A novel tool for transient stability analysis of large-scale power systems: Its application to the KEPCO system

Yoon Sung Cho, Jungsoo Park, Gilsoo Jang

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Time-domain simulation is an important tool for power system dynamic analysis. We solve a set of differential and algebraic equations (DAE) in order to study the dynamic behavior of power systems. These power systems include thousands of generators, exciters, turbine-governors, loads, and other devices. The resultant large-scale DAEs are very difficult to handle and solve. Nevertheless, solution techniques are needed to not just guarantee accuracy but have computational efficiency. In this paper, we report on a novel tool that we developed to deal with time-domain simulation for dynamic analysis and operation of large-scale power systems. The tool has several major features related to transient stability analysis, contingency screening, and ranking. We mainly discuss the structure of this tool and the accuracy of the included dynamic models. Also, the paper proposes a new load model to overcome the low-voltage problem. The proposed technique provides a good performance and convergence when the terminal voltage is below some predefined value. Compared to the commercial tools, the developed tool is numerically well conditioned by introducing the ZIP model algorithm. This tool has been used to support and enhance power engineering education at both the undergraduate and graduate levels. In the case study, simulation results were validated through comparative simulations with the Power System Simulator for Engineering (PSS/E) and Transient Security Assessment Tool (TSAT).

Original languageEnglish
Pages (from-to)786-800
Number of pages15
JournalSimulation Modelling Practice and Theory
Volume15
Issue number7
DOIs
Publication statusPublished - 2007 Aug 1

Keywords

  • Large-scale power systems
  • Power system modeling
  • PSS/E
  • Transient stability analysis
  • TSAT

ASJC Scopus subject areas

  • Information Systems and Management
  • Applied Mathematics
  • Control and Optimization
  • Modelling and Simulation

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