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An Intelligent Control Method of Grid Frequency Based on Empirical Mode Decomposition

An empirical mode decomposition and power grid frequency technology, applied in neural learning methods, biological neural network models, neural architectures, etc., can solve problems that cannot meet the requirements of power system efficiency and achieve optimal power grid frequency control effects

Active Publication Date: 2022-05-13
GUANGXI UNIV
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Problems solved by technology

Therefore, the traditional single-layer frequency control framework cannot meet the power system's requirements for frequency control efficiency

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  • An Intelligent Control Method of Grid Frequency Based on Empirical Mode Decomposition
  • An Intelligent Control Method of Grid Frequency Based on Empirical Mode Decomposition
  • An Intelligent Control Method of Grid Frequency Based on Empirical Mode Decomposition

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Embodiment Construction

[0051] A power grid frequency intelligent control method based on empirical mode decomposition proposed by the present invention is described in detail in conjunction with the accompanying drawings as follows:

[0052] figure 1 It is the implementation flowchart of the method of the present invention. In order to prove the superiority of the method of the present invention, an IEEE standard two-area load frequency control simulation example including a wind power generation model, a photovoltaic power generation model and an energy storage device model is used for verification, and the inventive method is further elaborated and illustrated. The implementation steps of this embodiment are as follows:

[0053] (1) Record the frequency deviation signal data of a certain area in the two areas of the previous day. The format of the data is to sample the frequency deviation every 1 second from 0:00 to 24:00 of the current day, with a total of 86401 time nodes Record the grid frequ...

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Abstract

The present invention proposes a power grid frequency intelligent control method based on empirical mode decomposition. The method includes two modules. Learning method and control module of deep neural network, while proposing a two-layer step-by-step frequency control framework. First, the decomposition module decomposes the grid frequency signal into multiple modal components in real time to highlight the regularity of the signal. Secondly, the control module adjusts the output of the generator set according to the high-frequency signal and low-frequency signal of the modal component to maintain the stability of the grid frequency. Finally, in a power grid with multiple units, the decomposition module and the control module can be effectively applied in a two-layer step-by-step frequency control framework to obtain optimal control performance.

Description

technical field [0001] The invention belongs to the field of power grid frequency control, and relates to a frequency control method based on artificial intelligence technology, which is suitable for secondary frequency regulation of power systems. Background technique [0002] Frequency stability is one of the important indicators to measure the power quality of the power grid. Frequency adjustment can generally be divided into primary frequency modulation, secondary frequency modulation and tertiary frequency modulation according to the frequency modulation cycle. Secondary frequency modulation is also called automatic power generation control. It maintains the frequency of the power grid within a stable range (50±0.2Hz in China) by adjusting the output of the generator set in real time, and evaluates the main indicators of control performance with frequency deviation and regional control error. . Proportional-integral-derivative control method is the main traditional con...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H02J3/24H02J3/46H02J3/28G06N3/04G06N3/08
CPCH02J3/241H02J3/466H02J3/28G06N3/049G06N3/08H02J2203/20H02J2203/10G06N3/044G06N3/045Y04S10/50
Inventor 殷林飞吴云智孙志响高放
Owner GUANGXI UNIV
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