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Research on Harmonic Current Detection Method Based on Hopfield Neural Network and High Accuracy Algorithm

Author: ZouYu
Tutor: WangPing
School: Tianjin University
Course: Power Electronics and Power Drives
Keywords: Harmonic Detection Hopfield neural network Active Power Filter Windowing function Interpolation algorithm MATLAB
CLC: TM714
Type: Master's thesis
Year: 2007
Downloads: 175
Quote: 2
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Abstract


Harmonic detection is an important branch of the harmonic problems , has an important role to suppress harmonics . Harmonic analysis and measurement is an important task in power system analysis and control , is an important prerequisite of the relay to determine the point of failure , and fault type . Accurate , real-time detection the grid transient changes in distortion of current , voltage , is the goal of many domestic and foreign scholars have been studying . The conventional harmonic measurement methods are mainly : analog band- pass or band- stop filter measurement harmonic ; harmonics measurement based on Fourier transform ; harmonic detection based on wavelet transform or artificial neural network based on instantaneous reactive power harmonic measurement ; methods. However, the basic method in the practical application of both the limitations and shortcomings of different degrees . To solve this problem , expanding and improving methods came into being on the basis of these various methods , in particular, to adapt to the new direction of active power filter and improved methods to receive special attention . This article in the in-depth study on the basis of the predecessors harmonic detection theory and implementation methods , the harmonic detection method along with high accuracy and real-time performance . The method uses the Hopfield neural network energy function and optimization principle with Fourier windowed interpolation algorithm , so neural network and Fourier algorithm effective and complementary combination to achieve the precise purpose of rapid detection of harmonics . Special Hopfield neural networks with different characteristics in both serial and parallel detection structure and the corresponding frequency detection model . This paper argued Hopfield neural network harmonic detection theory is derived , and the performance characteristics of the different detection structure , a more complete set of Hopfield neural network theory and system for the detection of power harmonic structure . The accuracy of the method in the MATLAB / SIMULINK environment , fast and self-adaptive done a lot of simulation. Given its excellent performance , the future can be applied in areas such as active power filter .

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CLC: > Industrial Technology > Electrotechnical > Transmission and distribution engineering, power network and power system > Theory and Analysis > Load analysis
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