## Recent trends of the most used metaheuristic techniques for distribution network reconfiguration

**Date**

2017-11-11

**Author**

Quintero Duran, Michell Josep

Candelo Becerra, John Edwin

Sousa Santos, Vladimir

### Abstract

Distribution network reconfiguration (DNR) continues to be a good option to reduce technical losses in a distribution power grid. However, this non-linear combinatorial problem is not easy to assess by exact methods when solving for large distribution networks, which requires large computational times. For solving this type of problem, some researchers prefer to use metaheuristic techniques due to convergence speed, near-optimal solutions, and simple programming. Some literature reviews specialize in topics concerning the optimization of power network reconfiguration and try to cover most techniques. Nevertheless, this does not allow detailing properly the use of each technique, which is important to identify the trend. The contributions of this paper are three-fold. First, it presents the objective functions and constraints used in DNR with the most used metaheuristics. Second, it reviews the most important techniques such as particle swarm optimization (PSO), genetic algorithm (GA), simulated annealing (SA), ant colony optimization (ACO), immune algorithms (IA), and tabu search (TS). Finally, this paper presents the trend of each technique from 2011 to 2016. This paper will be useful for researchers interested in knowing the advances of recent approaches in these metaheuristics applied to DNR in order to continue developing new best algorithms and improving solutions for the topic
Referencias:

[1] Y. M. Atwa, E. F. El-Saadany, M. M. A. Salama, and R. Seethapathy, “Optimal Renewable Resources Mix for Distribution System Energy Loss Minimization,” IEEE Trans. Power Syst., vol. 25, no. 1, pp. 360–370, Feb. 2010. [2] D. Q. Hung, N. Mithulananthan, and R. C. Bansal, “Analytical strategies for renewable distributed generation integration considering energy loss minimization,” Appl. Energy, vol. 105, pp. 75–85, 2013. [3] D. Q. Hung, N. Mithulananthan, and R. C. Bansal, “Analytical Expressions for DG Allocation in Primary Distribution Networks,” IEEE Trans. Energy Convers., vol. 25, no. 3, pp. 814–820, Sep. 2010. [4] D. D. Wu, M. Junjie, W. Yulong, and L. Yang, “Size and Location of Distributed Generation in Distribution System Based on Immune Algorithm,” Syst. Eng. Procedia, vol. 4, pp. 124–132, 2012. [5] 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. [6] G. Naik, D. K. Khatod, and M. P. Sharma, “Optimal Allocation of Distributed Generation in Distribution System for Loss Reduction,” in International Proceedings of Computer Science and Information Technology IPCSIT, 2012. [7] A. K. Singh and S. K. Parida, “Selection of load buses for DG placement based on loss reduction and voltage improvement sensitivity,” in 2011 International Conference on Power Engineering, Energy and Electrical Drives, 2011, pp. 1–6. [8] L. Ramesh and S. Chowdhury, “Minimization of power Loss in distribution networks by different techniques,” Int. J. Electr. Electron. Eng., vol. 2, pp. 521–527, 2009. [9] Y.-K. Wu, C.-Y. Lee, L.-C. Liu, and S.-H. Tsai, “Study of Reconfiguration for the Distribution System With Distributed Generators,” IEEE Trans. Power Deliv., vol. 25, no. 3, pp. 1678– 1685, Jul. 2010. [10]R. S. Rao, K. Ravindra, K. Satish, and S. V. L. Narasimham, “Power Loss Minimization in Distribution System Using Network Reconfiguration in the Presence of Distributed Generation,” IEEE Trans. Power Syst., vol. 28, no. 1, pp. 317– 325, Feb. 2013. [11]A. Samui, S. Singh, T. Ghose, and S. R. Samantaray, “A Direct Approach to Optimal Feeder Routing for Radial Distribution System,” IEEE Trans. Power Deliv., vol. 27, no. 1, pp. 253–260, Jan. 2012. [12] a. R. Jordehi, “Optimisation of electric distribution systems: A review,” Renew. Sustain. Energy Rev., vol. 51, pp. 1088–1100, Nov. 2015. [13]S. Kalambe and G. Agnihotri, “Loss minimization techniques used in distribution network: bibliographical survey,” Renew. Sustain. Energy Rev., vol. 29, pp. 184–200, Jan. 2014. [14]R. J. Sarfi, M. M. a. Salama, and A. Y. Chikhani, “A survey of the state of the art in distribution system reconfiguration for system loss reduction,” Electr. Power Syst. Res., vol. 31, no. 1, pp. 61– 70, Oct. 1994. [15]L. Tang, F. Yang, and J. Ma, “A survey on distribution system feeder reconfiguration: Objectives and solutions,” in 2014 IEEE Innovative Smart Grid Technologies - Asia (ISGT ASIA), 2014, pp. 62–67. [16]A. Y. Abdelaziz, F. M. Mohamed, S. F. Mekhamer, and M. A. L. Badr, “Distribution system reconfiguration using a modified Tabu Search algorithm,” Electr. Power Syst. Res., vol. 80, no. 8, pp. 943–953, Aug. 2010. [17]H. Bagheri Tolabi, M. H. Ali, and M. Rizwan, “Simultaneous Reconfiguration, Optimal Placement of DSTATCOM, and Photovoltaic Array in a Distribution System Based on FuzzyACO Approach,” IEEE Trans. Sustain. Energy, vol. 6, no. 1, pp. 210–218, Jan. 2015. [18]S. Bruno, S. Lamonaca, M. La Scala, and U. Stecchi, “Integration of optimal reconfiguration tools in advanced distribution management system,” in 2012 3rd IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe), 2012, pp. 1–8. [19]A. M. Eldurssi and R. M. O’Connell, “A Fast Nondominated Sorting Guided Genetic Algorithm for Multi-Objective Power Distribution System Reconfiguration Problem,” IEEE Trans. Power Syst., vol. 30, no. 2, pp. 593–601, Mar. 2015. [20]J. Franco, M. Lavorato, M. J. Rider, and R. Romero, “An efficient implementation of tabu search in feeder reconfiguration of distribution systems,” in 2012 IEEE Power and Energy Society General Meeting, 2012, pp. 1–8. [21]C. Gu, J. Ji, and L. Liu, “Research of immune algorithms for reconfiguration of distribution network with distributed generations,” in The 26th Chinese Control and Decision Conference (2014 CCDC), 2014, pp. 2156–2160. [22]N. G. A. Hemdan, B. Deppe, M. Pielke, M. Kurrat, T. Schmedes, and E. Wieben, “Optimal reconfiguration of radial MV networks with load profiles in the presence of renewable energy based decentralized generation,” Electr. Power Syst. Res., vol. 116, pp. 355–366, Nov. 2014. [23]E. Herazo, M. Quintero, J. Candelo, J. Soto, and J. Guerrero, “Optimal power distribution network reconfiguration using Cuckoo Search,” in 2015 4th International Conference on Electric Power and Energy Conversion Systems (EPECS), 2015, pp. 1–6. [24]N. Kanwar, N. Gupta, K. R. Niazi, and A. Swarnkar, “Improved meta-heuristic techniques for simultaneous capacitor and DG allocation in radial distribution networks,” Int. J. Electr. Power Energy Syst., vol. 73, pp. 653–664, Dec. 2015. [25]P. Kritavorn, T. Lantharthong, and N. Rugthaicharoencheep, “The combined loss reduction approach to apply in distribution system with distribution generation,” in TENCON 2014 - 2014 IEEE Region 10 Conference, 2014, pp. 1–5. [26]S. Mehfuz and F. Rashid, “Ant colony system algorithm for optimal network reconfiguration,” Int. J. Comput. Intell. Syst., vol. 7, no. 5, pp. 973–978, Sep. 2014. [27]M. N. M. Nasir, N. M. Shahrin, M. F. Sulaima, M. H. Jali, and M. F. Baharom, “Optimum network reconfiguration and DGs sizing with allocation simultaneously by using particle swarm optimization (PSO),” Int. J. Eng. Technol., vol. 6, no. 2, pp. 773– 780, 2014. [28]T. T. Nguyen and A. V. Truong, “Distribution network reconfiguration for power loss minimization and voltage profile improvement using cuckoo search algorithm,” Int. J. Electr. Power Energy Syst., vol. 68, pp. 233–242, Jun. 2015. [29]S. Nie, X.