Distributed PSO Algorithm for Data Model Partitioning in Power Distribution Systems

 

A. Erdeljan, D. Capko*, S. Vukmirovic, D. Bojanic and V. Congradac

 

Faculty of Technical Sciences University of Novi Sad Serbia. *dcapko@uns.ac.rs

 

Abstract

This paper presents a method for data model partitioning of power distribution network. Modern Distribution Management Systems which utilize multiprocessor systems for efficient processing of large data model are considered. The data model partitioning is carried out for parallelization of analytical power calculations. The proposed algorithms (Particle Swarm Optimization (PSO) and distributed PSO algorithms) are applied on data model describing large power distribution network. The experimental results of PSO and distributed PSO algorithms are presented. Distributed PSO algorithm achieves significantly better results than the basic PSO algorithm.

Keywords: Particle swarm optimization, Partitioning algorithms, Power distribution networks, Data models.

 

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References

[1] V. Strezoski et al., "DMS - Basis for Increasing of Green Distributed Generation Penetration in Distribution Networks", Thermal Science, vol.16, Supplement, pp. 189-203, 2012.         [ Links ]

[2] S. Vukmirovic et al., "Optimal Workflow Scheduling in Critical Infrastructure Systems with Neural Networks", Journal of Applied Research and Technology, vol. 10 no.2, pp. 114-121, April 2012.         [ Links ]

[3] F. Jiyuan and S. Borlase, "The Evolution of Distribution", IEEE Power & Energy Magazine, pp. 63-68, march/april 2010.         [ Links ]

[4] G. Heydt, "The next generation of power distribution systems", IEEE Transactions on Smart Grid, vol. 1, no. 3, pp. 225-235, 2010.         [ Links ]

[5] V. Strezoski et al., "Osnovne energetske funkcije za analizu, upravljanje i planiranje pogona srednjenaponskih distributivnih mreza", IV skup Trendovi Razvoja: Nove tehnologije u elektrodistribuciji", Kopaonik, 1998.         [ Links ]

[6] D. Capko et al., "An Optimal Relationship-Based Partitioning of Large Datasets", 14th East-European Conference on Advances in Databases and Information Systems, Novi Sad,         [ Links ] Lecture Notes in Computer Sciences, vol. 6295, pp. 547-550., 2011.         [ Links ]

[7] M.R. Garey and D.S. Johnson, "Computers and Intractability: A Guide to the Theory of NP-Completeness", W.H. Freeman, San Francisco, 1979.         [ Links ]

[8] H.C. Kuo and C. H. Lin, "Cultural evolution algorithm for global optimizations and its applications", Journal of Applied Research and Technology, vol. 11, no. 4, pp. 510-522., 2013.         [ Links ]

[9] T.N. Bui and B.R. Moon, "Genetic Algorithm and Graph Partitioning", IEEE Trans. Computers, vol. 45, no. 7, pp. 841-855., 1996.         [ Links ]

[10] G. Karypis and V. Kumar, "A fast and high quality multilevel scheme for partitioning irregular graphs", SIAM Journal of Scientic Computing, vol.20, no.1, pp. 359-392., 1998.         [ Links ]

[11] IEC 61970 Energy management system application program interface (EMS-API) - Part 301: Common Information Model (CIM) Base, IEC, Edition 2.0, 2007.         [ Links ]

[12] IEC/TR 61968-11 Application integration at electric utilities - System interfaces for distribution management -Part 11: Common information model (CIM) extensions for distribution, IEC, Edition 1.0, 2010.         [ Links ]

[13] IEC 61970 Energy management system application program interface (EMS-API) - Part 403: Generic data access, IEC, 2008.         [ Links ]

[14] OMG Specification: Utility Management Systems (UMS) Data Access Facility DAF, Version 2.0.1, 2005.         [ Links ]

[15] A. Erdeljan and D. Capko, "Analiza primene DAF i GDA specifikacija za pristup objektnom modelu UMS-a", 51. Konferencija ETRAN 2007., Herceg Novi, jun 2007.         [ Links ]

[16] S. Vukmirovic et al., "Extension of the Common Information Model with Virtual Meter", Electronics and Electrical Engineering, Kaunas: Technologija, vol.107, no.1.,pp. 59-64, 2011.         [ Links ]

[17] D. Capko et al., "A Hybrid Genetic Algorithm for Partitioning of Data Model in Distribution Management Systems", Information technology and control, vol. 40, no. 4, pp. 316-322, 2011.         [ Links ]

[18] J. Kennedy and R. Eberhart, "Particle swarm optimization", In: Proceedings of the 1995 IEEE International. Conference on Neural Networks (ICNN), IEEE Service Center, Piscataway, New Jersey, vol.4, pp.1942-1948, 1995.         [ Links ]

[19] E.O. Wilson, Sociobiology: The new synthesis", Belknap Press, Cambridge, 1975.         [ Links ]

[20] J. Kennedy and R. Eberhart, "A discrete binary version of the particle swarm algorithm", In: Proceedings of the 1997 IEEE International Conference on Systems, Man, and Cybernetics, IEEE Service Center, Piscataway, New Jersey, vol. 5, pp. 4104-4108, 1997.         [ Links ]

[21] E. Laskari et al., "Particle swarm optimization for integer programming", In: Proceedings of the IEEE Congress on Evolutionary Computation, Honolulu, Hawaii USA, vol. 2, pp. 1582-1587, 2002.         [ Links ]

[22] D. Capko et al., "PSO algorithm for Graph Partitioning", 17th Telecommunication Forum 2009, Belgrade, 2009.         [ Links ]

[23] H. Rezazadeh et al., "Linear programming embedded particle swarm optimization for solving an extended model of dynamic virtual cellular manufacturing systems", Journal of Applied Research and Technology, vol.7, no. 1, pp. 83-108, April 2009.         [ Links ]

[24] R. Eberhart and Y. Shi, "Particle Swarm Optimization: Developments, Applications and Resources", In: Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2001), Seoul, Korea, 2001.         [ Links ]

[25] G. A. Laguna-Sánchez et al., "Comparative Study of Parallel Variants for a Particle Swarm Optimization Algorithm Implemented on a Multithreading GPU", Journal of Applied Research and Technology, vol.7, no. 3, pp. 292-307., December 2009.         [ Links ]

[26] W. Gropp, "Using MPI, 2nd Edition: Portable Parallel Programming with the Message Passing Interface", Cambridge, MIT Press, 1999.         [ Links ]

[27] MPI Forum: MPI: A Message-Passing Interface Standard, Version 2.2, High Performance Computing Center Stuttgart, 2009.         [ Links ]