Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology

Research on Harmonic Analysis in Power Systems Based on Neural Network

Authors
Rui-peng Yang
Corresponding Author
Rui-peng Yang
Available Online March 2016.
DOI
10.2991/icmmct-16.2016.17How to use a DOI?
Keywords
Harmonic analysis; Electric power system; Neural network; Algorithm; Computer simulation
Abstract

A new harmonic analysis method for electric power systems based on triangle basis functions neural network was presented, the convergence theorem of the algorithm was proposed, and a window function and interpolation algorithm were employed to correct the frequency of fundamental waves. This approach does not require synchronized sampling and integer period truncation, and can obtain directly the frequencies, amplitudes and phases of fundamental waves and harmonics. The result of computer simulations has shown that the algorithm is an ideal analysis method with high precision, small amount of calculation and speedy convergence.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology
Series
Advances in Engineering Research
Publication Date
March 2016
ISBN
10.2991/icmmct-16.2016.17
ISSN
2352-5401
DOI
10.2991/icmmct-16.2016.17How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Rui-peng Yang
PY  - 2016/03
DA  - 2016/03
TI  - Research on Harmonic Analysis in Power Systems Based on Neural Network
BT  - Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology
PB  - Atlantis Press
SP  - 85
EP  - 90
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmmct-16.2016.17
DO  - 10.2991/icmmct-16.2016.17
ID  - Yang2016/03
ER  -