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Halve, Shrunkhala, Raghuwanshi, Santosh, Sonje, Deepak. (1405). Radial Distribution System Network Reconfiguration for Reduction in Real Power Loss and Improvement in Voltage Profile, and Reliability. سامانه مدیریت نشریات علمی, 14(2), 78-85. doi: 10.22098/joape.2024.14549.2113
Shrunkhala Halve; Santosh Raghuwanshi; Deepak Sonje. "Radial Distribution System Network Reconfiguration for Reduction in Real Power Loss and Improvement in Voltage Profile, and Reliability". سامانه مدیریت نشریات علمی, 14, 2, 1405, 78-85. doi: 10.22098/joape.2024.14549.2113
Halve, Shrunkhala, Raghuwanshi, Santosh, Sonje, Deepak. (1405). 'Radial Distribution System Network Reconfiguration for Reduction in Real Power Loss and Improvement in Voltage Profile, and Reliability', سامانه مدیریت نشریات علمی, 14(2), pp. 78-85. doi: 10.22098/joape.2024.14549.2113
Halve, Shrunkhala, Raghuwanshi, Santosh, Sonje, Deepak. Radial Distribution System Network Reconfiguration for Reduction in Real Power Loss and Improvement in Voltage Profile, and Reliability. سامانه مدیریت نشریات علمی, 1405; 14(2): 78-85. doi: 10.22098/joape.2024.14549.2113

Radial Distribution System Network Reconfiguration for Reduction in Real Power Loss and Improvement in Voltage Profile, and Reliability

Journal of Operation and Automation in Power Engineering
مقاله 1، دوره 14، شماره 2، تیر 2026، صفحه 78-85    اصل مقاله (1.3 M)
نوع مقاله: Research paper
شناسه دیجیتال (DOI): 10.22098/joape.2024.14549.2113
نویسندگان
Shrunkhala Halve* 1؛ Santosh Raghuwanshi2؛ Deepak Sonje3
1Department of Electrical Engineering, Gokhale Education Society R.H.Sapat COEMS and R, Nashik, India.
2Department of Electrical Engineering, Medi-Caps University, Indore, India.
3Department of Electrical Engineering, GESRH Sapat College of Engineering and Management Studies, Nashik, Maharastra, India.
چکیده
Distribution systems play a crucial role in delivering power to customers and bridging the gap between bulk power transmission and end-users. Increasing energy demand due to factors like industrial development and population growth necessitates efficient distribution system management. A low X/R ratio in distribution networks leads to higher real power losses, lower voltage profiles, and reduced system reliability. Selecting optimal combinations of sectionalizing and tie switches for network reconfiguration is a complex and time-consuming task. This article introduces the Modified load flow (MLF) method, which combines the backward/forward sweep method with an effective approach for selecting sectionalizing and tie switches to minimize real power loss. The MLF method offers advantages such as ease of implementation, requiring fewer control parameters, and scalability to large distribution systems. The proposed MLF method is compared with particle swarm optimization (PSO) and other existing algorithms in literature such as the cuckoo search algorithm (CSA), Improved sine cosine algorithm (ISCA), and Improved harmony search algorithm (IHSA). Results obtained from MLF and PSO to IEEE-33, 69, and 118 bus radial distribution systems demonstrate significant reductions in real power loss, with MLF outperforming PSO in terms of efficiency and effectiveness. Voltage profiles at critical buses before and after network reconfiguration are examined, showing improvements in MLF better than the PSO method. Various reliability indices are evaluated to assess system performance before and after network reconfiguration, demonstrating improvements in system reliability. Overall, the proposed modified load flow method offers a promising approach to address the challenges of real power losses and system reliability in radial distribution systems.
کلیدواژه‌ها
Radial distribution system؛ network reconfiguration؛ modified load flow؛ particle swarm optimization؛ distributed generation؛ substation
مراجع
  1. M. Mahdavi, H. H. Alhelou, N. D. Hatziargyriou, and A. AlHinai, “An efficient mathematical model for distribution system reconfiguration using ampl,” IEEE Access, vol. 9, pp. 79961–79993, 2021.
  2. S. R. Salkuti and N. R. Battu, “An effective network reconfiguration approach of radial distribution system for loss minimization and voltage profile improvement,” Bull. Electr. Eng. Inf., vol. 10, no. 4, pp. 1819–1827, 2021.
  3. P. Srividhya, K. Mounika, S. Kirithikaa, K. Narayanan, S. Gulshan, R. Girish Ganesan, and S. Tomonobu, “Reliability improvement of radial distribution system by reconfiguration,” Adv. Sci. Technol. Eng. Syst. J., vol. 5, no. 6, pp. 472–480, 2020.
  4. R. Priyadarshini, R. Prakash, and C. Shankaralingappa, “Network reconfiguration of radial distribution network using cuckoo search algorithm,” in 2015 Annu. IEEE India Conf. (INDICON), pp. 1–5, IEEE, 2015.
  5. 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, 2015.
  6. M. M. Ansari, C. Guo, M. S. Shaikh, N. Chopra, I. Haq, and L. Shen, “Planning for distribution system with grey wolf optimization method,” J. Electr. Eng. Technol., vol. 15, pp. 1485–1499, 2020.
  7. M. A. Muhammad, H. Mokhlis, K. Naidu, A. Amin, J. F. Franco, and M. Othman, “Distribution network planning enhancement via network reconfiguration and dg integration using dataset approach and water cycle algorithm,” J. Mod. Power Syst. Clean Energy, vol. 8, no. 1, pp. 86–93, 2019.
