DocumentCode
586776
Title
Power system operational reliability equivalent modeling and analysis based on the Markov chain
Author
Yong Wang ; Xueshan Han ; Ying Ding
Author_Institution
Key Lab. of Power Syst. Intell. Dispatch & Control of Minist. of Educ., Shandong Univ., Jinan, China
fYear
2012
fDate
Oct. 30 2012-Nov. 2 2012
Firstpage
1
Lastpage
5
Abstract
Aiming at the disadvantage of Monte Carlo simulation method in slow convergence and using a great number of computation resources, this paper, based on analytical approach, builds a quick power system operational reliability analyzing model. From the viewpoint of operation, this model which is based on Markov chain, assumes that equipment failure rate follows exponential distribution. Its core content includes three aspects. Firstly, a convenient criterion, used to divide power system operation into three states, and the corresponding statespace transition expression are proposed for engineering application. Secondly, Markov state transition probability matrix is obtained based on power system operation historical data (or simulation data sample). Thirdly, based on state transition probability matrix and current operating state of power system, state transition probability, steady state probability and the mean time to first failure can be acquired very quickly. Example analysis using RBTS-BUS6 system, testified the Markov property of power system state transition and the efficiency of this study.
Keywords
Markov processes; Monte Carlo methods; exponential distribution; failure analysis; matrix algebra; power apparatus; power system reliability; MTTFF; Markov chain; Markov state transition probability matrix; Monte Carlo simulation method; RBTS-BUS6 system; equipment failure rate; equivalent modeling; exponential distribution; mean time to first failure; power system operational reliability; power system state transition; state space transition expression; steady state probability; Chaos; Phase locked loops; Reliability; Markov chain; power system; reliability assessment; reliability prediction;
fLanguage
English
Publisher
ieee
Conference_Titel
Power System Technology (POWERCON), 2012 IEEE International Conference on
Conference_Location
Auckland
Print_ISBN
978-1-4673-2868-5
Type
conf
DOI
10.1109/PowerCon.2012.6401316
Filename
6401316
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