Evaluation of Linear Implicit Quantized State System method for analyzing mission performance of power systems

TL;DR

This paper evaluates the Linear Implicit Quantized State System (LIQSS) method for simulating complex, nonlinear power systems with stiff equations, demonstrating its accuracy and efficiency at optimal quantization sizes.

Contribution

The study assesses LIQSS's suitability for long-duration power system simulations, identifying optimal quantization parameters for accuracy and computational efficiency.

Findings

LIQSS1 results differ less than 1% from continuous methods at 1% quantization size

Computational efficiency increases logarithmically with quantization size

An optimal quantization size balances accuracy and efficiency

Abstract

The Linear Implicit Quantized State System (LIQSS) method has been evaluated for suitability in modeling and simulation of long-duration mission profiles of Naval power systems which are typically characterized by stiff, nonlinear, differential algebraic equations. A reference electromechanical system consists of an electric machine connected to a torque source on the shaft end and to an electric grid at its electrical terminals. The system is highly non-linear and has widely varying rate constants; at a typical steady state operating point, the electrical and electromechanical time constants differ by three orders of magnitude being 3.2 ms and 2.7 s respectively. Two important characteristics of the simulation, accuracy, and computational intensity both depend on the quantization size of the system state variables. At a quantization size of about 1 percent of a maximum value of a variable, results from the LIQSS1 method differed by less than 1 percent from results computed by well-known continuous system state space methods. The computational efficiency of the LIQSS1 method increased logarithmically with increasing quantization size, without significant loss of accuracy, up to some particular quantization size, beyond which the error increased rapidly. For the particular system under study, a sweet spot was found at a particular quantum size that yielded both high computational efficiency and good accuracy.