COMPOSITE SYSTEM RELIABILITY EVALUATION AND EFFECTIVE CAPACITY EVALUATION OF TIME LIMITED ENERGY RESOURCES

Abstract

This first part of the thesis presents a study of the composite system reliability evaluation using a cross-entropy based importance sampling method to improve computational efficiency of sequential Monte Carlo simulation (MCS). The sensitivity analysis studies show how the computational performance of the method and reliability indices are affected by varying the system parameters like peak load and forced outage rates of the generators. The relationship between computation time, simulation parameters, coefficient of variance and number of system cores is also explored. The sequential Monte Carlo simulation is implemented using parallel computing techniques which reduces the computation time. A comparison study is carried out using Simple Monte Carlo method. These methods are tested on an IEEE RTS 79 test system. The second part of the thesis presents a study of various techniques to evaluate effective capacity of time limited and energy limited energy resources. The energy limited sources are added to the generation buses in the IEEE RTS 79 test system and the effective load that it can serve to maintain the same reliability benefit is evaluated. All the capacity evaluation of the energy limited resources is studied using a composite power system model. It is observed that the effective capacity increases as the resource duration increases.