for calibrating the output correlation of wind power plants
A wind farm and correlation technology, which is applied in the verification field of wind farm output correlation, can solve problems such as non-unique Copula function, difficult and time-consuming correlation measurement of wind farm output correlation model, etc., to ensure stable and economical operation Effect
Active Publication Date: 2020-01-17
NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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Problems solved by technology
In fact, the empirical Copula function is discontinuous, the Copula function determined based on the empirical method may not be unique, and the empirical Copula function distribution is only an approximation of the real distribution, no matter how large the sample size is, there will always be a certain gap between the two
In addition, there is no analytic expression for the empirical Copula function. When the amount of data information is large, it will take a long time to use this method to select a reasonable Copula function, or even get into trouble.
So far, how to establish an accurate wind farm output correlation model for correlation measurement is still a major difficulty
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[0050] The invention provides a method for verifying the output correlation of wind farms, aiming to solve the problems of selection difficulty and troublesome parameter determination faced by conventional Copula functions in output prediction, and can more accurately and conveniently determine the correlation characteristics of wind farm output.
[0051] Technical solution of the present invention comprises the following steps:
[0052] (1) In order to accurately obtain the probability density function of wind farm output, the non-parametric kernel density estimation method is used to calculate the window width value that affects the fitting accuracy of wind power output sequence. The process is as follows:
[0053] Let the output sample sequence of two wind farms be ω 1r ,ω 2r ,L,ω nr (r=1,2), using the Gauss kernel function to establish the following optimization model
[0054]
[0055] This model can be used to accurately calculate the window width h of two wind far...
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The invention discloses a method for calibrating the output correlation of wind power plants, and the method comprises the following steps: a, taking the historical output of the wind power plants assample data, and solving the probability density functions of the outputs of the two wind power plants through a non-parametric kernel density estimation method; b, calculating cumulative distributionfunction values of the two wind power plants; d, solving a joint probability density function and a joint distribution function H (u1, u2) of the two wind power plants by adopting multi-dimensional kernel density estimation; e, calculating a Spearman rank correlation coefficient and a Kendall rank correlation coefficient of an output sequence between different wind power plants; and f, comparingthe rank correlation coefficient with a set threshold value to obtain whether the output of the multiple wind power plants has correlation and a conclusion of the correlation. The method can effectively reflect the correlation characteristics of the wind power plant output, indicates the synchronization probability of the multi-wind power plant output, presents a multi-wind power plant output scene, and is of great significance for ensuring the stable and economic operation of a wind power grid-connected power system.
Description
technical field [0001] The invention relates to a test method for output correlation of a wind farm, belonging to the technical field of power generation. Background technique [0002] At present, wind power energy has been developed and utilized on a large scale, and the installed capacity of wind power has grown rapidly. By the end of 2017, my country's installed wind power capacity had reached 188.3GW. Due to the randomness and volatility of wind power, large-scale wind power grid integration will inevitably have a certain impact on the safe and stable operation of the power system. With the continuous expansion of the scale of wind farms, there are often multiple wind farms in the same area, and the wind power output of these wind farms has a certain correlation, especially the wind farms that are closer to each other are generally in the same wind speed zone. Field output not only has randomness in time, but also has strong correlation in space. The distribution of w...
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IPC IPC(8): G06F30/20G06F111/08G06F113/06
Inventor 徐玉琴孙坤宇
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)