Abstract

Intentional controlled islanding (ICI) is a final resort for preventing a cascading failure and catastrophic power system blackouts. This paper proposes a controlled islanding algorithm that uses spectral clustering over multi-layer graphs to find a suitable islanding solution. The multi-criteria objective function used in this controlled islanding algorithm involves the correlation coefficients between bus frequency components and minimum active and reactive power flow disruptions. Similar to the previous studies, the algorithm is applied in two stages. In the first stage, groups of coherent buses are identified with the help of modularity clustering using correlation coefficients between bus frequency components. In the second stage, the ICI solution satisfying bus coherency with minimum active and reactive power flow disruptions is determined by grouping all nodes using spectral clustering on the multi-layer graph. Simulation studies on the IEEE 39-bus test system demonstrate the effectiveness of the method in determining an islanding solution in real time while addressing the generator coherency problem.

Highlights

  • Intentional controlled islanding (ICI) has been proposed as a corrective measure of last resort to split the power system into several sustainable islands and prevent cascading outages

  • The inclusion of reactive power or voltage in the constraints leads to a mixed integer nonlinear program (MINLP) problem, which is, in general, more difficult to be solved than nonlinear programming problem (NPP) and mixed integer linear programming (MILP) problem [1, 2]

  • Considering these three sets found in the first stage, the number of outcomes of three clusters serves as the input in the second stage to solve the single-layer constrained spectral clustering based on the minimum reactive power flow disruption

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Summary

Introduction

Intentional controlled islanding (ICI) has been proposed as a corrective measure of last resort to split the power system into several sustainable islands and prevent cascading outages. In [10, 11], the authors present an islanding scheme with minimum active power flow disruption using a constrained spectral embedded clustering technique, while satisfying the generator coherency constraints These techniques disregard the effects of the bus voltage magnitude and reactive power, which have a substantial impact on the dynamic coupling. The number of ‘‘k’’ cluster outcomes of this grouping serves as the input in the second stage of the M-SCCI algorithm that identifies islanding boundaries with minimum active and reactive power flow disruption This technique is based on a multi-layer graph, whose common vertex set represents the buses, and the edges on individual layers represent power system attributes that reflect the similarities among the buses in term of the various modalities. These modalities include: À frequency correlation coefficient between buses; ` real power flow disruption; ́ reactive power flow disruption

Multi-layer graph models of power systems
Dynamic generator coherency
Reactive power similarity matrix
Pij ð9Þ
Stage I: coherency detection based on modularity clustering
Stage II: controlled islanding while preserving coherent bus groups
Simulation studies
Case 1
21 Island 2 19
Case 3
Case 4
Findings
Conclusion
Full Text
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