Adequacy Evaluation of Bulk Power Systems via Combination of Monte Carlo Simulation and Artificial Immune Recognition System

Monte Carlo simulation (MCS) is very useful in adequacy evaluation of complex power systems. However, it may be time-consuming when power flow analysis is needed to determine the status of each system state. In this study, we combine Monte Carlo simulation and artificial immune recognition system (AIRS), an effective classifier for imbalanced data set, in order to expedite the state evaluation process. An IEEE Reliability Test System is used for the simulation study. Numerical studies are conducted to show the effectiveness of the proposed method in approximating the loss of load probability (LOLP) with and without incorporating transmission line outages.