INFORMATION CHANGE THE WORLD

International Journal of Intelligent Systems and Applications(IJISA)

ISSN: 2074-904X (Print), ISSN: 2074-9058 (Online)

Published By: MECS Press

IJISA Vol.4, No.10, Aug. 2017

Placement and Sizing of DG Using PSO&HBMO Algorithms in Radial Distribution Networks

Full Text (PDF, 408KB), PP.43-49


Views:181   Downloads:3

Author(s)

M.Afzalan, M. A.Taghikhani

Index Terms

Distributed Generation;Distribution Networks;Particle Swarm Optimization (PSO);Sensi-tivity Analysis;Honey Bee Mating Optimization (HBMO);Voltage Profile

Abstract

Optimal placement and sizing of DG in distribution network is an optimization problem with continuous and discrete variables. Many researchers have used evolutionary methods for finding the opti-mal DG placement and sizing. This paper proposes a hybrid algorithm PSO&HBMO for optimal placement and sizing of distributed generation (DG) in radial distribution system to minimize the total power loss and improve the voltage profile. The proposed method is tested on a standard 13 bus radial distribution system and simulation results carried out using MATLAB software. The simulation results indicate that PSO&HBMO method can obtain better results than the simple heuristic search method and PSO algorithm. The method has a potential to be a tool for identifying the best location and rating of a DG to be installed for improving voltage profile and line losses reduction in an electrical power system. Moreover, current reduction is obtained in distribution system.

Cite This Paper

M.Afzalan, M. A.Taghikhani,"Placement and Sizing of DG Using PSO&HBMO Algorithms in Radial Distribution Networks", International Journal of Intelligent Systems and Applications(IJISA), vol.4, no.10, pp.43-49, 2012. DOI: 10.5815/ijisa.2012.10.05

Reference

[1]T. Ackermann, G. Anderson, L. Söder; “Distributed Generation: a Definition”, Electric Power System Research, 2001, Vol. 57, pp.195-204.

[2]P. P. Barker, R. W. de Mello; “Determining the Impact of Distributed Generation on Power Sys-tems: Part 1–Radial Distribution Systems”, IEEE PES Summer Meeting, 2000, Vol.3, pp.1645-1656.

[3]N. Hadjsaid, J. F. Canard, F. Dumas; “Dispersed Generation Impact on Distribution Networks”, IEEE Compt. Appl. Power, 1999, Vol. 12, pp.22–28.

[4]W.El-Khattam, M.M.A.Salama; “Distributed Generation Technologies, Definitions and Bene-fits”, Electric Power Systems Research, 2004, Vol. 71, pp.119-128.

[5]G.Pepermans, J.Driesen, D.Haeseldonckx, R.Belmans, W.D.haeseleer; “Distributed Genera-tion: Definitions, Benefits and Issues”, Energy Policy, 2005, Vol. 33, pp.787-798.

[6]A.Soroudi, M.Afrasiab; "Binary PSO-Based Dy-namic Multi-Objective Model for Distributed Generation Planning under Uncertainty", IET Re-newable Power Generation, 2012, Vol.6, No. 2, pp. 67 - 78. 

[7]Kai Zou, A.P.Agalgaonkar, K.M.Muttaqi, S.Perera; "Distribution System Planning with Incorporating DG Reactive Capability and System Uncertain-ties" ,IEEE Transactions on Sustainable Energy, 2012, Vol.3 , No.1, pp. 112 – 123.

[8]Sheng-Yi Su, Chan-Nan Lu, Rung-Fang Chang, G. Gutiérrez-Alcaraz; "Distributed Generation Inter-connection Planning: A Wind Power Case Study ", IEEE Transactions on Smart Grid, 2011, Vol.2 , No.1, pp. 181 – 189.

[9]Ruifeng Shi, Can Cui, Kai Su, Zaharn Zain; "Comparison Study of Two Meta-heuristic Algo-rithms with their Applications to Distributed Gen-eration Planning", Energy Procedia, 2011, Vol. 12, pp. 245-252.

[10]A.M. El-Zonkoly; "Optimal Placement of Mul-ti-Distributed Generation Units Including Different Load Models using Particle Swarm Optimization", Swarm and Evolutionary Computation, 2011, Vol.1, No.1, pp. 50-59.

[11]M.R. AlRashidi, M.F. AlHajri; "Optimal Planning of Multiple Distributed Generation Sources in Distribution Networks: A New Approach", Energy Conversion and Management, 2011, Vol. 52, No. 11, pp. 3301-3308.

[12]M.H. Moradi, M. Abedini; "A Combination of Genetic Algorithm and Particle Swarm Optimiza-tion for Optimal DG Location and Sizing in Dis-tribution Systems", International Journal of Elec-trical Power & Energy Systems, 2012, Vol.34, No.1, pp. 66-74.

[13]Qi Kang, Tian Lan, Yong Yan, Lei Wang, Qidi Wu; "Group Search Optimizer Based Optimal Location 

and Capacity of Distributed Generations", Neuro-computing, 2012, Vol.78, No.1, pp. 55-63.

[14]M. Gomez-Gonzalez, A. López, F. Jurado; "Optimization of Distributed Generation Systems using a New Discrete PSO and OPF", Electric Power Systems Research, 2012, Vol.84, No.1, pp. 174-180.

[15]R. Srinivasa Rao; "Capacitor Placement in Radial Distribution System for Loss Reduction using Ar-tificial Bee Colony Algorithm", World Academy of Science, Engineering and Technology, 2010, Vol. 68. 

[16]Y. Wang, B. Li, T. Weise, J. Wang , B. Yuan, Q. Tian; “ Self-Adaptive Learning Based Particle Swarm Optimization”, Information Sciences, 2011, Vol.181, No.20, pp. 4515-4538.

[17]Y. Jiang, T. Hu , C. Huang, X. Wu; “An Improved Particle Swarm Optimization Algorithm”, Applied Mathematics and Computation, 2007, Vol. 193, No.1, pp. 231–239.

[18]M. Fathian, B.Amiri, A. Maroosi; "Application of Honey-Bee Mating Optimization Algorithm on Clustering", Appl. Math. Comput., 2007, 190(2), pp.1502–1513.

[19]A. Afshar, O. Bozorg Haddad, M.A. Mariٌo, BJ.Adams; "Honey-Bee Mating Optimization (HBMO) Algorithm for Optimal Reservoir Opera-tion", J. Franklin Inst., 2007, 344(5), pp.452–462.

[20]T. Niknam; "Application of Honey Bee Mating Optimization on Distribution State Estimation In-cluding Distributed Generators", J. Zhejiang Univ. Sci. A, 2008, 9(12), pp.1753–1764.