-P. Fu, P. Li, F. Gao, C.-D. Ding, H. Yu, and C.-S. Wang, “Analysis of the impact of DG on distribution network reconfiguration using OpenDSS,” in IEEE PES Innovative Smart Grid Technologies, 2012, pp. 1–5. [30]T. Niknam, A. Kavousifard, and J. Aghaei, “Scenario-based multiobjective distribution feeder reconfiguration considering wind power using adaptive modified particle swarm optimisation,” IET Renew. Power Gener., vol. 6, no. 4, p. 236, 2012. [31]F. Nournejad, R. Kazemzade, and A. S. Yazdankhah, “A multiobjective evolutionary algorithm for distribution system reconfiguration,” in 16th Conference on Electrical Power Distribution Networks (EPDC), 2011, pp. 1–7. [32]J. Olamei, T. Niknam, A. Arefi, and A. H. Mazinan, “A novel hybrid evolutionary algorithm based on ACO and SA for distribution feeder reconfiguration with regard to DGs,” in 2011 IEEE GCC Conference and Exhibition (GCC), 2011, no. 2, pp. 259–262. [33]A. Saffar, R. Hooshmand, and A. Khodabakhshian, “A new fuzzy optimal reconfiguration of distribution systems for loss reduction and load balancing using ant colony search-based algorithm,” Appl. Soft Comput., vol. 11, no. 5, pp. 4021–4028, Jul. 2011. [34]F. Scenna, D. Anaut, L. I. Passoni, and G. J. Meschino, “Reconfiguration of electrical networks by an Ant Colony Optimization algorithm,” IEEE Lat. Am. Trans., vol. 11, no. 1, pp. 538–544, Feb. 2013. [35]N. H. Shamsudin, N. a Abidullah, a R. Abdullah, M. S. Mamat, and M. F. Sulaima, “A new technique for the reconfiguration of radial distribution network for loss minimization,” Int. J. Eng. Technol., vol. 6, no. 5, pp. 2488–2495, 2014. [36]N. H. Shamsudin, N. F. Omar, M. F. Sulaima, H. I. Jaafar, and A. F. A. Kadir, “The Distribution Network Reconfiguration Improved Performance of Genetic Algorithm Considering Power Losses and Voltage Profile,” Int. J. Eng. Technol., vol. 6, no. 2, pp. 1247–1258, 2014. [37]J. Shi, C. Wang, and P. An, “Loop-Based Coding Reactive Tabu Search for Comprehensive Optimization in Distribution Networks,” in 2011 Asia-Pacific Power and Energy Engineering Conference, 2011, pp. 1–4. [38]J. Shi, C. Wang, P. An, and H. Zhu, “Comparision of coding schemes for distribution networks reconfiguration,” in 2011 4th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), 2011, no. 2009, pp. 1816–1819. [39]S. S. F. Souza, R. Romero, and J. F. Franco, “Artificial immune networks Copt-aiNet and Opt-aiNet applied to the reconfiguration problem of radial electrical distribution systems,” Electr. Power Syst. Res., vol. 119, pp. 304–312, Feb. 2015. [40]M. F. Sulaima, M. N. M. Nasir, N. H. Shamsudin, M. Sulaiman, and W. M. Dahalan, “Implementation of Modified EPSO Technique in 69kV Distribution Network Reconfiguration for Losses Reduction,” Int. J. Eng. Technol., vol. 7, no. 2, pp. 502– 509, 2015. [41]S. Sultana and P. K. Roy, “Oppositional krill herd algorithm for optimal location of capacitor with reconfiguration in radial distribution system,” Int. J. Electr. Power Energy Syst., vol. 74, pp. 78–90, Jan. 2016. [42]A. Swarnkar, N. Gupta, and K. R. Niazi, “Adapted ant colony optimization for efficient reconfiguration of balanced and unbalanced distribution systems for loss minimization,” Swarm Evol. Comput., vol. 1, no. 3, pp. 129–137, Sep. 2011. [43]B. Tomoiagă, M. Chindriş, A. Sumper, R. Villafafila-Robles, and A. Sudria-Andreu, “Distribution system reconfiguration using genetic algorithm based on connected graphs,” Electr. Power Syst. Res., vol. 104, pp. 216–225, Nov. 2013. [44]C. Wang, A. Zhao, H. Dong, and Z. Li, “An Improved Immune Genetic Algorithm for Distribution Network Reconfiguration,” in 2009 International Conference on Information Management, Innovation Management and Industrial Engineering, 2009, pp. 218–223. [45]Xiaoli Meng, Limei Zhang, Pengwei Cong, Wei Tang, Xiaohui Zhang, and Dechang Yang, “Dynamic reconfiguration of distribution network considering scheduling of DG active power outputs,” in 2014 International Conference on Power System Technology, 2014, no. Powercon, pp. 1433–1439. [46]H. R. Esmaeilian and R. Fadaeinedjad, “Energy Loss Minimization in Distribution Systems Utilizing an Enhanced Reconfiguration Method Integrating Distributed Generation,” IEEE Syst. J., vol. 9, no. 4, pp. 1430–1439, Dec. 2015. [47]W.-C. Wu and M.-S. Tsai, “Application of simple examination and retrieval procedure in evolutionary algorithms for feeder reconfiguration,” Eur. Trans. Electr. Power, vol. 21, no. 1, pp. 1054–1071, Jan. 2011. [48]T. Niknam, M. Zare, J. Aghaei, and E. A. Farsani, “A new hybrid evolutionary optimization algorithm for distribution feeder reconfiguration,” Appl. Artif. Intell., vol. 26, no. 1–2, pp. 182– 182, Jan. 2012. [49]T. Niknam, E. Azadfarsani, and M. Jabbari, “A new hybrid evolutionary algorithm based on new fuzzy adaptive PSO and NM algorithms for Distribution Feeder Reconfiguration,” Energy Convers. Manag., vol. 54, no. 1, pp. 7–16, Feb. 2012. [50]A. A. A. Esmin and G. Lambert-Torres, “Application of particle swarm optimization to optimal power systems,” Int. J. Innov. Comput. Inf. Control, vol. 8, no. 3A, pp. 1705–1716, 2012. [51]E. Azad-Farsani, M. Zare, R. Azizipanah-Abarghooee, and H. Askarian-Abyaneh, “A new hybrid CPSO-TLBO optimization algorithm for distribution network reconfiguration,” J. Intell. FUZZY Syst., vol. 26, no. 5, pp. 2175–2184, 2014. [52]K. D. Mistry and R. Roy, “Impact of demand response program in wind integrated distribution network,” Electr. Power Syst. Res., vol. 108, pp. 269–281, Mar. 2014. [53]S. Chen, Z. Chen, X. Zhang, C. Su, and W. Hu, “Optimal reactive power and voltage control in distribution networks with distributed generators by fuzzy adaptive hybrid particle swarm optimisation method,” IET Gener. Transm. Distrib., vol. 9, no. 11, pp. 1096–1103, Aug. 2015. [54]H. Liang, “An Improved Optimization Algorithm for Network Skeleton,” Teh. Vjesn. Gaz., vol. 22, no. 6, pp. 1359–1363, 2015. [55]W.-T. Huang, T.-H. Chen, H.-T. Chen, J.-S. Yang, K.-L. Lian, Y.- R. Chang, Y.-D. Lee, and Y.-H. Ho, “A Two-stage Optimal Network Reconfiguration Approach for Minimizing Energy Loss of Distribution Networks Using Particle Swarm Optimization Algorithm,” Energies, vol. 8, no. 12, pp. 13894–13910, 2015. [56]R. Jabbari-Sabet, S.-M. Moghaddas-Tafreshi, and S.