Document Type : Research paper


1 Assistant Professor, Electrical Engineering Department, University of Zanjan, Zanjan, Iran.

2 Department of Electrical Engineering, University of Zanjan, Zanjan, Iran

3 West Mazandaran electrical power distribution company, Noshahr, Iran


In the most recent heuristic methods, the high potential buses for capacitor placement are initially identified and ranked using loss sensitivity factors (LSFs) or power loss index (PLI). These factors or indices help to reduce the search space of the optimization procedure, but they may not always indicate the appropriate placement of capacitors. This paper proposes an efficient approach for the optimal capacitor placement in radial distribution networks with the aim of annual costs minimization based on the sequential placement of capacitors and calculation of power loss index. In the proposed approach, initially, the number of capacitors location is estimated using the total reactive power demand and the average range of capacitors available in the market. Then, the high potential buses can be identified using sequential power loss index-based method. This method leads to achieve the optimal or near optimal locations for the capacitors and decrease the search space of the optimization procedure significantly. The particle Swarm Optimization (PSO) algorithm takes the final decision for the optimum size and location of capacitors. To evaluate the efficiency of the conducted approach, it is tested on several well-known distribution networks, and the results are compared with those of existing methods in the literature. The comparisons verify the effectiveness of the proposed method in producing fast and optimal solutions.


Main Subjects

[1]    A. A. Sallam, O. P. Malik, “Electric distribution systems”, John Wiley and Sons, New Jersey, 2011.
[2]    A. A. El-Fergany, A. Almoataz, Y. Abdelaziz, “Capacitor placement for net saving maximization and system stability enhancement in distribution networks using artificial bee colony-based approach”, Electr. Power Energy Syst., vol. 54, pp. 235-243, 2014.
[3]    R. Sirjani, M. Azah, H. Shareef, “Heuristic optimization techniques to determine optimal capacitor placement and sizing in radial distribution networks: a comprehensive review”, Electr. Rev., vol. 88, no. 7a, pp. 1-7, 2012.
[4]    K. Prakash, M. Sydulu, “Particle swarm optimization based capacitor placement on radial distribution systems”, IEEE Power Eng. Soc. Gen. Meeting, pp. 1-5, 2007.
[5]    RS. Rao, SVL. Narasimham, M. Ramalingaraju, “Optimal capacitor placement in a radial distribution system using plant growth simulation algorithm”, Electr. Power Energy Syst., vol. 33, no. 5,  pp. 1133-1139, 2011.
[6]    A. A. El-Fergany, “Optimal capacitor allocations using evolutionary algorithm”, IET Gener. Transm. Distrib., vol. 7, no. 6, pp. 593-601, 2013.
[7]    Y. Shuiab, M. Kalavathi, C. Rajan, “Optimal capacitor placement in radial distribution system using gravitational search algorithm”, Electr. Power Energy Syst., vol. 64, pp. 384-397, 2015.
[8]    A.Y. Abdelaziz, E.S. Ali, S.M. Abd Elazim, “Flower pollination algorithm and loss sensitivity factors for optimal sizing and placement of capacitors in radial distribution systems”, Electr. Power Energy Syst., vol. 78, pp. 207-214, 2016.
[9]    A. A. El-Fergany, A. Y. Abdelaziz, “Cuckoo search-based algorithm for optimal shunt capacitors allocations in distribution networks”, Electr. Power Compon. Syst., vol. 41, no. 16, pp. 1567-1581, 2013.
[10] A. A. El-Fergany, A.Y. Abdelaziz, “Capacitor allocations in radial distribution networks using cuckoo search algorithm”, IET Gener. Transm. Distrib., vol. 8, no. 2, pp. 223-232, 2014.
[11] M. Sydulu, V. V. K. Reddy, “Index and GA based optimal location and sizing of distribution system capacitors”, IEEE power Eng. Soc. Gen. Meeting, pp. 1-4, 2007.
[12] S. K. Injeti, V. K. Thunuguntla, M. Shareef, “Optimal allocation of capacitor banks in radial distribution systems for minimization of real power loss and maximization of network savings using bio-inspired optimization algorithms”, Electr. Power Energy Syst., vol. 69, pp. 441-455, 2015.
[13] A. Elmaouhab, M. Boudour, R. Gueddouche, “New evolutionary technique for optimization shunt capacitors in distribution networks”, Electr. Eng., vol. 62, no. 3, pp. 163-167, 2011.
[14] S. Sneha, R. Provas Kumar, “Optimal capacitor placement in radial distribution systems using teaching learning based optimization”, Electr. Power Energy Syst., vol. 54, pp. 387-398, 2014.
[15] M. R. Raju, K. V. S. R. Murthy, K. R. Avindra, “Direct search algorithm for capacitive compensation in radial distribution systems”, Electr. Power Energy Syst., vol. 42, no. 1, pp. 24-30, 2012.
[16] J. H. Teng, “A direct approach for distribution system load flow solutions”, IEEE Trans. Power Delivery, vol. 18, no. 3, pp. 882-887, 2003.
[17] J. Kennedy, R. Eberhart, “Particle swarm optimization”, Proc. IEEE Int. Conf. Neural Networks, pp. 1942-1948, 1995.
[18] M. Darabian, A. Jalilvand, R. Noroozian, “Combined use of sensitivity analysis and hybrid Wavelet-PSO-ANFIS to improve dynamic performance of DFIG-based wind generation”, J. Oper. Autom. Power Eng., vol. 2, no. 1, pp. 60-73, 2007.
[19] H. Shayeghi, A. Ghasemi, “FACTS devices allocation using a novel dedicated improved PSO for optimal operation of power system”, J. Oper. Autom. Power Eng., vol. 1, no. 2, pp. 124-135, 2013.
[20] E. Babaei, A. Ghorbani, “Combined economic dispatch and reliability in power system by using PSO-SIF algorithm”, J. Oper. Autom. Power Eng., vol. 3, no. 1, pp. 23-33, 2015.
[21] M. Chis, MMA. Salama, S. Jayaram, “Capacitor placement in distribution systemusing heuristic search strategies”, IET Gener. Transm.  Distrib., vol. 144, no. 3, pp. 225-230, 1997.
[22] D. Das, D. P. Kothari, A. Kalam, “Simple and efficient method for load flow solution of radial distribution network”, Electr. Power Energy Syst., vol. 17, no. 5, pp. 335-346, 1995.
[23] D. F. Pires, CH. Antunes, A.G. Martins, “NSGA-II with local search for a multi-objective reactive power compensation problem”, Electr. Power Energy Syst., vol. 43, no. 1, pp. 313-324, 2012.