Study Of Reliability Evaluation For Bus Configurations Of Power Station And Substation

This paper presents a hybrid method which integrates analytical and sequential Monte-Carlo simulation method to evaluate the reliability of bus configurations.Firstly, this paper analysis operation of elements in power system, according to the logistic relations of series and parallel elements and the principle of minimal cut sets method, the mathematical reliability model of different elements are presented in this paper. It is to search minimal cut sets using breadth-first search method and treat with minimal cut sets equivalent to an element.Secondly, sampling is adopted according to the time sequential of system operation and the variety in system states is found. The system state relating to time is simulated by discrete time pace. It not only simulates actual system operation, but deals with the question relating to time rationally. The conventional approach to substation reliability evaluation is to assume that each component can be represented as a Markov model. The probability density functions of time to failure and time to repair are assumed to be exponential in a Markov system. Transition rates are constant, which implies that the time duration spent in the state is exponentially distributed. In real life situations, the assumption of exponential state residence times may be invalid for many repairable components. The time to failure can in many cases be considered exponentially distributed but the time to repair may beconsiderably different. The model in this paper is nonMarkovian model, The time to failure are assumed to be exponential, and the time to repair assumed to be weibull distribution respectively, it is to develop Monte-Carlo method in evaluation of power system reliability. For example, bus configurations of The IEEE RTS-96 are evaluated and compared. The study results show that the hybrid method gives acceptable reliability indices and permits the assumption of Markov models to be relaxed when substation data are available. And, the approach is searched to improve the reliability of power system by component sensitivity analysis. The computed result shows that the method is valid and efficient.