Title :
Special Protection System Reliability Assessment
Author :
Hsiao, Tsun-Yu ; Lu, Chan-Nan
Author_Institution :
NSYSU, Kaohsiung
Abstract :
Special protection systems (SPS) are sometimes perceived by the electric power industry as attractive alternatives to constructing new transmission facilities for maintaining system stability and security. One of the main concerns in the design of SPS is to assure whether the system could fit with the reliability requirements specification. Currently, there are only a few literatures that discuss the SPS reliability assessment. In one study conducted by the authors, some reliability evaluation techniques, including, reliability block diagram method, fault tree analysis, Markov modeling and Monte Carlo simulations, are applied to assess the probability that the decision process fails to respond as designed in an actual event-based SPS implemented by Taiwan Power Company (Taipower). Experiences acquired from using these methods for SPS reliability assessment and some recommendations are given in this paper.
Keywords :
Markov processes; Monte Carlo methods; fault trees; power system security; power system stability; power transmission protection; power transmission reliability; Markov modeling; Monte Carlo simulation; fault tree analysis; power system security; power transmission protection; reliability assessment; reliability block diagram; special protection system; Fault trees; Maintenance; Performance analysis; Phase frequency detector; Power system modeling; Power system protection; Power system reliability; Power system stability; Power system transients; System performance; Fault tree analysis; Markov modeling; Monte Carlo simulation; reliability assessment; reliability block diagram method; special protection system; system protection scheme;
Conference_Titel :
Industrial & Commercial Power Systems Technical Conference, 2007. ICPS 2007. IEEE/IAS
Conference_Location :
Edmonton, Alta.
Print_ISBN :
1-4244-1291-9
Electronic_ISBN :
1-4244-1291-9
DOI :
10.1109/ICPS.2007.4292105