Loss Reduction and Improvement of Voltage Profile in Distribution System with Unbalanced Loading Conditions Using Chaotic Stochastic Fractal Search Algorithm

International Journal of Electrical and Electronics Engineering

© 2023 by SSRG - IJEEE Journal

Volume 10 Issue 1

Year of Publication : 2023

Authors : Chava Hari Babu, R. Hariharan

10.14445/23488379/IJEEE-V10I1P108

How to Cite?

Chava Hari Babu, R. Hariharan, "Loss Reduction and Improvement of Voltage Profile in Distribution System with Unbalanced Loading Conditions Using Chaotic Stochastic Fractal Search Algorithm," SSRG International Journal of Electrical and Electronics Engineering, vol. 10,  no. 1, pp. 83-89, 2023. Crossref, https://doi.org/10.14445/23488379/IJEEE-V10I1P108

Abstract:

This paper emphasizes the power network reconstructions that restore resources in unbalanced systems. The main objective is to improve the voltage profile and to reduce the power losses at each bus. With two processes of diffuse and update, the developed method is a meta-heuristic to get better results. A description of the solution to the service restoration is also achieved with case studies to show its effectiveness. The solution process established by the Chaotic Stochastic Fractal Search Algorithm (CSFSA) is used to search for switching conditions under unbalanced load conditions for IEEE 33-bus system. Research shows that the right pattern to change whether the opening or closing of switches may appear to give less power loss while satisfying all the constraints. It also highlights service delivery strategies in distribution systems under different considerations.

Keywords:

Radial distribution system, Feeder reconfiguration, Loss minimization, Bus voltage improvement, Unbalanced system.

References:

[1] M. A. Kashem, V. Ganapathy, and G. B. Jasmon, “Network Reconfiguration for Load Balancing in Distribution Networks,” IEE Proceedings Genereration, Transmission and Distribution, vol. 146, no. 6, pp. 563-567, 1999. Crossref, http://doi.org/10.1049/ip-gtd:19990694
[2] T.P. Wagner, A.Y. Chikhani, and R. Hackam, “Feeder Reconfiguration for Loss Reduction: An Application of Distribution Automation,” IEEE Transactions on Power Delivery, vol. 6, no. 4, pp. 1922-1933, 1991. Crossref, http://doi.org/10.1109/61.97741
[3] R. D. Zimmerman, “Network Reconfiguration for Loss Reduction in Three-Phase Power Distribution System,” Thesis of the Graduate Schoolof Cornell University, May, 1992.
[4] P. Subburaj et al., “Distribution System Reconfiguration for Loss Reduction Using Genetic Algorithm,” Journal of Electrical Systems, vol. 2, no. 4, pp. 198-207, 2006.
[5] Young-Jae Jeon, and Jae-chul Kim, “Network Reconfiguration in Radial Distribution System Using Simulated Annealing and Tabu Search,” IEEE Power Engineering Society Winter Meeting. Conference Proceedings, vol. 4, pp. 2329-2333, 2000. Crossref, http://doi.org/10.1109/PESW.2000.847169
[6] T. Taylor, and D. Lub Keman, “Implementation of Heuristic Search Strategies for Distribution Feeder Reconfiguration,” IEEE Transactions on Power Delivery, vol. 5, no. 1, pp. 239-246, 1990. Crossref, http://doi.org/10.1109/61.107279
[7] B.Vahini, and P.Sunita, "Identify the Impact of Distributed Resources on Congestion Management," SSRG International Journal of Communication and Media Science, vol. 4, no. 2, pp. 8-15, 2017. Crossref, https://doi.org/10.14445/2349641X/IJCMS-V4I4P101
[8] R. Ranjan et al., “Power Flow Solution of Three-Phase Unbalanced Radial Distribution Network,” Electric Power Components and Systems, vol. 32, no. 4, pp. 421-433, 2004. Crossref, https://doi.org/10.1080/15325000490217452
[9] Farzad Hosseinzadeh, Bahman Alinejad, and Keyvan Pakfa, “A New Technique in Distribution Network Reconfiguration for Loss Reduction and Optimum Operation,” International Conference and Exhibition on Electricity Distribution, Prague, pp. 1-3, 2009. Crossref, https://doi.org/10.1049/cp.2009.0778
[10] Veeresha K B, and Dr.Thejaswi A H, "Power System Faults Mitigation using Generalized Unified Power Quality Conditioner," SSRG International Journal of Electrical and Electronics Engineering, vol. 7, no. 10, pp. 16-21, 2020. Crossref, https://doi.org/10.14445/23488379/IJEEE-V7I10P103
[11] S. Civanlar et al., “Distribution Feeder Reconfiguration for Loss Reduction,” IEEE Transactions on Power Delivery, vol. 3, no. 3, pp. 1217–1223, 1988. Crossref, https://doi.org/10.1109/61.193906
[12] M. E. Baran, and F. Wu, “Network Reconfiguration in Distribution System for Loss Reduction and Load Balancing,” IEEE Transactions on Power Delivery, vol. 4, no. 2, pp. 1401-1407, 1989. Crossref, https://doi.org/10.1109/61.25627
[13] Thuan Thanh Nguyen, and Anh Viet Truong, “Distribution Network Reconfiguration for Power Loss Minimization and Voltage 14 Complexity Profile Improvement Using Cuckoo Search Algorithm,” International Journal of Electrical Power & Energy Systems, vol. 68, pp. 233–242, 2015. Crossref, https://doi.org/10.1016/j.ijepes.2014.12.075
[14] Thuan Thanh Nguyen, Anh Viet Truong, and Tuan Anh Phung, “A Novel Method Based on Adaptive Cuckoo Search for Optimal Network Reconfiguration and Distributed Generation Allocation in Distribution Network,” International Journal of Electrical Power & Energy Systems, vol. 78, pp. 801–815, 2016. Crossref, https://doi.org/10.1016/j.ijepes.2015.12.030
[15] Hamid Salimi, “Stochastic Fractal Search: A Powerful Metaheuristic Algorithm,” Knowledge-Based Systems, vol. 75, pp. 1–18, 2015. Crossref, https://doi.org/10.1016/j.knosys.2014.07.025
[16] Marko Mitić et al., “Chaotic Fruit Fly Optimization Algorithm,” Knowledge-Based Systems, vol. 89, pp. 446–458, 2015. Crossref, https://doi.org/10.1016/j.knosys.2015.08.010
[17] G.Vasudevan, and B.Sudhir Kumar, "Embedded Based Real Time Monitoring and Detection of Bacterial Contamination in Drinking Water Using ORP Measurement," SSRG International Journal of Electronics and Communication Engineering, vol. 2, no. 9, pp. 1-4, 2015. Crossref, https://doi.org/10.14445/23488549/IJECE-V2I9P101
