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Dynamic probabilistic power flow (PPF) calculating method considering wind speed predication error temporal-spatial coherence

A dynamic probabilistic power flow, spatiotemporal correlation technology, applied in computing, AC network circuits, instruments, etc., can solve problems such as large kurtosis and skewness, ignoring wind speed timing, reducing wind speed uncertainty, etc.

Inactive Publication Date: 2015-04-01
HOHAI UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Existing DPPF calculations mostly assume that the wind speed obeys the Weibull distribution, and the wind speed sequence is generated by simulating the Weibull distribution. This method does not consider the timing of the wind speed. In actual situations, the uncertainty of the wind speed can be reduced through a specific wind speed prediction method
Secondly, most of the existing studies assume that the wind speed error obeys the normal distribution. However, the actual wind speed error will have large kurtosis and skewness, and it does not always obey the normal distribution. Using the normal distribution to describe the prediction error may affect the calculation of DPPF As a result, a large error is generated, so the wind speed error distribution needs to be considered specifically for the actual situation

Method used

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  • Dynamic probabilistic power flow (PPF) calculating method considering wind speed predication error temporal-spatial coherence
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  • Dynamic probabilistic power flow (PPF) calculating method considering wind speed predication error temporal-spatial coherence

Examples

Experimental program
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Effect test

Embodiment 1

[0065] Take the IEEE14 node system as an example, such as figure 2 As shown, wind farms with a rated power of 50MW are added to the nodes 10, 11, 13 and 14 of the system respectively. The fans are all operated with a constant power factor of 1, and the cut-in wind speed, rated wind speed and cut-out wind speed of the fan are respectively taken as 3m / s, 12m / s and 22m / s. Assuming that the actual power error of the wind farm obeys a normal distribution with zero mean, its probability density function is as follows:

[0066] f [ P ϵ ( v ) ] = 1 2 π · ( αv ) exp [ - ( P ϵ ...

Embodiment 2

[0077] Taking IEEE118 nodes as an example, wind farms with a rated power of 50MW are added to nodes 20, 35, 38 and 51 respectively. The wind farm and wind speed model are the same as those in Example 1. On the basis of the original load, the active load of 200MW is increased proportionally, and the load model is the same as Section 3.1. Considering the spatial correlation of active load prediction errors among nodes 2, 3, 4, and 5, the spatial correlation coefficient of load prediction errors at different locations is 0.5, and the value of time correlation is the same as that in Embodiment 1.

[0078] Such as Figure 8 As shown, the obtained dynamic probability distribution curve of active power between branches 19-20. Such as Figure 9 As shown, there are 500 sample function curves of active power between branches 19-20.

[0079] From Figure 8 and Figure 9 It can be seen that the DPPF calculation based on LHS can obtain the dynamic characteristics of the branch power ...

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Abstract

The invention discloses a dynamic probabilistic power flow (PPF) calculating method considering wind speed predication error temporal-spatial coherence. The method is to analyze the node voltage and dynamic probability distribution of branch power flow of a wind power station built power system, so as to enable operators to analyze a system state conveniently. The method comprises the steps of describing the input variable predication error process according to autocorrelation coefficient stationary process; directly fitting to obtain the predication error distribution on the basis of nonparametric kernel density estimation and according to historical predication error data; performing Nataf transformation technology on the basis of the iso-probability transformation theory to obtain an error sample of temporal-spatial coherence; performing dynamic PPF calculation by the monte carlo simulation method on the basis of latin hypercube sampling so as to obtain the node voltage amplitude value and the digital characteristics and dynamic probability distribution of the branch power flow. By adopting the method, the node voltage and the dynamic probability distribution of the branch power flow can be effectively analyzed; the method has the advantages of being accurate in result and convenient to realize.

Description

technical field [0001] The invention belongs to the technical field of power system operation analysis and control, and relates to a dynamic probabilistic power flow calculation method that takes into account the time-space correlation of wind speed prediction errors. technical background [0002] In recent years, wind power, as a pollution-free and renewable green energy, has been more and more widely used all over the world. There are many uncertainties in the actual power system, and the grid connection of wind farms further exacerbates the uncertainty. It has become a hot spot in the academic circle to study the influence of this uncertainty on the system. [0003] Probabilistic power flow (PPF) is an effective means of dealing with uncertainty. Since it was proposed in 1974, many scholars have proposed various PPF methods for solving uncertainties such as wind speed and load, as well as dealing with the correlation of input variables. s method. The dynamic probability...

Claims

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Application Information

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IPC IPC(8): H02J3/00G06F19/00
CPCH02J3/00H02J2203/20Y02A30/00
Inventor 孙国强李逸驰卫志农孙永辉高楷楚云飞李春
Owner HOHAI UNIV
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