-S. Mirhoseini, “Microgrid operation and management using probabilistic reconfiguration and unit commitment,” Int. J. Electr. Power Energy Syst., vol. 75, pp. 328–336, Feb. 2016. [57]B. R. Jouybari, M. Hosseini, and Z. Byagowi, “Optimal Placement of Distributed Generators and Reconfiguration of Distribution Systems for Loss Reduction Using Genetic Algorithm,” Int. Rev. Electr. Eng., vol. 6, no. 2, B, pp. 1007–1012, 2011. [58]A. E. Milani and M. R. Haghifam, “An evolutionary approach for optimal time interval determination in distribution network reconfiguration under variable load,” Math. Comput. Model., vol. 57, no. 1–2, pp. 68–77, Jan. 2013. [59]A. Zidan and E. F. El-Saadany, “Distribution system reconfiguration for energy loss reduction considering the variability of load and local renewable generation,” Energy, vol. 59, pp. 698–707, Sep. 2013. [60]C. Wang and Y. Gao, “Determination of Power Distribution Network Configuration Using Non-Revisiting Genetic Algorithm,” IEEE Trans. Power Syst., vol. 28, no. 4, pp. 3638– 3648, Nov. 2013. [61]N. Gupta, A. Swarnkar, and K. R. Niazi, “Distribution network reconfiguration for power quality and reliability improvement using Genetic Algorithms,” Int. J. Electr. Power Energy Syst., vol. 54, pp. 664–671, Jan. 2014. [62]W. M. Dahalan, H. Mokhlis, R. Ahmad, A. H. Abu Bakar, and I. Musirin, “Simultaneous Network Reconfiguration and DG Sizing Using Evolutionary Programming and Genetic Algorithm to Minimize Power Losses,” Arab. J. Sci. Eng., vol. 39, no. 8, pp. 6327–6338, Aug. 2014. [63]X. Lei, H. Wu, Y. Shi, and P. Shi, “Distribution network reconfiguration based on parallel genetic membrane computing,” J. Intell. Fuzzy Syst., vol. 29, no. 5, pp. 2287–2298, Aug. 2015. [64]T. Niknam, E. A. Farsani, M. Nayeripour, and B. B. Firouzi, “Hybrid Fuzzy Adaptive Particle Swarm Optimization and Differential Evolution Algorithm for Distribution Feeder Reconfiguration,” Electr. Power Components Syst., vol. 39, no. 2, pp. 158–175, Jan. 2011. [65]A. R. Malekpour, T. Niknam, A. Pahwa, and A. Kavousi Fard, “Multi-Objective Stochastic Distribution Feeder Reconfiguration in Systems With Wind Power Generators and Fuel Cells Using the Point Estimate Method,” IEEE Trans. Power Syst., vol. 28, no. 2, pp. 1483–1492, May 2013. [66]M. J. Kasaei, “Distribution Network Reconfiguration for Optimal Operation of Distributed Generation with Ant Colony Algorithm,” Prz. ELEKTROTECHNICZNY, vol. 88, no. 12A, pp. 255–258, 2012. [67]A. Y. Abdelaziz, R. A. Osama, and S. M. Elkhodary, “Distribution Systems Reconfiguration Using Ant Colony Optimization and Harmony Search Algorithms,” Electr. Power Components Syst., vol. 41, no. 5, pp. 537–554, Mar. 2013. [68]S. Abazari and M. H. Soudejani, “A new technique for efficient reconfiguration of distribution networks,” Sci. Iran., vol. 22, no. 6, pp. 2516–2526, 2015. [69]C. H. N. D. R. Barbosa, R. F. Alexandre, and J. A. De Vasconcelos, “A practical codification and its analysis for the generalized reconfiguration problem,” Electr. Power Syst. Res., vol. 97, pp. 19–33, Apr. 2013. [70]L. W. de Oliveira, E. J. de Oliveira, F. V. Gomes, I. C. Silva, A. L. M. Marcato, and P. V. C. Resende, “Artificial Immune Systems applied to the reconfiguration of electrical power distribution networks for energy loss minimization,” Int. J. Electr. Power Energy Syst., vol. 56, pp. 64–74, Mar. 2014. [71]M. N. Muhtazaruddin, J. J. Jamian, G. Fujita, M. a. Baharudin, M. W. Wazir, and H. Mokhlis, “Distribution Network Loss Minimization via Simultaneous Distributed Generation Coordination with Network Reconfiguration,” Arab. J. Sci. Eng., vol. 39, no. 6, pp. 4923–4933, Jun. 2014. [72]F. R. Alonso, D. Q. Oliveira, and A. C. Zambroni de Souza, “Artificial Immune Systems Optimization Approach for Multiobjective Distribution System Reconfiguration,” IEEE Trans. Power Syst., vol. 30, no. 2, pp. 840–847, Mar. 2015. [73]A. Botea, J. Rintanen, and D. Banerjee, “Optimal Reconfiguration for Supply Restoration With Informed A* Search,” IEEE Trans. Smart Grid, vol. 3, no. 2, pp. 583–593, Jun. 2012. [74]L. W. de Oliveira, F. D. S. Seta, and E. J. de Oliveira, “Optimal reconfiguration of distribution systems with representation of uncertainties through interval analysis,” Int. J. Electr. Power Energy Syst., vol. 83, pp. 382–391, Dec. 2016. [75]S. S. F. Souza, R. Romero, J. Pereira, and J. T. Saraiva, “Artificial immune algorithm applied to distribution system reconfiguration with variable demand,” Int. J. Electr. Power Energy Syst., vol. 82, pp. 561–568, Nov. 2016. [76]S. . Nawaz, M. . Imran, A. K. . Sharma, and A. . Jain, “Optimal feeder reconfiguration and DG placement in distribution network,” Int. J. Appl. Eng. Res., vol. 11, no. 7, pp. 4878–4885, 2016. [77]Y. Lu, J. Wu, and L. Hao, “Multi-objective distribution network reconfiguration with distributed generations based on improved MOBPSO algorithm,” Dianli Xitong Baohu yu Kongzhi/Power Syst. Prot. Control, vol. 44, no. 7, pp. 62–68, 2016. [78]M. R. Haghifam, A. Moradkhani, and S. M. Miri Larimi, “Riskbased reconfiguration of active electric distribution networks,” IET Gener. Transm. Distrib., vol. 10, no. 4, pp. 1006–1015, Mar. 2016. [79]S. Chen, W. Hu, and Z. Chen, “Comprehensive Cost Minimization in Distribution Networks Using Segmented-Time Feeder Reconfiguration and Reactive Power Control of Distributed Generators,” IEEE Trans. Power Syst., vol. 31, no. 2, pp. 983– 993, Mar. 2016. [80]T. Zhang, S. Shi, and X. Xu, “Distribution network reconfiguration with distributed generation based on improved quantum binary particle swarm optimization,” Dianli Xitong Baohu yu Kongzhi/Power Syst. Prot. Control, vol. 44, no. 4, pp. 22–28, 2016. [81]H. . Yi, B. . Zhang, H. . Wang, Y. . Wu, G. . Yuan, and R. . Lü, “Distribution network dynamic reconfiguration method for improving distribution network’s ability of accepting DG,” Dianwang Jishu/Power Syst. Technol., vol. 40, no. 5, pp. 1431– 1436, 2016. [82]A. A. Zidan, M. F. Shaaban, and E. F. El-Saadany, “Impacts of Feeder Reconfiguration on Renewable Resources Allocation in Balanced and Unbalanced Distribution Systems,” Electr. Power Components Syst., vol. 44, no. 9, pp. 974–989, May 2016. [83]A. Asrari, S. Lotfifard, and M. Ansari, “Reconfiguration of Smart Distribution Systems With Time Varying Loads Using Parallel Computing,” IEEE Trans. Smart Grid, pp. 1–11, 2016. [84]C. Yan, Q. Luo, and Y. Chen, “An Efficient Hybrid Evolutionary Optimization Algorithm combining Ant Colony Optimization with Simulated Annealing,” Int. J. Digit. Content Technol. its Appl., vol. 5, no. 8, pp. 234–240, Aug. 2011. [85]W. Hui, Z. Liang, W. Wei, Z. Fei-fan, J. Xiu, and Z. Hong, “Distribution network reconstruction based on improved ant colony algorithm of directional pheromones,” in The 27th Chinese Control and Decision Conference (2015 CCDC), 2015, pp. 1243–1247. [86]Y. Xiang, J. Liu, M. Li, and W. Wang, “Two-stage Control Strategy for Structure Optimization of Faulted Distribution System with Distributed Generation,” Electr. Power Components Syst., vol. 42, no. 6, pp. 595–604, Apr. 2014. [87]M. R. Nayak, “Optimal feeder reconfiguration of distribution system with distributed generation units using HC-ACO,” Int. J. Electr. Eng. Informatics, vol. 6, no. 1, pp. 107–128, 2014. [88]N. I. Voropai and B. . Bat-Undraal, “Multicriteria Reconfiguration of Distribution Network with Distributed Generation,” J. Electr. Comput. Eng., vol. 2012, pp. 1–8, 2012. [89]M. J. . Kasaei and H. . Norouzi, “Reconfiguration of distribution network with dispersed generations based on ant colony algorithm,” Int. Rev. Model. Simulations, vol. 4, no. 6, pp. 3113– 3118, 2011. [90]H. . Takano, J. . Murata, Y. . Maki, and M. . Yasuda, “Improving the search ability of tabu search in the distribution network reconfiguration problem,” J. Adv. Comput. Intell. Intell. Informatics, vol. 17, no. 5, pp. 681–689, 2013. [91]A. Y. Abdelaziz, R. A. Osama, and S. M. El-Khodary, “Reconfiguration of distribution systems for loss reduction using the hyper-cube