[18] N. Rugthaicharoencheep, and S. Sirisumrannukul, “Feeder Reconfiguration for Loss Reduction in Three Phase Distribution System under Unbalanced Loading Conditions,” 45th International Universities Power Engineering Conference UPEC2010, pp. 1-6, 2010.
[19] Ganesh. Vulasala, Sivanagaraju. Sirigiri, and Ramana. Thiruveedula, “Feeder Reconfiguration for Loss Reduction in Unbalanced Distribution System Using Genetic Algorithm,” World Academy of Science, Engineering and Technology, vol. 3, no. 4, 2009.
[20] Anudevi.S, and Vinayak.N.Shet, "Distribution Network with Optimal DG Placement and Protection Impacts: Review Analysis," SSRG International Journal of Electrical and Electronics Engineering, vol. 4, no. 2, pp. 12-16, 2017. Crossref, https://doi.org/10.14445/23488379/IJEEE-V4I2P103
[21] N. C. Sahoo, and K. Prasad, “A Fuzzy Genetic Approach for Network Reconfiguration to Enhance Voltage Stability in Radial Distribution Systems,” Energy Conversion and Management, vol. 47, no. 18-19, pp. 3288–3306, 2006. Crossref, https://doi.org/10.1016/j.enconman.2006.01.004
[22] Rayapudi Srinivasa Rao et al., “Optimal Network Reconfiguration of Large-Scale Distribution System Using Harmony Search Algorithm,” IEEE Transactions on Power Systems, vol. 26, no. 3, pp. 1080–1088, 2011. Crossref, https://doi.org/10.1109/TPWRS.2010.2076839
[23] Sangeeta Das, Debapriya Das, and Amit Patra, “Reconfiguration of Distribution Networks with Optimal Placement of Distributed Generations in the Presence of Remote Voltage Controlled Bus,” Renewable and Sustainable Energy Reviews, vol. 73, pp. 772–781, 2017. Crossref, https://doi.org/10.1016/j.rser.2017.01.055
[24] Nishant Jakhar, and Rainu Nandal, "Load and Delay Effective based Resource Allocation And Scheduling Model to Optimize Power Distribution in Smart Grid Network," International Journal of Engineering Trends and Technology, vol. 70, no. 12, pp. 67-75, 2022. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I12P208
[25] Y.-C. Huang, “Enhanced-Genetic-Algorithm-Based Fuzzy Multi-Objective Approach to Distribution Network Reconfiguration,” IEE Proceedings—Generation, Transmission and Distribution, vol. 149, no. 5, pp. 615-620, 2002. Crossref, https://doi.org/10.1049/ip-gtd:20020512
[26] M.-R. Haghifam, J. Olamaei, and M.-R. Andervazh, “Adaptive Multi-Objective Distribution Network Reconfiguration Using Multi-Objective Discrete Particles Swarm Optimisation Algorithm And Graph Theory,” IET Generation, Transmission & Distribution, vol. 7, no. 12, pp. 1367–1382, 2013. Crossref, https://doi.org/10.1049/iet-gtd.2012.0712
[27] Mostafa Sedighizadeh, and Reza Bakhtiary, “Optimal Multi-Objective Reconfiguration and Capacitor Placement of Distribution Systems with the Hybrid Big Bang-Big Crunch Algorithm in the Fuzzy Framework,” Ain Shams Engineering Journal, vol. 7, no. 1, pp. 113-129, 2016. Crossref, https://doi.org/10.1016/j.asej.2015.11.018
[28] M.G.Anand, and R.Poomalai Prakash, "A DC–DC Quad Active Bridge Converter Based Hybrid Energy Storage Systems," International Journal of P2P Network Trends and Technology, vol. 4, no. 1, pp. 24-28 2014.
[29] J. B. V. Subrahmanyam, “Load Flow Solution of Unbalanced Radial Distribution Systems,” Journal of Theoretical and Applied Information Technology, vol. 6, no. 1, pp. 40-51, 2009.
[30] Hsiao-Dong Chiang et al., “Optimal Capacitor Placement, Replacement and Control in Large-Scale Unbalanced Distribution System: System Modelling and a New Formulation,” IEEE Transactions on Power Systems, vol. 10, no. 1, pp. 356-362, 1995. Crossref, https://doi.org/10.1109/59.373956
[31] Tung Tran The, Dieu Vo Ngoc, and Nguyen Tran Anh, “Distribution Network Reconfiguration for Power Loss Reduction and Voltage Profile Improvement Using haotic Stochastic Fractal Search Algorithm,” Hindawi Complexity, 2020. Crossref, https://doi.org/10.1155/2020/2353901
[32] Luonan Chen, and Kazuyuki Aihara, “Chaotic Simulated Annealing by a Neural Network Model with Transient Chaos,” Neural Networks, vol. 8, no. 6, pp. 915–930, 1995. Crossref, https://doi.org/10.1016/0893-6080(95)00033-V
[33] Ying-Yi Hong, and Saw-Yu Ho, “Determination of Network Configuration Considering Multiobjective in Distribution Systems Using Genetic Algorithms,” IEEE Transactions on Power Systems, vol. 20, no. 2, pp. 1062–1069, 2005. Crossref, https://doi.org/10.1109/TPWRS.2005.846067