Ingeniería ISSN Impreso: 1409-2441 ISSN electrónico: 2215-2652

Controlled Islanding with Special Consideration of Parallel Power System Restoration Constraints

Jairo Quirós-Tortós, Pablo Fernández-Porras



Intentional Controlled Islanding (ICI) can prevent blackouts by splitting the system into islands following a severe disturbance. Post-islanding events, however, might lead to instabilities that can result into blackouts within one or more islands. Although it is critical to ensure that the islands can be restored in the case of local blackouts, this has not been addressed in the literature. To fill this gap, this paper proposes an ICI method that considers not only the typical ICI constraints, but also Parallel Power System Restoration (PPSR) constraints. The traditional islanding problem for minimal power-flow disruption ensuring the typical generator coherency constraint is extended to include at least one blackstart unit within each island and to exclude various branches from possible solutions. To understand the extent to which each island can be restored, the method quantifies the active and reactive power generation available within each island to determine the maximum load that can be picked up. By applying the proposed ICI method, the restoration process can be facilitated and speeded up. Simulation studies on two IEEE test systems are used to demonstrate the effectiveness of the method in determining an islanding solution that considers PPSR constraints with different network topologies and sizes.


Graph theory; intentional controlled islanding; parallel power system restoration; spectral clustering

Full Text:



Henner VE. A network separation scheme for emergency control. Int J Electr Power Energy Syst. 1980 Apr;2(2):109–14.

Sun K, Zheng DZ, Lu Q. Splitting strategies for islanding operation of large-scale power systems using OBDD-based methods. IEEE Trans Power Syst. 2003 May;18(2):912–23.

Sun K, Zheng DZ, Lu Q. A simulation study of OBDD-based proper splitting strategies for power systems under consideration of transient stability. IEEE Trans Power Syst. 2005 Feb;20(1):389–99.

Adibi MM, Kafka RJ, Maram S, Mili LM. On power system controlled separation. IEEE Trans Power Syst. 2006;21(4):1894–902.

Peiravi A, Ildarabadi R. Comparison of computational requirements for spectral and kernel k-means bisection of power system. Aust J Basic Appl Sci. 2009;3(3):2366–88.

Ding L, Gonzalez-Longatt FM, Wall P, Terzija V. Two-step spectral clustering controlled islanding algorithm. IEEE Trans Power Syst. 2013;28(1):75–84.

Quiros-Tortos J, Sánchez-García R, Brodzki J, Bialek J, Terzija V. Constrained Spectral Clustering Based Methodology for Intentional Controlled Islanding of Large-Scale Power Systems. IET Gener Transm Distrib. 2014;in press:1–12.

Adibi MM, Kafka RJ. Power System Restoration Issues. IEEE Comput Appl Power. 1991 Apr;4(2):19–24.

Lindenmeyer D, Dommel HW, Adibi MM. Power system restoration - a bibliographical survey. Int J Electr Power Energy Syst. 2001;23(3):219–27.

Liu Y, Fan R, Terzija V. Power system restoration: a literature review from 2006 to 2016. J Mod Power Syst Clean Energy. 2016 Jul;4(3):332–41.

Quirós-Tortós J, Terzija V. Controlled islanding strategy considering power system restoration constraints. In: IEEE PES General Meeting. San Diego; 2012. p. 1–8.

Von Luxburg U. A tutorial on spectral clustering. Stat Comput. 2007;17(4):395–416.

Bie T De, Suykens J, Moor DB. Learning from general label constraints. In: IAPR International Workshop on Statistical Pattern Recognition. Lisbon; 2004.

Zhao Q, Sun K, Zheng DZ, Ma J, Lu Q. A Study of System Splitting Strategies for Island Operation of Power System: A Two-Phase Method Based on OBDDs. IEEE Trans Power Syst. 2003 Nov;18(4):1556–65.

Adibi M, Clelland P, Fink L, Happ H, Kafka R, Raine J. Power System Restoration - A Task Force Report. IEEE Trans Power Syst. 1987 May;2(2):271–7.

Kaufman L, Rousseeuw PJ. Finding groups in data: an introduction to cluster analysis. Vol. 1. New York: Wiley; 1990.

Wang X, Davidson I. Flexible Constrained Spectral Clustering. ACM SIGKDD Int Conf Knowl Disc Data Min. 2010;563–72.

Yusof SB, Alden RTH, Rogers GJ. Slow coherency based network partitioning including load buses. IEEE Trans Power Syst. 1993 Aug;8(3):1375–82.

You H, Vittal V, Wang X. Slow Coherency-Based Islanding. IEEE Trans Power Syst. 2004 Feb;19(1):483–91.

Jonsson M, Begovic M, Daalder J. A new method suitable for real-time generator coherency determination. IEEE Trans Power Syst. 2004 Aug;19(3):1473–82.

Ariff M a. M, Pal BC. Coherency identification in interconnected power system — An independent component analysis approach. IEEE Trans Power Syst. 2013;28(2):1–1.

Zimmerman RD, Murillo-Sanchez CE, Thomas RJ. MATPOWER: Steady-State Operations, Planning, and Analysis Tools for Power Systems Research and Education. IEEE Trans Power Syst. 2011 Feb;26(1):12–9.


  • There are currently no refbacks.

© 2017 Universidad de Costa Rica. Para ver más detalles sobre la distribución de los artículos en este sitio visite el aviso legal. Este sitio es desarrollado por UCRIndex y Open Journal Systems.