Anti-Islanding Protection of Distributed Generation Based on Social Spider Optimization Technique
( Vol-4,Issue-6,June 2017 )

Dr.R.Vijay, V.Priya


Anti-islanding Protection, IEEE 34 Bus Distribution System, Distributed Generation, Social Spider Optimization algorithm, Synchronous Generator Oscillations.


Anti-islanding protection is one of the most important requirements for the connection of Distributed Generators in power systems. This paper proposes a Social Spider Optimization (SSO) algorithm to detect unintentional islanding in power systems with distributed generation. The SSO algorithm is employed to differentiate frequency oscillations in synchronous generator those caused by non-islanding events. The SSO algorithm is based on the forging strategy of social spiders, which generated vibrations spread over the spider web to determine the positions of preys or any other disturbances. The vibrations from the spider are used to detect the occurrence of islanding in the synchronous generator. The SSO algorithm has superior performance when tested with IEEE 34 bus distribution system. The taken test system is evaluated for different scenarios and load distribution. The proposed SSO algorithm detects the islanding and prevents the system from undue tripping and outages. Furthermore, this technique may apply to prevent the system from islanding and maintains the future Indian Distributed Generation (DG) system reliability.

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[1] N.Jenkins, R.Allan, P.A.Crossley, D.Kirschen and G.Strbac, “Embedded Generation,” IEEE Power and Energy Series vol. 31, 2000.
[2] N. N. A. Bakar, M. Y. Hassan, M. F. Sulaima, M. Na’im Mohd Nasir, and A. Khamis, “Microgrid and load shedding scheme during islanded mode: A review,” Renewable and Sustainable Energy Reviews vol. 71, pp. 161–169, 2017.
[3] P. Gupta, R.S. Bhatia, and D.K. Jain, “Average absolute frequency deviation value based active islanding detection technique,” IEEE Trans. Smart Grid vol. 6, no. 1, pp. 26–35, 2015.
[4] D. Velasco, C. Trujillo, G. Garcera, and E. Figueres, “An active anti-islanding method based on phase-PLL perturbation,” IEEE Trans. Power Electron. vol. 26, no. 4, pp. 1056–1066, 2011.
[5] N.W.A. Lidula, and A.D. Rajapakse, “A pattern recognition approach for detecting power islands using transient signals – part II: performance evaluation,” IEEE Trans. Power Deliver. vol. 27, no. 3, pp. 1071–1080, 2012.
[6] R. Vijay, and C.S. Ravichandran, “A detailed investigation on conventional and meta-heuristic optimization algorithms for economic power scheduling problems,” International Journal of Engineering Trends and Applications, vol. 3, no. 4, pp. 40-53, 2016.
[7] J. House, K. Landis, and D. Umberson, “Social relationships and health,” Science, vol. 241, no. 4865, pp. 540–545, 1988.
[8] C. W. Clark, and M. Mangel, “Foraging and flocking strategies: Information in an uncertain environment,” The American Naturalist, vol. 123, no. 5, pp. 626–641, 1984.
[9] R. Vijay, and C.S. Ravichandran, “Scheduling practical generating system using an improved bacterial swarm optimization,” Tehnicki vjesnik, vol. 23, no. 5, pp. 1307-1315, 2016.
[10] R. Vijay, and C.S. Ravichandran, “Quorum sensing based bacterial swarm optimization on test benchmark functions,” International Journal of Research and Innovation in Engineering Technology, vol. 2, no. 12, pp. 27-38, 2016.
[11] R. Vijay, and C.S. Ravichandran, “Enriched biogeography-based optimization algorithm to solve economic power dispatch problem,” In Proceedings of fifth international conference on soft computing for problem solving, Springer Singapore, pp. 875-888, 2016.
[12] R. Vijay, “Optimal and reliable operation of micro grid using enriched Biogeography Based Optimization algorithm,” Journal of Electrical Engineering, 2017. (Accepted for Publication)
[13] R. Vijay, and C.S. Ravichandran, “Enhanced ant colony optimization to solve the optimal power flow with ecological emission,” International Journal of System Assurance Engineering and Management, Springer, pp. 1-8, 2016.
[14] R. Vijay, and C.S. Ravichandran, “Optimal placement and sizing of distributed power sources in microgrid for power loss minimization using bat motivated optimization algorithm,” Asian Journal of Research in Social Sciences and Humanities, vol. 6, no. 8, pp. 252-266, 2016.
[15] E. Cuevas, M. Cienfuegos, D. Zaldívar, and M. Pérez-Cisneros, “A swarm optimization algorithm inspired in the behavior of the social-spider”, Expert Systems with Applications, vol. 40, no. 16, pp. 6374-6384, 2013.
[16] R. Vijay, R. Antrut Jaffrin, and C.S. Ravichandran, “Optimal placement and sizing of solar constructed DG using SSO technique,” International Journal of Computer Science Trends and Technology, vol. 4, no. 3, pp. 333-342, 2016.
[17] Online available:
[18] K.E. Yeager, and J.RWillis, “Modeling of emergency diesel generators in an 800 megawatt nuclear power plant,” IEEE Trans. Energy Convers, vol. 8, no. 3, pp. 433, 1993.
[19] L.N. Hannett,, F.P. de Mlello, G.H. Tylinski, W.H. Becker, “Validation of nuclear plant auxiliary power supply by test,” IEEE Trans. Power Appar. Syst. PAS-101 no. 9 pp. 3068, 1982.