ant colony optimisation algorithm,” IET Gener. Transm. Distrib., vol. 6, no. 2, p. 176, 2012. [92]H. a. Abdelsalam, A. Y. Abdelaziz, and V. Mukherjee, “Optimal PMU placement in a distribution network considering network reconfiguration,” in 2014 International Conference on Circuits, Power and Computing Technologies [ICCPCT-2014], 2014, pp. 191–196. [93]A. Ahuja, A. Pahwa, B. K. Panigrahi, and S. Das, “PheromoneBased Crossover Operator Applied to Distribution System Reconfiguration,” IEEE Trans. Power Syst., vol. 28, no. 4, pp. 4144–4151, Nov. 2013. [94]W. An, Q. Zhou, X. Zhang, Y. Qin, and W. Chen, “An immune genetic algorithm based approach for distribution system reconfiguration,” in 2010 Sixth International Conference on Natural Computation, 2010, pp. 92–95. [95]J. Chen, F. Zhang, and Y. Zhang, “Distribution Network Reconfiguration Based on Simulated Annealing Immune Algorithm,” Energy Procedia, vol. 12, pp. 271–277, 2011. [96]F. Wang, Y. Li, Q. Liu, and X. Ji, “A multi-agent Immune-based Co-Taboo search algorithm for distribution network reconfiguration,” in 2011 International Conference on Electrical and Control Engineering, 2011, no. 3, pp. 953–956. [97]W. Wu and M. Tsai, “Application of Enhanced Integer Coded Particle Swarm Optimization for Distribution System Feeder Reconfiguration,” IEEE Trans. Power Syst., vol. 26, no. 3, pp. 1591–1599, Aug. 2011. [98]A. M. Othman, A. A. El-Fergany, and A. Y. Abdelaziz, “Optimal Reconfiguration Comprising Voltage Stability Aspect Using Enhanced Binary Particle Swarm Optimization Algorithm,” Electr. Power Components Syst., vol. 43, no. 14, pp. 1656–1666, Aug. 2015. [99]G. Graditi, M. L. Di Silvestre, D. La Cascia, E. Riva Sanseverino, and G. Zizzo, “On multi-objective optimal reconfiguration of MV networks in presence of different grounding,” J. Ambient Intell. Humaniz. Comput., vol. 7, no. 1, pp. 97–105, Feb. 2016. [100] V. Farahani, B. Vahidi, and H. A. Abyaneh, “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, May 2012. [101] S. Garcia-Martinez and E. Espinosa-Juarez, “Reconfiguration of power systems by applying Tabu search to minimize voltage sag indexes,” in 2011 North American Power Symposium, 2011, pp. 1–6. [102] S. García-Martínez and E. Espinosa-Juárez, “Optimal Reconfiguration of Electrical Networks by Applying Tabu Search to Decrease Voltage Sag Indices,” Electr. Power Components Syst., vol. 41, no. 10, pp. 943–959, Jul. 2013. [103] P. Mitra and G. K. Venayagamoorthy, “Implementation of an Intelligent Reconfiguration Algorithm for an Electric Ship’s Power System,” IEEE Trans. Ind. Appl., vol. 47, no. 5, pp. 2292– 2300, Sep. 2011. [104] C. Wang, Y. Liu, and Y. Zhao, “Application of dynamic neighborhood small population particle swarm optimization for reconfiguration of shipboard power system,” Eng. Appl. Artif. Intell., vol. 26, no. 4, pp. 1255–1262, Apr. 2013. [105] F. Shariatzadeh, C. B. Vellaithurai, S. S. Biswas, R. Zamora, and A. K. Srivastava, “Real-Time Implementation of Intelligent Reconfiguration Algorithm for Microgrid,” IEEE Trans. Sustain. Energy, vol. 5, no. 2, pp. 598–607, Apr. 2014. [106] H. Arasteh, M. S. Sepasian, and V. Vahidinasab, “An aggregated model for coordinated planning and reconfiguration of electric distribution networks,” Energy, vol. 94, pp. 786–798, 2016. [107] H. . b Wu, X. . Lei, B. . Liu, Y. . Lu, and G. . Xu, “Membrane computing based genetic algorithm for dynamic reconfiguration of distribution network with dividing time and considering electric vehicles and wind turbines,” Diangong Jishu Xuebao/Transactions China Electrotech. Soc., vol. 31, no. 2, pp. 196–205 and 220, 2016. [108] Z. Ghofrani-Jahromi, M. Kazemi, and M. Ehsan, “Distribution Switches Upgrade for Loss Reduction and Reliability Improvement,” IEEE Trans. Power Deliv., vol. 30, no. 2, pp. 684–692, Apr. 2015. [109] J. Kennedy and R. Eberhart, “Particle swarm optimization,” in Proceedings of ICNN’95 - International Conference on Neural Networks, 1995, vol. 4, pp. 1942–1948. [110] J. Kennedy and R. C. Eberhart, “A discrete binary version of the particle swarm algorithm,” in 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation, 1997, vol. 5, pp. 4104–4108. [111] S. Su, C. Lu, R. Chang, and G. Gutierrez-Alcaraz, “Distributed Generation Interconnection Planning: A Wind Power Case Study,” IEEE Trans. Smart Grid, vol. 2, no. 1, pp. 181–189, Mar. 2011. [112] S. Jazebi, M. Moghimi Haji, and R. A. Naghizadeh, “Distribution Network Reconfiguration in the Presence of Harmonic Loads: Optimization Techniques and Analysis,” IEEE Trans. Smart Grid, vol. 5, no. 4, pp. 1929–1937, Jul. 2014. [113] B. Amanulla, S. Chakrabarti, and S. N. Singh, “Reconfiguration of Power Distribution Systems Considering Reliability and Power Loss,” IEEE Trans. Power Deliv., vol. 27, no. 2, pp. 918– 926, Apr. 2012. [114] J. H. Holland, “Adaptation in Natural and Artificial Systems,” University of Michigan Press, Ann Arbor, 1975. [115] A. Zidan, M. F. Shaaban, and E. F. El-Saadany, “Long-term multi-objective distribution network planning by DG allocation and feeders’ reconfiguration,” Electr. Power Syst. Res., vol. 105, pp. 95–104, Dec. 2013. [116] G. L. Storti, M. Paschero, A. Rizzi, and F. M. Frattale Mascioli, “Comparison between time-constrained and time-unconstrained optimization for power losses minimization in Smart Grids using genetic algorithms,” Neurocomputing, vol. 170, pp. 353–367, Dec. 2015. [117] S. H. Alemohammad, E. Mashhour, and M. Saniei, “A marketbased method for reconfiguration of distribution network,” Electr. Power Syst. Res., vol. 125, pp. 15–22, Aug. 2015. [118] V. C. do Nascimento, G. Lambert-Torres, C. I. de A. Costa, and L. E. Borges da Silva, “Control model for distributed generation and network automation for microgrids operation,” Electr. Power Syst. Res., vol. 127, pp. 151–159, Oct. 2015. [119] S. Kirkpatrick, C. D. Gelatt, and M. P. Vecchi, “Optimization by Simulated Annealing,” Science (80-. )., vol. 220, no. 4598, pp. 671–680, 1983. [120] F. Nournejad, R. Kazemzade, and A. S. Yazdankhah, “A multiobjective evolutionary algorithm for distribution system reconfiguration,” in 16th Conference on Electrical Power Distribution Networks (EPDC), 2011, pp. 1–7. [121] R. Belkacemi and A. Feliachi, “Multi-agent design for power distribution system reconfiguration based on the artificial immune system algorithm,” in Proceedings of 2010 IEEE International Symposium on Circuits and Systems, 2010, pp. 3461–3464. [122] F. Glover, “Tabu Search—Part I,” ORSA J. Comput., vol. 1, no. 3, pp. 190–206, Feb. 1989. [123] F. Glover, “Tabu Search—Part II,” ORSA J. Comput., vol. 2, no. 1, pp. 4–32, 1990. [124] E. Espinosa Juarez and A. Hernandez, “An Analytical Approach for Stochastic Assessment of Balanced and Unbalanced Voltage Sags in Large Systems,” IEEE Trans. Power Deliv., vol. 21, no. 3, pp. 1493–1500, Jul. 2006. [125] V. S. Santos, P. R. V. Felipe, J. R. G. Sarduy, N. a. Lemozy, A. Jurado, and E. C. Quispe, “Procedure for Determining Induction Motor Efficiency Working Under Distorted Grid Voltages,” IEEE Trans. Energy Convers., vol. 30, no. 1, pp. 331–339, Mar. 2015. [126] J. Candelo and H. Hernández, “Distributed Generation Placement in Radial Distribution Networks using a Bat-inspired Algorithm,” DYNA, vol. 82, no. 192, pp. 60–67, Aug. 2015.

