A power system network splitting strategy based on contingency analysis

Nur Zawani Saharuddin, Izham Zainal Abidin, Hazlie Mokhlis, Abdul Rahim Abdullah, Kanendra Naidu

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2 Citations (Scopus)

Abstract

This paper proposes a network splitting strategy following critical line outages based on N-1 contingency analysis. Network splitting is the best option for certain critical outages when the tendency of severe cascading failures is very high. Network splitting is executed by splitting the power system network into feasible set of islands. Thus, it is essential to identify the optimal splitting solution (in terms of minimal power flow disruption) that satisfies certain constraints. This paper determines the optimal splitting solution for each of the critical line outage using discrete evolutionary programming (DEP) optimization technique assisted by heuristic initialization approach. Heuristic initialization provides the best initial cutsets which will guide the optimization technique to find the optimal splitting solution. Generation-load balance and transmission line overloading analysis are carried out in each island to ensure the steady state stability is achieved. Load shedding scheme is initiated if the power balance criterion is violated in any island to sustain the generation-load balance. The proposed technique is validated on the IEEE 118 bus system. Results show that the proposed approach produces an optimal splitting solution with lower power flow disruption during network splitting execution.

Original languageEnglish
Article numberen11020434
JournalEnergies
Volume11
Issue number2
DOIs
Publication statusPublished - Feb 2018

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All Science Journal Classification (ASJC) codes

  • Renewable Energy, Sustainability and the Environment
  • Energy Engineering and Power Technology
  • Energy (miscellaneous)
  • Control and Optimization
  • Electrical and Electronic Engineering

Cite this

Saharuddin, N. Z., Abidin, I. Z., Mokhlis, H., Abdullah, A. R., & Naidu, K. (2018). A power system network splitting strategy based on contingency analysis. Energies, 11(2), [en11020434]. https://doi.org/10.3390/en11020434