  8. G. Kumar, S. Kumar, and S. Kumar, “Reconfiguration of radial distribution system for loss reduction and reliability enhancement with dg placement,” Int. J. Appl. Eng. Res., vol. 13, no. 23, pp. 16356–16362, 2018.
  9. S. Kamel, H. Hamour, L. Nasrat, J. Yu, K. Xie, and
    M. Khasanov, “Radial distribution system reconfiguration for real power losses reduction by using salp swarm optimization algorithm,” in 2019 IEEE Innovative Smart Grid Technol.-Asia (ISGT Asia), pp. 720–725, IEEE, 2019.
  10. R. Rajaram, K. S. Kumar, and N. Rajasekar, “Power system reconfiguration in a radial distribution network for reducing losses and to improve voltage profile using modified plant growth simulation algorithm with distributed generation (dg),” Energy Rep., vol. 1, pp. 116–122, 2015.
  11. S. Jena and S. Chauhan, “Solving distribution feeder reconfiguration and concurrent dg installation problems for power loss minimization by multi swarm cooperative pso algorithm,” in 2016 IEEE/PES Trans. Distrib. Conf. Exposition (T&D), pp. 1–9, IEEE, 2016.
  12. M. Aman, G. Jasmon, A. H. A. Bakar, and H. Mokhlis, “A new approach for optimum simultaneous multi-dg distributed generation units placement and sizing based on maximization of system loadability using hpso (hybrid particle swarm optimization) algorithm,” Energy, vol. 66, pp. 202–215, 2014.
  13. S. R. Biswal, G. Shankar, R. M. Elavarasan, and L. Mihet-Popa, “Optimal allocation/sizing of dgs/capacitors in reconfigured radial distribution system using quasi-reflected slime mould algorithm,” IEEE Access, vol. 9, pp. 125658– 125677, 2021.
  14. B. Venkatesh, S. Chandramohan, N. Kayalvizhi, and R. K. Devi, “Optimal reconfiguration of radial distribuion system using artificial intelligence methods,” in 2009 IEEE Toronto Int. Conf. Sci. Technol. Humanity (TIC-STH), pp. 660–665, IEEE, 2009.
  15. J. Wang, W. Wang, H. Wang, and H. Zuo, “Dynamic reconfiguration of multiobjective distribution networks considering dg and evs based on a novel ldbas algorithm,” IEEE Access, vol. 8, pp. 216873–216893, 2020.
  16. B. Mohammadzadeh, A. Safari, and S. Najafi Ravadanegh, “Reliability and supply security based method for simultaneous placement of sectionalizer switch and der units,” J. Oper. Autom. Power Eng., vol. 4, no. 2, pp. 165– 174, 2016.
  17. S. Halve, A. Koshti, and R. Arya, “A sampling method based on system state transition for distribution system adequacy assessment using distributed generation,” J. Oper. Autom. Power Eng., vol. 11, no. 4, pp. 249–257, 2023.
  18. S. Gupta, J. Tripathi, A. Ranjan, R. Kesh, A. Kumar, M. Ranjan, and P. Sahu, “Optimal sizing of distributed power flow controller based on jellyfish optimizer,” J. Oper. Autom. Power Eng., vol. 12, no. 1, pp. 69–76, 2024.
  19. U. Raut and S. Mishra, “Power distribution network reconfiguration using an improved sine–cosine algorithmbased meta-heuristic search,” in Soft Comput. Probl. Solving: SocProS 2017, Volume 1, pp. 1–13, Springer, 2019.
  20. P. Khetrapal, “Distribution network reconfiguration of radial distribution systems for power loss minimization using improved harmony search algorithm.,” Int. J. Electr. Eng. Inf., vol. 12, no. 2, 2020.
  21. E. Bompard, E. Carpaneto, G. Chicco, and R. Napoli, “Convergence of the backward/forward sweep method for the load-flow analysis of radial distribution systems,” Int. J. Electr. Power Energy Syst., vol. 22, no. 7, pp. 521–530, 2000.
  22. S. S. Halve, R. Arya, and A. Koshti, “Locating, optimal sizing and reliability analysis of solar based dgs in radial distribution system,” J. Inst. Eng. (India): Series B, vol. 104, no. 1, pp. 201–213, 2023.
  23. A. S. Reddy and M. D. Reddy, “Optimization of network reconfiguration by using particle swarm optimization,” in 2016 IEEE 1st Int. Conf. Power Electron. Intell. Control Energy Syst. (ICPEICES), pp. 1–6, IEEE, 2016.
  24. M. E. Baran and F. F. Wu, “Network reconfiguration in distribution systems for loss reduction and load balancing,” IEEE Trans. Power Delivery, vol. 4, no. 2, pp. 1401–1407, 1989.
  25. N. Gupta, A. Swarnkar, and K. Niazi, “Distribution network reconfiguration for power quality and reliability improvement using genetic algorithms,” Int. J. Electr. Power Energy Syst., vol. 54, pp. 664–671, 2014.
  26. N. Sahoo and K. Prasad, “A fuzzy genetic approach for network reconfiguration to enhance voltage stability in radial distribution systems,” Energy Convers. Manage., vol. 47, no. 18-19, pp. 3288–3306, 2006.
  27. D. Zhang, Z. Fu, and L. Zhang, “An improved ts algorithm for loss-minimum reconfiguration in large-scale distribution systems,” Electr. Power Syst. Res., vol. 77, no. 5-6, pp. 685–694, 2007.
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