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Wind power plant time-space dynamic correlation modeling method and system

A space-time dynamic and correlation technology, applied in the direction of instruments, data processing applications, forecasting, etc., can solve the problems that cannot reflect the characteristics of the lower tail of wind speed, achieve accurate space-time dynamic correlation, and improve the effect of matching

Inactive Publication Date: 2017-03-29
SOUTHWEST PETROLEUM UNIV
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  • Claims
  • Application Information

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Problems solved by technology

For example, literature [3] uses the Gumbel Copula function, which can only reflect the upper tail characteristics of wind speed, but cannot reflect the lower tail characteristics of wind speed; Literature [4] uses the normal Copula function, which is only suitable for describing the symmetrical correlation characteristics of wind speed

Method used

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  • Wind power plant time-space dynamic correlation modeling method and system
  • Wind power plant time-space dynamic correlation modeling method and system
  • Wind power plant time-space dynamic correlation modeling method and system

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Experimental program
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Effect test

Embodiment 1

[0035] Through the probability distribution model of wind speed, combined with the relationship between wind speed and wind generator output power, the probability distribution model of wind generator output is obtained, so as to determine the wind power stochastic model of the wind farm.

[0036] Such as figure 1 As shown, the method for modeling the spatial-temporal dynamic correlation of wind farms disclosed in Embodiment 1 of the present invention includes the following steps:

[0037] Step 101: Obtain the probability density function of the first parameter of wind speed according to the historical measured wind speed samples of the wind farm

[0038] The probability distribution model of wind speed is the basis of wind energy resource analysis. In recent years, a large number of literatures have been studied on the probability distribution of wind speed, and different theoretical distributions are used to fit the wind speed. The main theoretical distributions are: Weibull...

Embodiment 2

[0070] Taking the wind speed of a certain period of time in a wind farm as an example, the correlation of wind speed is analyzed by constructing a mixed Copula function. Based on the historical measured data of the wind speed of the wind farm in a certain period of time, the maximum expectation algorithm is used to estimate the parameters of the hybrid Copula function, and the obtained parameter estimate θ i and the corresponding weight coefficient ω i , as shown in Table 1 below:

[0071] Table 1

[0072]

[0073] In order to quantitatively evaluate the accuracy of the wind farm correlation model, the relative error index ε and the root mean value (Average Root Mean Square, ARMS) index ξ of the sum of variances are used to evaluate the accuracy of the built model. The calculation formulas of indexes ε and ξ are as follows.

[0074]

[0075]

[0076] where P wf is the simulated total active power of wind power, P wr for the actual value. P wfi and P wri are th...

Embodiment 3

[0082] Such as image 3 As shown, a wind speed probability distribution modeling system disclosed in an embodiment of the present invention includes: a sample storage module with a central processing unit and a running memory connected through a local area network, a wireless access network, etc. or a network bus interface, and a probability distribution Calculation module, hybrid Copula function construction module, and probability distribution model establishment module.

[0083] Among them, the sample storage module is used to store historical measured wind speed samples;

[0084]The probability distribution calculation module is used to obtain the probability density function of the first parameter of wind speed according to the historical measured wind speed samples of the wind farm; according to the relationship between the wind speed and the output power of the wind power generator, the probability density function of the active output of the wind power generator is obt...

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Abstract

The invention discloses a wind power plant time-space dynamic correlation modeling method and system. Through constructing a hybrid Copula function describing time-space dynamic correlation between a wind speed and aerogenerator active output, according to historical actual measurement wind speed samples of a wind power plant, parameter estimation values and corresponding weight coefficients of sub Copula functions in the hybrid Copula function are obtained; and through the constructed hybrid Copula function and a relation between the wind speed and aerogenerator output power, a wind power output distribution function with correlation is obtained, such that time-space dynamic correlation between the wind speed of the wind power plant and the aerogenerator output power can be more accurately described, and the matching degree with the actual wind speed of the wind power plant is improved.

Description

technical field [0001] The invention relates to the technical field of wind power generation, in particular to a method and system for modeling the temporal-spatial dynamic correlation of a wind farm. Background technique [0002] Due to its mature technology and good economy, wind power has become one of the fastest growing renewable energy sources in recent years. As of 2015, the installed capacity of wind power put into operation in my country reached 100 million kilowatts, and the average annual wind power generation accounted for more than 3% of the country's total power generation, reaching 190 billion kwh. At present, my country's wind power mainly adopts a centralized large-scale development method. Among them, the installed capacity of wind power in the areas where large-scale wind power bases such as Hebei, Mengdong, Mengxi, Gansu Jiuquan, Jilin, Jiangsu Coast and Shandong Coast reached 79 million kilowatts, and the installed capacity of offshore wind power reached...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06
Inventor 李茜何豪张安安林钰曾蕊张珂嘉张阳李中云左芸裴葛茗瑞陈位发
Owner SOUTHWEST PETROLEUM UNIV
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