Binary Gravitational Search based Algorithm for Optimum Siting and Sizing of DG and Shunt Capacitors in Radial Distribution Systems


This paper presents a binary gravitational search algorithm (BGSA) is applied to solve the problem of optimal allotment of DG sets and Shunt capacitors in radial distribution systems. The problem is formulated as a nonlinear constrained single-objective optimization problem where the total line loss (TLL) and the total voltage deviations (TVD) are to be minimized separately by incorporating optimal placement of DG units and shunt capacitors with constraints which include limits on voltage, sizes of installed capacitors and DG. This BGSA is applied on the balanced IEEE 10 Bus distribution network and the results are compared with conventional binary particle swarm optimization.

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N. A. Khan, S. Ghosh and S. P. Ghoshal, "Binary Gravitational Search based Algorithm for Optimum Siting and Sizing of DG and Shunt Capacitors in Radial Distribution Systems," Energy and Power Engineering, Vol. 5 No. 4B, 2013, pp. 1005-1010. doi: 10.4236/epe.2013.54B192.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] K. Zou, A. P. Agalgaonkar, K. M. Muttaqi, S. Perera. “Optimisation of Distributed Generation Units and Shunt Capacitors for Economic Operation of Distribution Systems,” Power Engineering Conference; Australasian Universities; pp. 1-7, 14-17 Dec. 2008.
[2] K. Zou, A. P Agalgaonkar, K. M. Muttaqi and S. Perera, “Voltage Support by Distributed Generation Units and Shunt Capacitors in Distribution Systems,” Power & Energy Society General Meeting, IEEE, pp.1-8; 26-30 July 2009.
[3] K. Haghdar and H. A. Shayanfar, “Optimal Placement and Sizing of DG and Capacitor for the Loss Reduction via Methods of Generalized Pattern Search and Genetic Algorithm.” Power and Energy Engineering Conference Asia-Pacific, pp. 1-4, 28-31 March 2010.
[4] R. A. Hooshmand and H. Mohkami, “New Optimal Placement of Capacitors and Dispersed Generators Using Bacterial Foraging Oriented by Particle Swarm Optimization Algorithm in Distribution Systems,” Springer Electr Eng 93, pp. 43-53, Jan 2011.
[5] M. Kalantari and A. Kazemi, “Placement of Distributed Generation Unit and Capacitor Allocation in Distribution Systems Using Genetic Algorithm,” pp.1-5, 8-11 May 2011.
[6] E. Rashedi, H. Nezamabadipour and S. Saryazdi, “Gsa: A Gravitational Search Algorithm,” Information Sciences, Vol. 179, No. 13, 2009, pp. 2232-2248. doi:10.1016/j.ins.2009.03.004
[7] P. Avishek and J. Maiti, “Development of a Hybrid Methodology for Dimensionality Reduction in Mahalanobis–Taguchi System Using Mahalanobis Distance and Binary Particle Swarm Optimization,” Expert Syst Appl Vol. 37, No. 2, 2010, pp. 1286-1293. doi:10.1016/j.eswa.2009.06.011
[8] M. Beretaa and T. Burczynski, “Comparing Binary and Real-valued Coding in Hybrid Immune Algorithm for Feature Selection and Classification of ECG Signals.” Eng Appl Artif Intell, Vol. 20, 2007, pp. 571-585.
[9] X. Wang and J. Yang, “Feature Selection Based on Rough Sets and Particle Swarm Optimization,” Pattern Recogn Lett, Vol. 28, 2007, pp. 459-471.
[10] L. H. Chuang and H. W. Chang, “Improved Binary PSO for Feature Selection Using Gene Expression Data,” Comput Biol Chem,Vol. 32, No. 1, 2008, pp.29-38.
[11] X. P. Zeng and Y. M Li, “A Dynamic Chain-like Agent Genetic Algorithm for Global Numerical Optimization and Feature Selection,” Neurocomputing, Vol. 72, 2009, pp. 214-1228. doi:10.1016/j.neucom.2008.02.010
[12] K. G Srinivasa and K. R Venugopal, “A Self-adaptive Migration Model Genetic Algorithm for Data Mining Applications. Inf Sci, Vol. 177, No. 20, 2007, pp. 4295-4313.
[13] X. Yuan and Nie, “An Improved Binary Particle Swarm Optimization for Unit Commitment Problem,” Expert Syst Appl, Vol. 36, No. 4, 2009, pp. 8049-8055. doi:10.1016/j.eswa.2008.10.047
[14] T. H. Wu and C. C. Chang, “A Simulated Annealing Algorithm for Manufacturing Cell Formation Problems,” Expert Syst Appl , Vol. 34, No. 3, 2008, pp. 1609-1617.
[15] E. Rashedi, H. Nezamabadipour and S. Saryazdi, “Bgsa: Binary Gravitational Search Algorithm,” Natural Computing, Vol. 9, 2010, pp. 727-745. doi:10.1007/s11047-009-9175-3
[16] R. Annaluru, S. Das and A. Pahwa, “Multi-level Ant Colony Algorithm for Oplacement of Capacitors in Distribution Systems,” Congress on Evolutionary Computation, Vol. 2, 2004, pp. 1932-1937.
[17] J. J Grainger and S. H Lee, “Capacity Release by Shunt Capacitor Placement on Distribution Feeders, A New Voltage-Dependent Model,” Power Engineering Review, IEEE, Vol. 2, No. 5, 1982, pp. 42-43.

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