| The reliability evaluation of a power system, considering both generation and transmission facilities, has become a very important issue since power systems have been growing in size and complexity; thus, making it necessary to model the complete system. This problem will become even more important because of current and future developments like non-utility generation and open transmission access.; This dissertation presents the development of a simulation model to evaluate the reliability of a composite power system by using the Monte Carlo method. The managing of the time, in the simulation process, is based on the next event approach.; Two probability density functions have been implemented in the simulation model to represent the randomness of the transition times for each component, the exponential distribution and the gamma distribution. Other distributions can be implemented if required. Transition times for each component can be modeled by either distribution or both.; Loads are modeled by defining groups of buses with similar load shape, for each group the load is modeled on an hourly basis. This reduces the storage space for load data and results in efficient calculations.; A novel procedure to incorporate bus configuration is introduced in the paper. This procedure to model the buses simplifies the computations significantly. Two bus schemes are considered in this dissertation, the ring bus and the breaker-and-a-half bus.; An important contribution of this research is the development of a heuristic evaluation algorithm. This heuristic procedure simplifies the adequacy evaluation process reducing the number of calculations considerably. Therefore the computation time is significantly reduced.; Special effort has been made to consider the problems of steady state, transient behavior, and correlation of the data obtained from the simulation model. These problems are generally overlooked in the available literature on the Monte Carlo method for power system reliability analysis.; The reliability indices calculated are: the loss of load probability, the average duration of load curtailment, the loss of load frequency, and the average demand of load curtailment. |
