A new approach to real-time reliability analysis of transmission system using fuzzy Markov model
To date the studies of power system reliability over a specified time period have used average values of the system transition rates in Markov techniques [Singh C, Billinton R. System reliability modeling and evaluation. London: Hutchison Educational; 1977]. However, the level of power systems reliability varies from time to time due to weather conditions, power demand and random faults [Billinton R, Wojczynski E. Distributional variation of distribution system reliability indices. IEEE Trans Power Apparatus Systems 1985; PAS-104(11):315260]. It is essential to obtain an estimate of system reliability under all environmental and operating conditions. In this paper, fuzzy logic is used in the Markov model to describe both transition rates and temperature-based seasonal variations, which identifies multiple weather conditions such as normal, less stormy, very stormy, etc. A three-bus power system model is considered to determine the variation of system reliability in real-time, using this newly developed fuzzy Markov model (FMM). The results cover different aspects such as daily and monthly reliability changes during January and August. The reliability of the power transmission system is derived as a function of augmentation in peak load level. Finally the variation of the system reliability with weather conditions is determined.
real-time reliability fuzzy markov model power system reliability