[1] Y. M. Atwa, E. F. El-Saadany, M. M. A. Salama, and R. Seethapathy, “Optimal Renewable Resources Mix for Distribution System Energy Loss Minimization,” IEEE Trans. Power Syst., vol. 25, no. 1, pp. 360–370, Feb. 2010. [2] D. Q. Hung, N. Mithulananthan, and R. C. Bansal, “Analytical strategies for renewable distributed generation integration considering energy loss minimization,” Appl. Energy, vol. 105, pp. 75–85, 2013. [3] D. Q. Hung, N. Mithulananthan, and R. C. Bansal, “Analytical Expressions for DG Allocation in Primary Distribution Networks,” IEEE Trans. Energy Convers., vol. 25, no. 3, pp. 814–820, Sep. 2010. [4] D. D. Wu, M. Junjie, W. Yulong, and L. Yang, “Size and Location of Distributed Generation in Distribution System Based on Immune Algorithm,” Syst. Eng. Procedia, vol. 4, pp. 124–132, 2012. [5] 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. [6] G. Naik, D. K. Khatod, and M. P. Sharma, “Optimal Allocation of Distributed Generation in Distribution System for Loss Reduction,” in International Proceedings of Computer Science and Information Technology IPCSIT, 2012. [7] A. K. Singh and S. K. Parida, “Selection of load buses for DG placement based on loss reduction and voltage improvement sensitivity,” in 2011 International Conference on Power Engineering, Energy and Electrical Drives, 2011, pp. 1–6. [8] L. Ramesh and S. Chowdhury, “Minimization of power Loss in distribution networks by different techniques,” Int. J. Electr. Electron. Eng., vol. 2, pp. 521–527, 2009. [9] Y.-K. Wu, C.-Y. Lee, L.-C. Liu, and S.-H. Tsai, “Study of Reconfiguration for the Distribution System With Distributed Generators,” IEEE Trans. Power Deliv., vol. 25, no. 3, pp. 1678– 1685, Jul. 2010. [10]R. S. Rao, K. Ravindra, K. Satish, and S. V. L. Narasimham, “Power Loss Minimization in Distribution System Using Network Reconfiguration in the Presence of Distributed Generation,” IEEE Trans. Power Syst., vol. 28, no. 1, pp. 317– 325, Feb. 2013. [11]A. Samui, S. Singh, T. Ghose, and S. R. Samantaray, “A Direct Approach to Optimal Feeder Routing for Radial Distribution System,” IEEE Trans. Power Deliv., vol. 27, no. 1, pp. 253–260, Jan. 2012. [12] a. R. Jordehi, “Optimisation of electric distribution systems: A review,” Renew. Sustain. Energy Rev., vol. 51, pp. 1088–1100, Nov. 2015. [13]S. Kalambe and G. Agnihotri, “Loss minimization techniques used in distribution network: bibliographical survey,” Renew. Sustain. Energy Rev., vol. 29, pp. 184–200, Jan. 2014. [14]R. J. Sarfi, M. M. a. Salama, and A. Y. Chikhani, “A survey of the state of the art in distribution system reconfiguration for system loss reduction,” Electr. Power Syst. Res., vol. 31, no. 1, pp. 61– 70, Oct. 1994. [15]L. Tang, F. Yang, and J. Ma, “A survey on distribution system feeder reconfiguration: Objectives and solutions,” in 2014 IEEE Innovative Smart Grid Technologies - Asia (ISGT ASIA), 2014, pp. 62–67. [16]A. Y. Abdelaziz, F. M. Mohamed, S. F. Mekhamer, and M. A. L. Badr, “Distribution system reconfiguration using a modified Tabu Search algorithm,” Electr. Power Syst. Res., vol. 80, no. 8, pp. 943–953, Aug. 2010. [17]H. Bagheri Tolabi, M. H. Ali, and M. Rizwan, “Simultaneous Reconfiguration, Optimal Placement of DSTATCOM, and Photovoltaic Array in a Distribution System Based on FuzzyACO Approach,” IEEE Trans. Sustain. Energy, vol. 6, no. 1, pp. 210–218, Jan. 2015. [18]S. Bruno, S. Lamonaca, M. La Scala, and U. Stecchi, “Integration of optimal reconfiguration tools in advanced distribution management system,” in 2012 3rd IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe), 2012, pp. 1–8. [19]A. M. Eldurssi and R. M. O’Connell, “A Fast Nondominated Sorting Guided Genetic Algorithm for Multi-Objective Power Distribution System Reconfiguration Problem,” IEEE Trans. Power Syst., vol. 30, no. 2, pp. 593–601, Mar. 2015. [20]J. Franco, M. Lavorato, M. J. Rider, and R. Romero, “An efficient implementation of tabu search in feeder reconfiguration of distribution systems,” in 2012 IEEE Power and Energy Society General Meeting, 2012, pp. 1–8. [21]C. Gu, J. Ji, and L. Liu, “Research of immune algorithms for reconfiguration of distribution network with distributed generations,” in The 26th Chinese Control and Decision Conference (2014 CCDC), 2014, pp. 2156–2160. [22]N. G. A. Hemdan, B. Deppe, M. Pielke, M. Kurrat, T. Schmedes, and E. Wieben, “Optimal reconfiguration of radial MV networks with load profiles in the presence of renewable energy based decentralized generation,” Electr. Power Syst. Res., vol. 116, pp. 355–366, Nov. 2014. [23]E. Herazo, M. Quintero, J. Candelo, J. Soto, and J. Guerrero, “Optimal power distribution network reconfiguration using Cuckoo Search,” in 2015 4th International Conference on Electric Power and Energy Conversion Systems (EPECS), 2015, pp. 1–6. [24]N. Kanwar, N. Gupta, K. R. Niazi, and A. Swarnkar, “Improved meta-heuristic techniques for simultaneous capacitor and DG allocation in radial distribution networks,” Int. J. Electr. Power Energy Syst., vol. 73, pp. 653–664, Dec. 2015. [25]P. Kritavorn, T. Lantharthong, and N. Rugthaicharoencheep, “The combined loss reduction approach to apply in distribution system with distribution generation,” in TENCON 2014 - 2014 IEEE Region 10 Conference, 2014, pp. 1–5. [26]S. Mehfuz and F. Rashid, “Ant colony system algorithm for optimal network reconfiguration,” Int. J. Comput. Intell. Syst., vol. 7, no. 5, pp. 973–978, Sep. 2014. [27]M. N. M. Nasir, N. M. Shahrin, M. F. Sulaima, M. H. Jali, and M. F. Baharom, “Optimum network reconfiguration and DGs sizing with allocation simultaneously by using particle swarm optimization (PSO),” Int. J. Eng. Technol., vol. 6, no. 2, pp. 773– 780, 2014. [28]T. T. Nguyen and A. V. Truong, “Distribution network reconfiguration for power loss minimization and voltage profile improvement using cuckoo search algorithm,” Int. J. Electr. Power Energy Syst., vol. 68, pp. 233–242, Jun. 2015. [29]S. Nie, X.-P. Fu, P. Li, F. Gao, C.-D. Ding, H. Yu, and C.