NDLI: State estimation of 500 kV sulphur hexafluoride high-voltage CBs based on Bayesian probability and neural network

Content Provider	IET Digital Library
Author	Geng, Sujie Wang, Xiuli Sun, Peng
Abstract	Circuit breakers (CBs) are of vital importance for the stability of power systems, and a new two-stage hierarchical state estimation method is proposed for 500 kV sulphur hexafluoride CBs based on Bayesian probability and perceptron neural networks. On the basis of the samples collected from Yunnan Power Grid in China, a new indicator system is constructed by association rules. Bayesian probability is applied to measure the correlation between the individual indicators and comprehensive indicators at the same status level, to weigh the individual indicators. Also, an adaptive perceptron is improved to train the weights of comprehensive indicators in different operational conditions, to eliminate the influence of the imbalance problem of relative deterioration. Then, the operating state of equipment can be inferred according to the calculated comprehensive scores. Finally, taking the actual operating equipment as an example, the effectiveness of this proposed method is proved by sample tests and comparison with other existing linear methods.
Starting Page	4503
Ending Page	4509
Page Count	7
ISSN	17518687
Volume Number	13
e-ISSN	17518695
Issue Number	Issue 19, Oct (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-gtd/13/19
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-gtd.2018.5525
Journal	IET Generation, Transmission & Distribution
Publisher Date	2019-08-13
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	500 KV Sulphur Hexafluoride High-voltage CBs Adaptive Perceptron Bayes Method Bayesian Probability Circuit Breaker Indicator System Multilayer Perceptrons Neural Computing Technique Perceptron Neural Network Power Engineering Computing Power Grid Power System Control Power System Stability Power System State Estimation Statistics Switch Two-stage Hierarchical State Estimation Method Yunnan Power Grid
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Energy Engineering and Power Technology Electrical and Electronic Engineering

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