Thesis submitted in fulfilment of the requirements for the degree Master of Technology: Electrical Engineering in the Faculty of Engineering at the Cape Peninsula University of Technology 2013 / The demand for electrical energy has kept on increasing, thus causing power systems to be more complex and bringing the challenging problems of electrical energy generation, transmission, stability, as well as storage to be examined more thoroughly. With the advent of high-speed computation and the desire to analyze increasingly complex behaviour in power systems, simulation techniques are gaining importance and prevalence. Nevertheless, while simulations of large, interconnected complex power systems are feasible, they remain time-consuming. Moreover, the models and parameters used in simulations are uncertain, due to measurement uncertainty, the need to represent a complex behaviour with low-order models, and the inherent changing nature of the power system. This research explores the use of a model reduction technique and the applications of a Real-Time Digital Simulator (RTDS) to reduce the uncertainty in large-scale complex power system models. The main goal of the research is to develop a reduced order model and to investigate the applications of the RTDS simulator in reduction of large, interconnected power systems models. The first stage of the study is to build and simulate the full model of the power system using the DigSILENT and RTDS simulators. The second phase is to apply model reduction technique to the full model and to determine the parameters in the reduced-order model as well as how the process of reduction increases this model uncertainty. In the third phase the results of the model reduction technique are compared based on the results of the original model - IEEE standard benchmark models has been used. The RTDS was used for comparative purposes. The thesis investigations use a particular model reduction technique as Coherency based Method. Though the method ideas are applicable more generally, a concrete demonstration of its principles is instructive and necessary. Further, while this particular technique is not relevant to every system, it does apply to a broad class of systems and illustrates the salient features of the proposed methodology. The results of the thesis can be used in the development of reduced models of complex power systems, simulation in real-time during power system operation, education at universities, and research. Keywords: IEEE benchmark models, reduced models, Coherency based Method, DigSILENT, RTDS, model uncertainty, power system stability