Simultaneous Network Reconfiguration and Capacitor Placement in Distribution Systems Using the Proposed Discrete PSO Algorithm with Chaos Module
Subject Areas : Optimizing Educational Outcome via Technology
1 - Department of Electrical Engineering, ShQ.C.,Islamic Azad University, Shahre-e- Qods, Iran
Keywords: distribution system reconfiguration, sensitivity analysis, capacitor placement, two-layer discrete PSO.,
Abstract :
In this study, a simultaneous optimization method is proposed for distribution network reconfiguration in the presence of harmonic disturbances, along with determining the optimal size and location of switchable capacitors. The main objectives are to reduce active power losses and improve voltage profiles while considering operational constraints and power quality. The optimization objective function includes active power loss costs, capacitor installation costs, and penalty terms for constraint violations. To enhance convergence speed and optimization accuracy, candidate buses for capacitor placement are selected using sensitivity analysis, and the search space is efficiently reduced. The proposed algorithm is a novel Discrete Particle Swarm Optimization (PSO) with chaos module (PSOCM), which delivers fast and superior results compared to conventional methods. The applied constraints include the maximum allowable reactive power of installed capacitors and bus voltage limits according to the IEEE-519 standard. The algorithm is implemented on the Sirjan distribution network, and the results demonstrate significant performance improvements.
[1] Al-ammar, E. A. et al., “Comprehensive impact analysis of ambient temperature on multi-objective capacitor placements in a radial distribution system”, Ain Shams Eng. J. 12(1), 717–727 (2021).
[2] Asabere, P., Sekyere, F., Ayambire, P. & Ofosu, W. K., “Optimal capacitor bank placement and sizing using particle swarm optimization for power loss minimization in distribution network”, J. Eng. Res. https://doi.org/10.1016/j.jer.2024.03.007 (2024).
[3] Mouwafi, M. T., El-Sehiemy, R. A. & El-Ela, A. A. A., “A two-stage method for optimal placement of distributed generation units and capacitors in distribution systems”, Appl. Energy 307, 118188 (2022).
[4] Elseify, M. A., Hashim, F. A., Hussien, A. G. & Kamel, “S. Single and multi-objectives based on an improved golden jackal optimization algorithm for simultaneous integration of multiple capacitors and multi-type DGs in distribution systems”, Appl. Energy 353, 122054 (2024).
[5] Hoseini, S. E., Simab, M., & Bahmani-Firouzi, B.,“AI-Based Multi-Objective Distribution Network Reconfiguration Considering Optimal Allocation of Distributed Energy Storages and Renewable Resources”, International Journal of Smart Electrical Engineering, 14(2), 67-82, 2025.
[6] G. Vulasala, S. Sirirgiri, and S. Thiruveedula, “Feeder reconfiguration for loss reduction in unbalanced distribution system using genetic algorithm,” Int. J. Elect. Power Energy Syst. Eng., vol. 2, no. 4, pp. 240–248, Feb. 2009.
[7] E. López, H. Opazo, L. García, and P. Bastard, “Online reconfiguration considering variability demand: Applications to real networks,” IEEE Trans. Power Syst., vol. 19, no. 1, pp. 549–553, Feb. 2004.
[8] J. Z. Zhu, “Optimal reconfiguration of electrical distribution network using the refined genetic algorithm”, Electric Power Systems Research, vol. 62, no. 1, pp. 37-42, 2002.
[9] A.Y. Abdelaziz, F.M. Mohammed, S.F. Mekhamer and M.A.L. Badr, “Distribution Systems Reconfiguration using a modified particle swarm optimization algorithm”, Electric Power Systems Research, vol. 79, no. 11, pp. 1521-1530, 2009.
[10] C. F. Chang, “Reconfiguration and capacitor placement for loss reduction of distribution systems by ant colony search algorithm,” IEEE Trans. Power Syst., vol. 23, no. 4, pp. 1747–1755, Nov. 2008.
[11] Z. Rong, P. Xiyuan, H. Jinliang, and S. Xinfu, “Reconfiguration and capacitor placement for loss reduction of distribution systems,” in Proc. IEEE TENCON’02, 2002, pp. 1945–1949.
[12] Sayadi F., Esmaeili S., and Keynia F., “Feeder reconfiguration and capacitor allocation in the presence of non-linear loads using new PPSO algorithm”, IET. Gener. Transm. Distrib., 2016, 10, (10), pp. 2316–2326
[13] D.Zhang, Z. Fu, and L. Zhang, “Joint optimization for power loss reduction in distribution systems,” IEEE Trans. Power Syst., vol. 23, no. 1, pp. 161–169, Feb. 2008.
[14] V. Farahani, B. Vahidi, “Reconfiguration and Capacitor Placement Simultaneously for Energy Loss Reduction Based on an Improved Reconfiguration Method”, IEEE Trans. Power Syst., vol. 27, no. 2, pp. 587-595, 2012.
[15] Sayadi Shahraki. F, Bakhtiari. Sh, Zamani Nouri, “A, Optimal use of photovoltaic systems in the distribution network considering the variable load and production profile of Kerman city”, Optimization in Soft Computing, pp. 56-65, 2025.
[16] Sayadi, F., Esmaeili S., Keynia F., “Two-layer volt/var/total harmonic distortion control in distribution network based on PVs output and load forecast errors”, IET Gener. Transm. Distrib. 11(8), 2130–2137 (2017).
[17] Jen-HaoTeng, Chuo-Yean Chan “Backward/ ForwardSweep- Based Harmonic Analysis Method for Distribution Systems”, IEEE Transactions on Power Delivery, VOL. 22, NO. 3, JULY 2007.
[18] R. Eberhart, Y. Shi, “Comparing inertia weights and constriction factors in particle swarm”, Proceedings of the Congress on Evolutionary Computation, pp. 84–88, 2000.
[19] Yu J, Zhang F, Ni F, Ma Y., “Improved genetic algorithm with infeasible solution disposing of distribution network reconfiguration”, IEEE Proc 2009 WRI Global Congr Intell Syst 2009;2:48–52.