By Topic

Power System Operation Risk Assessment Based on a Novel Probability Distribution of Component Repair Time and Utility Theory

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Zelei Zhu ; China Electr. Power Res. Inst., Beijing, China ; Jingyang Zhou ; Cuihui Yan ; Lijie Chen

Power system operation risk assessment can comprehensively take into account the occurrence possibility and severity of disturbances, and it is an effective complement to traditional deterministic security analysis. Calculating transient state probability of components in future short time duration is one of the key issues in power system operation risk assessment. In this paper, a novel probability distribution named 'log-normal distribution' was presented for repair time. The shape of probability density of log-normal distribution can describe the distribution characteristics of component repair times well. The numerical test result using real-life data showed that the log-normal distribution matched the real-life data well, and calculation of the transient state probability was very easy. Then, two different time-varying component outage models for overhead transmission line described by Markov model and transformer described by non-Markov mode1 are developed respectively. Subsequently, the utility function is used to measure the degree of dissatisfaction induced by fault and the utility theory based risk indices of overload, low voltage, voltage collapse and angle instability are given. The proposed risk indices can sensitively reflect the trends of risk indices and accord with the actual power system operation. Based on the above research, the practical result shows that this algorithm is easy to be realized and the accuracy and practicality have been are verified.

Published in:

2012 Asia-Pacific Power and Energy Engineering Conference

Date of Conference:

27-29 March 2012