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Time-Frequency Domain Modeling Method of Wind Farm Based on Empirical Mode Decomposition

A technology of empirical mode decomposition and modeling method, which is applied in the field of wind farm grid-connected impact analysis, and can solve problems such as difficulty in finding corresponding relationships, unfavorable analysis of wind farm grid-connected impacts, and inability to reproduce output power fluctuation characteristics. The effect of high reliability, clear observation and analysis

Inactive Publication Date: 2017-03-08
INST OF ELECTRICAL ENG CHINESE ACAD OF SCI +2
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Problems solved by technology

However, due to the existence of inertia and smoothing effects inside the wind farm, it is difficult to find an accurate correspondence between the input wind speed and the output power, so that the equivalent model cannot reproduce the fluctuation characteristics of the output power
This is extremely unfavorable for the analysis of the impact of wind farm grid connection

Method used

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  • Time-Frequency Domain Modeling Method of Wind Farm Based on Empirical Mode Decomposition
  • Time-Frequency Domain Modeling Method of Wind Farm Based on Empirical Mode Decomposition
  • Time-Frequency Domain Modeling Method of Wind Farm Based on Empirical Mode Decomposition

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Embodiment Construction

[0047] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0048] The concrete steps of modeling method of the present invention are as follows:

[0049] 1. Acquisition of wind farm active power data

[0050] Collect the output power P of each unit in a wind farm in a wind farm wind_i (t), and summed up, the result is the total output power P of the wind farm wind_f (t), namely:

[0051]

[0052] 2. Normalization processing

[0053] Select the total rated output power Pe(t) of the wind farm as the base value, for the P obtained in step 1 wind_f (t) Perform normalization processing to obtain data

[0054] 3. Data filtering processing

[0055] For the discrete sequence P obtained in step 2 or (t) Generating the power spectrum by a numerical method, observing P or (t) Frequency distribution, select a reasonable low-pass digital filter pair P or (t) is filtered to filter out the interference ...

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Abstract

The invention relates to a wind farm time-frequency domain modeling method based on empirical mode decomposition (EMD). The method comprises the steps that obtained measured data of wind farm power is processed through EMD into a plurality of intrinsic mode functions (IMF) after being subjected to normalized filtering processing, hilbert transform is carried out on the IMFs respectively to generate corresponding time-frequency spectra, then the time-frequency spectra are respectively fitted, the fitting results are respectively subjected to hilbert transform to obtain time domain expressions, and the time domain expressions are summed to obtain a wind farm analytical model containing various fluctuation characteristics. According to the modeling method disclosed by the invention, the analytical model established in a time-frequency domain modeling means contains the typical fluctuation characteristic information of the wind farm, and the model is used for simulating the impact analysis of wind farm fluctuation with nonstationary randomness on network voltage and frequency.

Description

technical field [0001] The invention relates to the technical field of wind farm grid connection impact analysis, in particular to the establishment of a wind farm reliable model including fluctuation information. Background technique [0002] Empirical Mode Decomposition (EMD) is a component of HHT (Hilbert-HuangTransform), which was published by Norden E. Huang and Steven R. Long in 1998, "The Empirical Mode Decomposition and the A method for dealing with non-stationary signals proposed in Hilbert Spectrum for Nonlinear and Non-stationaryTime Series Analysis". The function of EMD is to decompose the non-stationary signal into a number of intrinsic mode functions IMF (intrinsic Mode Function) that satisfy the Hilbert transform, and perform Hilbert transform on these IMFs to obtain the distribution of the time-frequency spectrum of the signal. EMD is fully self-adaptive, and can adaptively generate "basis" according to specific signals, that is, the IMF generated by the "sc...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/50
CPCY02E60/00
Inventor 唐西胜胡枭苗福丰贺惠民吴涛李善颖
Owner INST OF ELECTRICAL ENG CHINESE ACAD OF SCI
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