Power Harmonic Analysis via Neural Network and Quasi-synchronous Sampling Method
Aiming at the accuracy of power system harmonic analysis with asynchronous sampling, a harmonic analysis algorithm based on quasi synchronous sampling algorithm and neural network is proposed in this paper. Based on the quasi synchronous sampling algorithm, a functional expression of quasi synchrono...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Control and Information Technology
2021-01-01
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| Series: | Kongzhi Yu Xinxi Jishu |
| Subjects: | |
| Online Access: | http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2021.06.008 |
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| Summary: | Aiming at the accuracy of power system harmonic analysis with asynchronous sampling, a harmonic analysis algorithm based on quasi synchronous sampling algorithm and neural network is proposed in this paper. Based on the quasi synchronous sampling algorithm, a functional expression of quasi synchronous window coefficient in common cases is given, which provides a fundamental frequency estimation for neural network harmonic analysis algorithm. Then, based on the steepest descent method, the adaptive optimal step size in the iterative direction is determined, which makes the neural network algorithm converge to the global minimum value. In the case of asynchronous sampling, the iteration number of the algorithm is more than 10 times, the relative error accuracy of amplitude detection can reach 1×10-10%, and the relative error accuracy of phasor detection can reach 1×10-8%. When the signal-to-noise ratio is 30 dB, the relative error of amplitude detection is basically less than 1×10-2%. Simulation results show that the algorithm has fast detection speed and high precision, and has good application value. |
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| ISSN: | 2096-5427 |