Simulating swing dynamics of a power system model using nonlinear model order reduction

Abstract

Purpose

The purpose of this paper is to demonstrate the applicability of the Discrete Empirical Interpolation method (DEIM) for simulating the swing dynamics of benchmark power system problems. The authors demonstrate that considerable savings in computational time and resources are obtained using this methodology. Another purpose is to apply a recently developed modified DEIM strategy with a reduced on-line computational burden on this problem.

Design/methodology/approach

On-line computational cost of the power system dynamics problem is reduced by using DEIM, which reduces the complexity of the evaluation of the nonlinear function in the reduced model to a cost proportional to the number of reduced modes. The on-line computational cost is reduced by using an approximate snap-shot ensemble to construct the reduced basis.

Findings

Considerable savings in computational resources and time are obtained when DEIM is used for simulating swing dynamics. The on-line cost implications of DEIM are also reduced considerably by using approximate snapshots to construct the reduced basis.

Originality/value

Applicability of DEIM (with and without approximate ensemble) to a large-scale power system dynamics problem is demonstrated for the first time.

Citation

Singh, S., Bazaz, M.A. and Nahvi, S.A. (2019), "Simulating swing dynamics of a power system model using nonlinear model order reduction", COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, Vol. 38 No. 6, pp. 1918-1930. https://doi.org/10.1108/COMPEL-08-2018-0331