The ways of electrical equipment fault probability influenced by typhoons and rainstorms are analyzed in detail. The scope of data acquisition of blackout defense system is expanded to macroscale meteorological forecast information as well as local meteorological data. A spatial-temporal early-warning method against these natural disasters is proposed. Firstly
according to the information of meteorology
environment
topography and geomorphology
the spatial-temporal evolution trends of typhoons and rainstorms can be predicted and modified. Then
the probability of faults such as broken lines
collapsed towers
flashover caused by adverse weather or derivative disasters such as landslide
debris flow and flood is forecasted on line. Through the module interface between natural disaster evaluation and power system stability analysis
the predictive fault set of online security analysis which was fixed can now be dynamically modified. Therefore
the blackout defense system against typhoon and rainstorm has definite ability of early warning and decision support. This work is supported by Special Fund of the National Basic Research Program of China (973 Program) (No. 2013CB228204)
State Key Program of National Natural Science Foundation of China (No. 61533010)
China-Thailand Cooperation Fund Project (No. 5151101161)
and Science and Technology Project of Yunnan Power Grid Company (No. YDTZ-F2014-105).
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Impact of Runoff Generation and Concentration Process in Watershed Reservoirs on Carbon Emissions of Power Generation Under Natural Disasters
Evaluation of Compound-disaster Failure Rate for Transmission Lines from Perspective of Whole Reductionism Thinking —Part Two Algorithm and Application
Online Evaluation Method for Transient Active Power Support Capability of Wind Farm Considering Wind Speed Uncertainty
Related Author
XIE Yunyun
XIE Yingbiao
HOU Hui
TANG Junyi
YAN Yulin
ZHANG Ji
XIE Changjun
ZHANG Jianmin
Related Institution
Department of Automation,Nanjing University of Science and Technology
Economics and Technology Research Institute, State Grid Hubei Electric Power Company
School of Automation, Wuhan University of Technology
State Grid Electric Power Research Institute (NARI Group Corporation)