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IEEE Access
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IEEE Access
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Fast Power System Dynamic Simulation Using Continued Fractions

Authors: Chengxi Liu; Bin Wang; Kai Sun;

Fast Power System Dynamic Simulation Using Continued Fractions

Abstract

This paper proposes a novel method for power system dynamic simulation that solves power system differential algebraic equations by a semi-analytical and semi-numerical approach using continued fractions. The method implements a two-stage scheme to enhance online performance of simulation: the offline derivation stage finds approximate analytical solutions, so-called “semi-analytical solutions,”for state variables of dynamic devices, such as generators in the form of power series of time with symbolic coefficients about system conditions; the online evaluation stage substitutes values on actual system conditions for symbolic coefficients, then transforms the solution into a continued fraction to prolong its time interval of accuracy, and finally calculates the system's trajectory over consecutive, adaptive time intervals for expected simulation results. A priori error bound for continued fractions is proposed to enable the simulation on adaptive time intervals. Compared with the conventional numerical simulation methods, the proposed continued fraction-based method has a fast simulation speed and a good suitability for parallel computing. The method is demonstrated and tested on the IEEE 9-bus system, the IEEE 39-bus system, and Polish 327-generator 2383-bus system.

Keywords

Continued fractions, error bound, differential algebraic equations, dynamic simulation, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Top 10%
Average
Average
gold