-S. Wang, “Analysis of the impact of DG on distribution network reconfiguration using OpenDSS,” in IEEE PES Innovative Smart Grid Technologies, 2012, pp. 1–5. [30]T. Niknam, A. Kavousifard, and J. Aghaei, “Scenario-based multiobjective distribution feeder reconfiguration considering wind power using adaptive modified particle swarm optimisation,” IET Renew. Power Gener., vol. 6, no. 4, p. 236, 2012. [31]F. Nournejad, R. Kazemzade, and A. S. Yazdankhah, “A multiobjective evolutionary algorithm for distribution system reconfiguration,” in 16th Conference on Electrical Power Distribution Networks (EPDC), 2011, pp. 1–7. [32]J. Olamei, T. Niknam, A. Arefi, and A. H. Mazinan, “A novel hybrid evolutionary algorithm based on ACO and SA for distribution feeder reconfiguration with regard to DGs,” in 2011 IEEE GCC Conference and Exhibition (GCC), 2011, no. 2, pp. 259–262. [33]A. Saffar, R. Hooshmand, and A. Khodabakhshian, “A new fuzzy optimal reconfiguration of distribution systems for loss reduction and load balancing using ant colony search-based algorithm,” Appl. Soft Comput., vol. 11, no. 5, pp. 4021–4028, Jul. 2011. [34]F. Scenna, D. Anaut, L. I. Passoni, and G. J. Meschino, “Reconfiguration of electrical networks by an Ant Colony Optimization algorithm,” IEEE Lat. Am. Trans., vol. 11, no. 1, pp. 538–544, Feb. 2013. [35]N. H. Shamsudin, N. a Abidullah, a R. Abdullah, M. S. Mamat, and M. F. Sulaima, “A new technique for the reconfiguration of radial distribution network for loss minimization,” Int. J. Eng. Technol., vol. 6, no. 5, pp. 2488–2495, 2014. [36]N. H. Shamsudin, N. F. Omar, M. F. Sulaima, H. I. Jaafar, and A. F. A. Kadir, “The Distribution Network Reconfiguration Improved Performance of Genetic Algorithm Considering Power Losses and Voltage Profile,” Int. J. Eng. Technol., vol. 6, no. 2, pp. 1247–1258, 2014. [37]J. Shi, C. Wang, and P. An, “Loop-Based Coding Reactive Tabu Search for Comprehensive Optimization in Distribution Networks,” in 2011 Asia-Pacific Power and Energy Engineering Conference, 2011, pp. 1–4. [38]J. Shi, C. Wang, P. An, and H. Zhu, “Comparision of coding schemes for distribution networks reconfiguration,” in 2011 4th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), 2011, no. 2009, pp. 1816–1819. [39]S. S. F. Souza, R. Romero, and J. F. Franco, “Artificial immune networks Copt-aiNet and Opt-aiNet applied to the reconfiguration problem of radial electrical distribution systems,” Electr. Power Syst. Res., vol. 119, pp. 304–312, Feb. 2015. [40]M. F. Sulaima, M. N. M. Nasir, N. H. Shamsudin, M. Sulaiman, and W. M. Dahalan, “Implementation of Modified EPSO Technique in 69kV Distribution Network Reconfiguration for Losses Reduction,” Int. J. Eng. Technol., vol. 7, no. 2, pp. 502– 509, 2015. [41]S. Sultana and P. K. Roy, “Oppositional krill herd algorithm for optimal location of capacitor with reconfiguration in radial distribution system,” Int. J. Electr. Power Energy Syst., vol. 74, pp. 78–90, Jan. 2016. [42]A. Swarnkar, N. Gupta, and K. R. Niazi, “Adapted ant colony optimization for efficient reconfiguration of balanced and unbalanced distribution systems for loss minimization,” Swarm Evol. Comput., vol. 1, no. 3, pp. 129–137, Sep. 2011. [43]B. Tomoiagă, M. Chindriş, A. Sumper, R. Villafafila-Robles, and A. Sudria-Andreu, “Distribution system reconfiguration using genetic algorithm based on connected graphs,” Electr. Power Syst. Res., vol. 104, pp. 216–225, Nov. 2013. [44]C. Wang, A. Zhao, H. Dong, and Z. Li, “An Improved Immune Genetic Algorithm for Distribution Network Reconfiguration,” in 2009 International Conference on Information Management, Innovation Management and Industrial Engineering, 2009, pp. 218–223. [45]Xiaoli Meng, Limei Zhang, Pengwei Cong, Wei Tang, Xiaohui Zhang, and Dechang Yang, “Dynamic reconfiguration of distribution network considering scheduling of DG active power outputs,” in 2014 International Conference on Power System Technology, 2014, no. Powercon, pp. 1433–1439. [46]H. R. Esmaeilian and R. Fadaeinedjad, “Energy Loss Minimization in Distribution Systems Utilizing an Enhanced Reconfiguration Method Integrating Distributed Generation,” IEEE Syst. J., vol. 9, no. 4, pp. 1430–1439, Dec. 2015. [47]W.-C. Wu and M.-S. Tsai, “Application of simple examination and retrieval procedure in evolutionary algorithms for feeder reconfiguration,” Eur. Trans. Electr. Power, vol. 21, no. 1, pp. 1054–1071, Jan. 2011. [48]T. Niknam, M. Zare, J. Aghaei, and E. A. Farsani, “A new hybrid evolutionary optimization algorithm for distribution feeder reconfiguration,” Appl. Artif. Intell., vol. 26, no. 1–2, pp. 182– 182, Jan. 2012. [49]T. Niknam, E. Azadfarsani, and M. Jabbari, “A new hybrid evolutionary algorithm based on new fuzzy adaptive PSO and NM algorithms for Distribution Feeder Reconfiguration,” Energy Convers. Manag., vol. 54, no. 1, pp. 7–16, Feb. 2012. [50]A. A. A. Esmin and G. Lambert-Torres, “Application of particle swarm optimization to optimal power systems,” Int. J. Innov. Comput. Inf. Control, vol. 8, no. 3A, pp. 1705–1716, 2012. [51]E. Azad-Farsani, M. Zare, R. Azizipanah-Abarghooee, and H. Askarian-Abyaneh, “A new hybrid CPSO-TLBO optimization algorithm for distribution network reconfiguration,” J. Intell. FUZZY Syst., vol. 26, no. 5, pp. 2175–2184, 2014. [52]K. D. Mistry and R. Roy, “Impact of demand response program in wind integrated distribution network,” Electr. Power Syst. Res., vol. 108, pp. 269–281, Mar. 2014. [53]S. Chen, Z. Chen, X. Zhang, C. Su, and W. Hu, “Optimal reactive power and voltage control in distribution networks with distributed generators by fuzzy adaptive hybrid particle swarm optimisation method,” IET Gener. Transm. Distrib., vol. 9, no. 11, pp. 1096–1103, Aug. 2015. [54]H. Liang, “An Improved Optimization Algorithm for Network Skeleton,” Teh. Vjesn. Gaz., vol. 22, no. 6, pp. 1359–1363, 2015. [55]W.-T. Huang, T.-H. Chen, H.-T. Chen, J.-S. Yang, K.-L. Lian, Y.- R. Chang, Y.-D. Lee, and Y.-H. Ho, “A Two-stage Optimal Network Reconfiguration Approach for Minimizing Energy Loss of Distribution Networks Using Particle Swarm Optimization Algorithm,” Energies, vol. 8, no. 12, pp. 13894–13910, 2015. [56]R. Jabbari-Sabet, S.-M. Moghaddas-Tafreshi, and S.-S. Mirhoseini, “Microgrid operation and management using probabilistic reconfiguration and unit commitment,” Int. J. Electr. Power Energy Syst., vol. 75, pp. 328–336, Feb. 2016. [57]B. R. Jouybari, M. Hosseini, and Z. Byagowi, “Optimal Placement of Distributed Generators and Reconfiguration of Distribution Systems for Loss Reduction Using Genetic Algorithm,” Int. Rev. Electr. Eng., vol. 6, no. 2, B, pp. 1007–1012, 2011. [58]A. E. Milani and M. R. Haghifam, “An evolutionary approach for optimal time interval determination in distribution network reconfiguration under variable load,” Math. Comput. Model., vol. 57, no. 1–2, pp. 68–77, Jan. 2013. [59]A. Zidan and E. F. El-Saadany, “Distribution system reconfiguration for energy loss reduction considering the variability of load and local renewable generation,” Energy, vol. 59, pp. 698–707, Sep. 2013. [60]C. Wang and Y. Gao, “Determination of Power Distribution Network Configuration Using Non-Revisiting Genetic Algorithm,” IEEE Trans. Power Syst., vol. 28, no. 4, pp. 3638– 3648, Nov. 2013. [61]N. Gupta, A. Swarnkar, and K. R. Niazi, “Distribution network reconfiguration for power quality and reliability improvement using Genetic Algorithms,” Int. J. Electr. Power Energy Syst., vol. 54, pp. 664–671, Jan. 2014. [62]W. M. Dahalan, H. Mokhlis, R. Ahmad, A. H. Abu Bakar, and I. Musirin, “Simultaneous Network Reconfiguration and DG Sizing Using Evolutionary Programming and Genetic Algorithm to Minimize Power Losses,” Arab. J. Sci. Eng., vol. 39, no. 8, pp. 6327–6338, Aug. 2014. [63]X. Lei, H. Wu, Y. Shi, and