The simultaneous application of optimum network reconfiguration and distributed generation sizing using PSO for power loss reduction

Dahalan, W.M. and Mokhlis, Hazlie and Bakar, A.H.A. and Jamian, J.J. (2013) The simultaneous application of optimum network reconfiguration and distributed generation sizing using PSO for power loss reduction. Przegląd Elektrotechniczny, 89 (4). pp. 137-141. ISSN 00332097,

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The utilization of Distributed Generation (DG) sources in Distribution Power system is indeed vital as it is capable of solving problems especially pertaining to power losses due to an increasing demand for electrical energy.The location and optimal size of DG has become a prominent issue for the network to have lower power losses value. In order to reduce unnecessary power losses, the use of a combination reconfiguration method and DG units can assist the system to obtain optimal power loss in the network distribution. The primary idea is to have the reconfiguration process embedded with Distributed Generation (DG) and being operated simultaneously to reduce power losses and determine the optimal size of DG by using Particle Swarm Optimization (PSO). The objective of this paper is to focus on reducing the real power losses in the system as well as improving the voltage profile while fulfilling distribution constraints. The simulation results show that the use of simultaneous approach has resulted the lower power losses and better voltage profile of the system. A detail performance analysis is carried out on IEEE 33-bus systems demonstrate the effectiveness of the proposed methodology.

Item Type: Article
Additional Information: Export Date: 17 April 2013 Source: Scopus Language of Original Document: English; Polish Correspondence Address: Dahalan, W. M.; Department of Electrical Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia; email: References: Mendoza, J., Lopez, R., Morales, D., López, E., Moraga, R., Dessante, P., Minimal Loss Reconfiguration using Genetic Algorithm with Restricted Population and Addressed Operators:Real Application (2006) IEEE Transactions on Power Systems, 21 (2), pp. 948-954. , May; Shirmohammadi, D., Hong, H.W., Reconfiguration of electric distribution networks for resistive line loss reduction (1989) IEEE Trans. Power Syst., 4 (1), pp. 1492-1498; Fang, J.Y., Wang, Z., A Refined Plant Growth Simulation Algorithm for Distribution Network Reconfiguration (2009) IEEE Trans. on Power Systems, pp. 4244-4738; Sathish Kumar, K., Jayabarathi, T., Power system reconfiguration and loss minimization for distribution systems using bacterial foraging optimization algorithm (2011) Electrical Power and Energy Systems, 36, pp. 13-17. , Nov; Zhu, I.Z., Optimal reconfiguration of electrical distribution networks using the refined genetic algorithm (2002) Elect. Power Syst. Res., 62, pp. 37-42; Huang, Y.C., Enhanced genetic algorithm-based fuzzy multi objective approach to distribution network reconfiguration (2002) Proc. Inst. Elect. Eng., 149 (5), pp. 615-620; Kim, H., Ko, Y., Artificial neural network based feeder reconfiguration for loss reduction in distribution systems (1993) IEEE Trans. Power Del., 8 (3), pp. 1356-1367; Padma Lalitha, M., Veera Reddy, V.C., Usha, V., Optimal DG Placement for Maximum Loss Reduction in Radial Distribution System using ABC algorithm Journal of Theoretical and Applied Information Technology, pp. 2005-2010; Padma Lalitha, M., Veera Reddy, V.C., Usha, V., Optimal DG Placement for Minimum Real Power Loss in Radial Distribution Systems Using PSO Journal of Theoretical and Applied Information Technology, pp. 2005-2010; Lopez, E., Opaso, H., Online reconfiguration considering variability deman Applications to real networks, IEEE Trans. Power Syst., 19 (1); Singh, D.S., Verma, K.S., GA based optimal sizing and placement of distributed generation for loss minimization (2007) International Journal of Electrical and Computer Engineering, 2, pp. 556-562. , 8 (ONLINE), ISSN: 1307-5179; Moradi, M.H., Abedini, M., A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems (2012) International Journal of Electrical Power & Energy Systems, 34 (1), pp. 66-74. , Jan; Nerves, A.C., Roncesvalles, J.C.K., Application of evolutionary programming to optimal siting and sizing and optimal scheduling of distributed generation (2009) TENCON 2009-2009 IEEE Region 10 Conference, pp. 1-6. , 23-26 Jan; Yasin, Z.M., Rahman, T.K.A., Musirin, I., Rahim, S.R.A., Optimal sizing of distributed generation by using quantuminspired evolutionary programming (2010) Power Engineering and Optimization Conference (PEOCO), (23-24), pp. 468-473. , 4th International, June 2010; Su, C.-T., Chang, C.-F., Chiou, J.-P., Distribution Network Reconfiguration for Loss Reduction by Ant Colony Search Algorithm (2005) Electric Power Systems Research, 75 (2-3), pp. 190-199. , August; Yasin, Z.M., Rahman, T.K.A., Network Reconfiguration in a Power Distribution System under Fault Condition with the Presence of Distributed Generation (2006) International Conference on Energy and Environment (ICEE), , 28-30 Aug; Zhu, Z., Optimal reconfiguration of electrical distribution networks using the refined GA (2002) Electric Power System Research, 62, pp. 37-84; Olamie, J., Niknam, T., Gharehpetian, G., Application of Particle Swarm Optimization for Distribution feeder Reconfiguration Considering Distributed Generators (2008) Applied Mathematics and Computation, pp. 575-586; Wu, Y.K., Lee, C.Y., Liu, L.C., Tsai, S.H., Study of Reconfiguration for the Distribution System With Distributed Generators IEEE Trans. on Power Del., 25 (3), pp. 1678-1685; Rugithaicharoencheep, N., Sirisumarannukul, S., (2009) Feeder reconfiguration for loss reduction in distribution system with Journal, 3, pp. 47-54; Prasad, K., Ranjan, R., Optimal reconfiguration of radial distribution system using a fuzzy mutated genetic algorithm (2005) IEEE Trans. Power Del., 20 (2), pp. 1211-1213; Jamian, J.J., Mustafa, M.W., Mokhlis, H., Abdullah, M.N., Comparative Study on Distributed Generator Sizing Using Three Types of Particle Swarm Optimization (2012) Intelligent Systems, Modelling and Simulation (ISMS), pp. 131-136. , Third International Conference no., 8-10 Feb. 2012
Uncontrolled Keywords: Distributed generation, Particle Swarm Optimization, Power loss and radial distribution systems, Reconfiguration.
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Engineering
Depositing User: Mr Jenal S
Date Deposited: 15 Jul 2013 00:51
Last Modified: 09 Oct 2019 09:28

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