Proceedings of the 2017 2nd International Conference on Electrical, Control and Automation Engineering (ECAE 2017)

The Improved PASTd and ESPRIT in Power System Harmonic Estimation Application

Authors
Feng Liu, Ligong Sun, Zhihao Cheng
Corresponding Author
Feng Liu
Available Online December 2017.
DOI
https://doi.org/10.2991/ecae-17.2018.3How to use a DOI?
Keywords
harmonic estimation; PASTd; MDL; ESPRIT
Abstract

The paper analyzes the current power system harmonic estimation algorithms which have a considerable number of shortages. In order to improve detection precision and reduce the computational complexity, we can combine the ESPRIT algorithm with improved PASTd algorithm, consequently, achieve the rapid estimation of harmonic frequency. Both theoretical analysis and simulation results show that the algorithm is characterized by better frequency resolution performance and anti-interference ability.

Copyright
© 2018, 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/).

Download article (PDF)

Volume Title
Proceedings of the 2017 2nd International Conference on Electrical, Control and Automation Engineering (ECAE 2017)
Series
Advances in Engineering Research
Publication Date
December 2017
ISBN
978-94-6252-458-3
ISSN
2352-5401
DOI
https://doi.org/10.2991/ecae-17.2018.3How to use a DOI?
Copyright
© 2018, 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  - Feng Liu
AU  - Ligong Sun
AU  - Zhihao Cheng
PY  - 2017/12
DA  - 2017/12
TI  - The Improved PASTd and ESPRIT in Power System Harmonic Estimation Application
BT  - Proceedings of the 2017 2nd International Conference on Electrical, Control and Automation Engineering (ECAE 2017)
PB  - Atlantis Press
SP  - 13
EP  - 17
SN  - 2352-5401
UR  - https://doi.org/10.2991/ecae-17.2018.3
DO  - https://doi.org/10.2991/ecae-17.2018.3
ID  - Liu2017/12
ER  -