P. Shi, “Distribution network reconfiguration based on parallel genetic membrane computing,” J. Intell. Fuzzy Syst., vol. 29, no. 5, pp. 2287–2298, Aug. 2015. [64]T. Niknam, E. A. Farsani, M. Nayeripour, and B. B. Firouzi, “Hybrid Fuzzy Adaptive Particle Swarm Optimization and Differential Evolution Algorithm for Distribution Feeder Reconfiguration,” Electr. Power Components Syst., vol. 39, no. 2, pp. 158–175, Jan. 2011. [65]A. R. Malekpour, T. Niknam, A. Pahwa, and A. Kavousi Fard, “Multi-Objective Stochastic Distribution Feeder Reconfiguration in Systems With Wind Power Generators and Fuel Cells Using the Point Estimate Method,” IEEE Trans. Power Syst., vol. 28, no. 2, pp. 1483–1492, May 2013. [66]M. J. Kasaei, “Distribution Network Reconfiguration for Optimal Operation of Distributed Generation with Ant Colony Algorithm,” Prz. ELEKTROTECHNICZNY, vol. 88, no. 12A, pp. 255–258, 2012. [67]A. Y. Abdelaziz, R. A. Osama, and S. M. Elkhodary, “Distribution Systems Reconfiguration Using Ant Colony Optimization and Harmony Search Algorithms,” Electr. Power Components Syst., vol. 41, no. 5, pp. 537–554, Mar. 2013. [68]S. Abazari and M. H. Soudejani, “A new technique for efficient reconfiguration of distribution networks,” Sci. Iran., vol. 22, no. 6, pp. 2516–2526, 2015. [69]C. H. N. D. R. Barbosa, R. F. Alexandre, and J. A. De Vasconcelos, “A practical codification and its analysis for the generalized reconfiguration problem,” Electr. Power Syst. Res., vol. 97, pp. 19–33, Apr. 2013. [70]L. W. de Oliveira, E. J. de Oliveira, F. V. Gomes, I. C. Silva, A. L. M. Marcato, and P. V. C. Resende, “Artificial Immune Systems applied to the reconfiguration of electrical power distribution networks for energy loss minimization,” Int. J. Electr. Power Energy Syst., vol. 56, pp. 64–74, Mar. 2014. [71]M. N. Muhtazaruddin, J. J. Jamian, G. Fujita, M. a. Baharudin, M. W. Wazir, and H. Mokhlis, “Distribution Network Loss Minimization via Simultaneous Distributed Generation Coordination with Network Reconfiguration,” Arab. J. Sci. Eng., vol. 39, no. 6, pp. 4923–4933, Jun. 2014. [72]F. R. Alonso, D. Q. Oliveira, and A. C. Zambroni de Souza, “Artificial Immune Systems Optimization Approach for Multiobjective Distribution System Reconfiguration,” IEEE Trans. Power Syst., vol. 30, no. 2, pp. 840–847, Mar. 2015. [73]A. Botea, J. Rintanen, and D. Banerjee, “Optimal Reconfiguration for Supply Restoration With Informed A* Search,” IEEE Trans. Smart Grid, vol. 3, no. 2, pp. 583–593, Jun. 2012. [74]L. W. de Oliveira, F. D. S. Seta, and E. J. de Oliveira, “Optimal reconfiguration of distribution systems with representation of uncertainties through interval analysis,” Int. J. Electr. Power Energy Syst., vol. 83, pp. 382–391, Dec. 2016. [75]S. S. F. Souza, R. Romero, J. Pereira, and J. T. Saraiva, “Artificial immune algorithm applied to distribution system reconfiguration with variable demand,” Int. J. Electr. Power Energy Syst., vol. 82, pp. 561–568, Nov. 2016. [76]S. . Nawaz, M. . Imran, A. K. . Sharma, and A. . Jain, “Optimal feeder reconfiguration and DG placement in distribution network,” Int. J. Appl. Eng. Res., vol. 11, no. 7, pp. 4878–4885, 2016. [77]Y. Lu, J. Wu, and L. Hao, “Multi-objective distribution network reconfiguration with distributed generations based on improved MOBPSO algorithm,” Dianli Xitong Baohu yu Kongzhi/Power Syst. Prot. Control, vol. 44, no. 7, pp. 62–68, 2016. [78]M. R. Haghifam, A. Moradkhani, and S. M. Miri Larimi, “Riskbased reconfiguration of active electric distribution networks,” IET Gener. Transm. Distrib., vol. 10, no. 4, pp. 1006–1015, Mar. 2016. [79]S. Chen, W. Hu, and Z. Chen, “Comprehensive Cost Minimization in Distribution Networks Using Segmented-Time Feeder Reconfiguration and Reactive Power Control of Distributed Generators,” IEEE Trans. Power Syst., vol. 31, no. 2, pp. 983– 993, Mar. 2016. [80]T. Zhang, S. Shi, and X. Xu, “Distribution network reconfiguration with distributed generation based on improved quantum binary particle swarm optimization,” Dianli Xitong Baohu yu Kongzhi/Power Syst. Prot. Control, vol. 44, no. 4, pp. 22–28, 2016. [81]H. . Yi, B. . Zhang, H. . Wang, Y. . Wu, G. . Yuan, and R. . Lü, “Distribution network dynamic reconfiguration method for improving distribution network’s ability of accepting DG,” Dianwang Jishu/Power Syst. Technol., vol. 40, no. 5, pp. 1431– 1436, 2016. [82]A. A. Zidan, M. F. Shaaban, and E. F. El-Saadany, “Impacts of Feeder Reconfiguration on Renewable Resources Allocation in Balanced and Unbalanced Distribution Systems,” Electr. Power Components Syst., vol. 44, no. 9, pp. 974–989, May 2016. [83]A. Asrari, S. Lotfifard, and M. Ansari, “Reconfiguration of Smart Distribution Systems With Time Varying Loads Using Parallel Computing,” IEEE Trans. Smart Grid, pp. 1–11, 2016. [84]C. Yan, Q. Luo, and Y. Chen, “An Efficient Hybrid Evolutionary Optimization Algorithm combining Ant Colony Optimization with Simulated Annealing,” Int. J. Digit. Content Technol. its Appl., vol. 5, no. 8, pp. 234–240, Aug. 2011. [85]W. Hui, Z. Liang, W. Wei, Z. Fei-fan, J. Xiu, and Z. Hong, “Distribution network reconstruction based on improved ant colony algorithm of directional pheromones,” in The 27th Chinese Control and Decision Conference (2015 CCDC), 2015, pp. 1243–1247. [86]Y. Xiang, J. Liu, M. Li, and W. Wang, “Two-stage Control Strategy for Structure Optimization of Faulted Distribution System with Distributed Generation,” Electr. Power Components Syst., vol. 42, no. 6, pp. 595–604, Apr. 2014. [87]M. R. Nayak, “Optimal feeder reconfiguration of distribution system with distributed generation units using HC-ACO,” Int. J. Electr. Eng. Informatics, vol. 6, no. 1, pp. 107–128, 2014. [88]N. I. Voropai and B. . Bat-Undraal, “Multicriteria Reconfiguration of Distribution Network with Distributed Generation,” J. Electr. Comput. Eng., vol. 2012, pp. 1–8, 2012. [89]M. J. . Kasaei and H. . Norouzi, “Reconfiguration of distribution network with dispersed generations based on ant colony algorithm,” Int. Rev. Model. Simulations, vol. 4, no. 6, pp. 3113– 3118, 2011. [90]H. . Takano, J. . Murata, Y. . Maki, and M. . Yasuda, “Improving the search ability of tabu search in the distribution network reconfiguration problem,” J. Adv. Comput. Intell. Intell. Informatics, vol. 17, no. 5, pp. 681–689, 2013. [91]A. Y. Abdelaziz, R. A. Osama, and S. M. El-Khodary, “Reconfiguration of distribution systems for loss reduction using the hyper-cube ant colony optimisation algorithm,” IET Gener. Transm. Distrib., vol. 6, no. 2, p. 176, 2012. [92]H. a. Abdelsalam, A. Y. Abdelaziz, and V. Mukherjee, “Optimal PMU placement in a distribution network considering network reconfiguration,” in 2014 International Conference on Circuits, Power and Computing Technologies [ICCPCT-2014], 2014, pp. 191–196. [93]A. Ahuja, A. Pahwa, B. K. Panigrahi, and S. Das, “PheromoneBased