Proceedings of the 2019 International Conference on Precision Machining, Non-Traditional Machining and Intelligent Manufacturing (PNTIM 2019)

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Research on Electric Power Emergency Warning Mechanism Based on Meteorological Big Data

Authors
Wang Bo, Guo Fei, Li Mei, Qin Faxian
Corresponding Author
Wang Bo
Available Online November 2019.
DOI
10.2991/pntim-19.2019.93How to use a DOI?
Keywords
Meteorological Big Data; Electric Power Emergency Warning Mechanism; Network Failure Probability Model
Abstract

In the context of climate change, power transmission and transformation equipment are experiencing increasingly severe weather disasters. Therefore, the theory and technology related to meteorological disaster warning and risk prevention have become important technologies for power system transmission equipment inspection operations. A regional grid security early warning mechanism affected by extreme meteorological conditions in the paper is established. Considering the meteorological elements that have an impact on grid security, a big data network failure probability model of meteorological elements is build. Taking the load reduction rate as the dominant consequence index, and taking the transmission line overload condition and the bus voltage deviation as the hidden consequence indicators, the failure probability and the fault impact are combined to evaluate the risk of failure under a certain meteorological condition. An early warning strategy, which includes the issuance of warning levels, warning time and warning areas, was established based on the degree of risk.

Copyright
© 2019, 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 2019 International Conference on Precision Machining, Non-Traditional Machining and Intelligent Manufacturing (PNTIM 2019)
Series
Atlantis Highlights in Engineering
Publication Date
November 2019
ISBN
10.2991/pntim-19.2019.93
ISSN
2589-4943
DOI
10.2991/pntim-19.2019.93How to use a DOI?
Copyright
© 2019, 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

risenwbib
TY  - CONF
AU  - Wang Bo
AU  - Guo Fei
AU  - Li Mei
AU  - Qin Faxian
PY  - 2019/11
DA  - 2019/11
TI  - Research on Electric Power Emergency Warning Mechanism Based on Meteorological Big Data
BT  - Proceedings of the 2019 International Conference on Precision Machining, Non-Traditional Machining and Intelligent Manufacturing (PNTIM 2019)
PB  - Atlantis Press
SP  - 455
EP  - 459
SN  - 2589-4943
UR  - https://doi.org/10.2991/pntim-19.2019.93
DO  - 10.2991/pntim-19.2019.93
ID  - Bo2019/11
ER  -