Proceedings of the 2016 International Conference on Energy, Power and Electrical Engineering

Research on Poisson Point Process Model of Transmission System and Its Reliability

Authors
Yonghua Zhu, Chenglin Chen, Tian Zhang
Corresponding Author
Yonghua Zhu
Available Online October 2016.
DOI
10.2991/epee-16.2016.8How to use a DOI?
Keywords
poisson marked point process; bayesian estimation; outage time
Abstract

This paper mainly discussed the system reliability with the new isolated circuit breaker and the traditional equipment in operation process. Firstly, we established the Poisson marked point process model of the outage time and derived their mathematical expectations. And we used the expectations as the index to evaluate the reliability of transmission system. Then we used the censored data to get the Bayesian estimation of the parameters. Finally we decomposed the system outage time to calculate the result of the reliability model. By the analysis, we provided a reference for the reliability evaluation of transmission system.

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 International Conference on Energy, Power and Electrical Engineering
Series
Advances in Engineering Research
Publication Date
October 2016
ISBN
978-94-6252-258-9
ISSN
2352-5401
DOI
10.2991/epee-16.2016.8How 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  - Yonghua Zhu
AU  - Chenglin Chen
AU  - Tian Zhang
PY  - 2016/10
DA  - 2016/10
TI  - Research on Poisson Point Process Model of Transmission System and Its Reliability
BT  - Proceedings of the 2016 International Conference on Energy, Power and Electrical Engineering
PB  - Atlantis Press
SP  - 34
EP  - 38
SN  - 2352-5401
UR  - https://doi.org/10.2991/epee-16.2016.8
DO  - 10.2991/epee-16.2016.8
ID  - Zhu2016/10
ER  -