Crossover Operator Applied to Distribution System Reconfiguration,” IEEE Trans. Power Syst., vol. 28, no. 4, pp. 4144–4151, Nov. 2013. [94]W. An, Q. Zhou, X. Zhang, Y. Qin, and W. Chen, “An immune genetic algorithm based approach for distribution system reconfiguration,” in 2010 Sixth International Conference on Natural Computation, 2010, pp. 92–95. [95]J. Chen, F. Zhang, and Y. Zhang, “Distribution Network Reconfiguration Based on Simulated Annealing Immune Algorithm,” Energy Procedia, vol. 12, pp. 271–277, 2011. [96]F. Wang, Y. Li, Q. Liu, and X. Ji, “A multi-agent Immune-based Co-Taboo search algorithm for distribution network reconfiguration,” in 2011 International Conference on Electrical and Control Engineering, 2011, no. 3, pp. 953–956. [97]W. Wu and M. Tsai, “Application of Enhanced Integer Coded Particle Swarm Optimization for Distribution System Feeder Reconfiguration,” IEEE Trans. Power Syst., vol. 26, no. 3, pp. 1591–1599, Aug. 2011. [98]A. M. Othman, A. A. El-Fergany, and A. Y. Abdelaziz, “Optimal Reconfiguration Comprising Voltage Stability Aspect Using Enhanced Binary Particle Swarm Optimization Algorithm,” Electr. Power Components Syst., vol. 43, no. 14, pp. 1656–1666, Aug. 2015. [99]G. Graditi, M. L. Di Silvestre, D. La Cascia, E. Riva Sanseverino, and G. Zizzo, “On multi-objective optimal reconfiguration of MV networks in presence of different grounding,” J. Ambient Intell. Humaniz. Comput., vol. 7, no. 1, pp. 97–105, Feb. 2016. [100] V. Farahani, B. Vahidi, and H. A. Abyaneh, “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, May 2012. [101] S. Garcia-Martinez and E. Espinosa-Juarez, “Reconfiguration of power systems by applying Tabu search to minimize voltage sag indexes,” in 2011 North American Power Symposium, 2011, pp. 1–6. [102] S. García-Martínez and E. Espinosa-Juárez, “Optimal Reconfiguration of Electrical Networks by Applying Tabu Search to Decrease Voltage Sag Indices,” Electr. Power Components Syst., vol. 41, no. 10, pp. 943–959, Jul. 2013. [103] P. Mitra and G. K. Venayagamoorthy, “Implementation of an Intelligent Reconfiguration Algorithm for an Electric Ship’s Power System,” IEEE Trans. Ind. Appl., vol. 47, no. 5, pp. 2292– 2300, Sep. 2011. [104] C. Wang, Y. Liu, and Y. Zhao, “Application of dynamic neighborhood small population particle swarm optimization for reconfiguration of shipboard power system,” Eng. Appl. Artif. Intell., vol. 26, no. 4, pp. 1255–1262, Apr. 2013. [105] F. Shariatzadeh, C. B. Vellaithurai, S. S. Biswas, R. Zamora, and A. K. Srivastava, “Real-Time Implementation of Intelligent Reconfiguration Algorithm for Microgrid,” IEEE Trans. Sustain. Energy, vol. 5, no. 2, pp. 598–607, Apr. 2014. [106] H. Arasteh, M. S. Sepasian, and V. Vahidinasab, “An aggregated model for coordinated planning and reconfiguration of electric distribution networks,” Energy, vol. 94, pp. 786–798, 2016. [107] H. . b Wu, X. . Lei, B. . Liu, Y. . Lu, and G. . Xu, “Membrane computing based genetic algorithm for dynamic reconfiguration of distribution network with dividing time and considering electric vehicles and wind turbines,” Diangong Jishu Xuebao/Transactions China Electrotech. Soc., vol. 31, no. 2, pp. 196–205 and 220, 2016. [108] Z. Ghofrani-Jahromi, M. Kazemi, and M. Ehsan, “Distribution Switches Upgrade for Loss Reduction and Reliability Improvement,” IEEE Trans. Power Deliv., vol. 30, no. 2, pp. 684–692, Apr. 2015. [109] J. Kennedy and R. Eberhart, “Particle swarm optimization,” in Proceedings of ICNN’95 - International Conference on Neural Networks, 1995, vol. 4, pp. 1942–1948. [110] J. Kennedy and R. C. Eberhart, “A discrete binary version of the particle swarm algorithm,” in 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation, 1997, vol. 5, pp. 4104–4108. [111] S. Su, C. Lu, R. Chang, and G. Gutierrez-Alcaraz, “Distributed Generation Interconnection Planning: A Wind Power Case Study,” IEEE Trans. Smart Grid, vol. 2, no. 1, pp. 181–189, Mar. 2011. [112] S. Jazebi, M. Moghimi Haji, and R. A. Naghizadeh, “Distribution Network Reconfiguration in the Presence of Harmonic Loads: Optimization Techniques and Analysis,” IEEE Trans. Smart Grid, vol. 5, no. 4, pp. 1929–1937, Jul. 2014. [113] B. Amanulla, S. Chakrabarti, and S. N. Singh, “Reconfiguration of Power Distribution Systems Considering Reliability and Power Loss,” IEEE Trans. Power Deliv., vol. 27, no. 2, pp. 918– 926, Apr. 2012. [114] J. H. Holland, “Adaptation in Natural and Artificial Systems,” University of Michigan Press, Ann Arbor, 1975. [115] A. Zidan, M. F. Shaaban, and E. F. El-Saadany, “Long-term multi-objective distribution network planning by DG allocation and feeders’ reconfiguration,” Electr. Power Syst. Res., vol. 105, pp. 95–104, Dec. 2013. [116] G. L. Storti, M. Paschero, A. Rizzi, and F. M. Frattale Mascioli, “Comparison between time-constrained and time-unconstrained optimization for power losses minimization in Smart Grids using genetic algorithms,” Neurocomputing, vol. 170, pp. 353–367, Dec. 2015. [117] S. H. Alemohammad, E. Mashhour, and M. Saniei, “A marketbased method for reconfiguration of distribution network,” Electr. Power Syst. Res., vol. 125, pp. 15–22, Aug. 2015. [118] V. C. do Nascimento, G. Lambert-Torres, C. I. de A. Costa, and L. E. Borges da Silva, “Control model for distributed generation and network automation for microgrids operation,” Electr. Power Syst. Res., vol. 127, pp. 151–159, Oct. 2015. [119] S. Kirkpatrick, C. D. Gelatt, and M. P. Vecchi, “Optimization by Simulated Annealing,” Science (80-. )., vol. 220, no. 4598, pp. 671–680, 1983. [120] F. Nournejad, R. Kazemzade, and A. S. Yazdankhah, “A multiobjective evolutionary algorithm for distribution system reconfiguration,” in 16th Conference on Electrical Power Distribution Networks (EPDC), 2011, pp. 1–7. [121] R. Belkacemi and A. Feliachi, “Multi-agent design for power distribution system reconfiguration based on the artificial immune system algorithm,” in Proceedings of 2010 IEEE International Symposium on Circuits and Systems, 2010, pp. 3461–3464. [122] F. Glover, “Tabu Search—Part I,” ORSA J. Comput., vol. 1, no. 3, pp. 190–206, Feb. 1989. [123] F. Glover, “Tabu Search—Part II,” ORSA J. Comput., vol. 2, no. 1, pp. 4–32, 1990. [124] E. Espinosa Juarez and A. Hernandez, “An Analytical Approach for Stochastic Assessment of Balanced and Unbalanced Voltage Sags in Large Systems,” IEEE Trans. Power Deliv., vol. 21, no. 3, pp. 1493–1500, Jul. 2006. [125] V. S. Santos, P. R. V. Felipe, J. R. G. Sarduy, N. a. Lemozy, A. Jurado, and E. C. Quispe, “Procedure for Determining Induction Motor Efficiency Working Under Distorted Grid Voltages,” IEEE Trans. Energy Convers., vol. 30, no. 1, pp. 331–339, Mar. 2015. [126] J. Candelo and H. Hernández, “Distributed Generation Placement in Radial Distribution Networks using a Bat-inspired Algorithm,” DYNA, vol. 82, no. 192, pp. 60–67, Aug. 2015.