Model order reduction using logarithmic assembly technique and second cauer form for power system models

Abstract

Power system is broad, wide and complex area to do research therefore, for reducing complexity; there is an enormous possibility of simplification of large system in the field of science and technology. Hence, this paper presents a new vital advance methodology a mixed-demand reduction that uses logarithmic assembly technique and the second Cauer form to minimize the order of multivariate feed systems on a large scale power system. Model order reduction technique helps to reduce the large scale power system into an approximate small scale model without changing the inherent property of the actual system. A multi-boundary model of the low-order model is achieved by utilizing new methodology for the aggregation of the pound called the logarithmic mass of the poles, while the numeral coefficients are obtained in the second form of Cauer. The usefulness of the anticipated technique has been tested on two-area power system models.