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Pandraju, Thandava Krishna Sai, Janamala, Varaprasad. (1402). An Enhanced Pathfinder Algorithm for Optimal Integration of Solar Photovoltaics and Rapid Charging Stations in Low-Voltage Radial Feeders. , 8(4), 1680-1690. doi: 10.22059/jser.2023.359041.1300
Thandava Krishna Sai Pandraju; Varaprasad Janamala. "An Enhanced Pathfinder Algorithm for Optimal Integration of Solar Photovoltaics and Rapid Charging Stations in Low-Voltage Radial Feeders". , 8, 4, 1402, 1680-1690. doi: 10.22059/jser.2023.359041.1300
Pandraju, Thandava Krishna Sai, Janamala, Varaprasad. (1402). 'An Enhanced Pathfinder Algorithm for Optimal Integration of Solar Photovoltaics and Rapid Charging Stations in Low-Voltage Radial Feeders', , 8(4), pp. 1680-1690. doi: 10.22059/jser.2023.359041.1300
Pandraju, Thandava Krishna Sai, Janamala, Varaprasad. An Enhanced Pathfinder Algorithm for Optimal Integration of Solar Photovoltaics and Rapid Charging Stations in Low-Voltage Radial Feeders. , 1402; 8(4): 1680-1690. doi: 10.22059/jser.2023.359041.1300

An Enhanced Pathfinder Algorithm for Optimal Integration of Solar Photovoltaics and Rapid Charging Stations in Low-Voltage Radial Feeders

Journal of Solar Energy Research
دوره 8، شماره 4، دی 2023، صفحه 1680-1690    اصل مقاله (542.58 K)
نوع مقاله: Original Article
شناسه دیجیتال (DOI): 10.22059/jser.2023.359041.1300
نویسندگان
Thandava Krishna Sai Pandraju1؛ Varaprasad Janamala* 2
1Department of Electrical and Electronics Engineering, Dhanekula Institute of Engineering and Technology, Vijayawada - 521139, Andhra Pradesh, India.
2Dept. of Electrical and Electronics Engineering School of Engineering and Technology Christ (Deemed to be University) Bangalore - 560074. INDIA
چکیده
Most low-voltage (LV) feeders have significant losses, poor voltage profiles, and inadequate stability margins owing to their radial construction and high R/X ratio branches, thus, they may not be able to handle substantial solar photovoltaics (SPVs) and EV penetration. Thus, optimal integration of SPVs and rapid charging stations (RCSs) can solve this problem. This paper offers an enhanced pathfinder algorithm (EPFA) with guiding elements and three followers' life lifestyle procedures based on animal foraging, exploitation, and killing. First, the EV load penetration was used to evaluate the feeder performance. Subsequently, the required RCSs and SPVs were appropriately integrated to match the EV load penetration and optimise feeder performance. An Indian 85-bus real-time system was used for simulations. The losses and GHG emissions increased by 150% and 80%, respectively, without the SPVs and RCS for zero-to-full EV load penetration. RCSs allocation alone reduced the losses by 40.1%, whereas simultaneous SPVs and RCSs allocation reduced the losses by 66%. However, the GHG emissions decreased by 13.7% and 54.33%, respectively. This study shows that SPVs and RCS can enhance the feeder performance both technically and environmentally. In contrast, EPFA outperformed the other algorithms in terms of the global solution and convergence time.
کلیدواژه‌ها
Solar systems؛ EV Charging stations؛ Electrical distribution network؛ Pathfinder algorithm؛ Optimization
مراجع
  1. https://ourworldindata.org/renewable-energy.
  2. https://www.iea.org/reports/global-ev-outlook-2023/trends-in-electric-light-duty-vehicles.
  3. HA, M. P., Huy, P. D., & Ramachandaramurthy, V. K. (2017). A review of the optimal allocation of distributed generation: Objectives, constraints, methods, and algorithms. Renewable and Sustainable Energy Reviews, 75, 293-312. DOI: 1016/j.rser.2016.10.071
  4. Ehsan, A., & Yang, Q. (2018). Optimal integration and planning of renewable distributed generation in the power distribution networks: A review of analytical techniques. Applied Energy, 210, 44-59. DOI: 1016/j.apenergy.2017.10.106
  5. Tolba, M. A., Rezk, H., Al-Dhaifallah, M., & Eisa, A. A. (2020). Heuristic optimization techniques for connecting renewable distributed generators on distribution grids. Neural Computing and Applications, 32, 14195-14225. DOI: 1007/s00521-020-04812-y
  6. Reddy, P. D. P., Reddy, V. C. V., & Manohar, T. G. (2018). Optimal renewable resources placement in distribution networks by combined power loss index and whale optimization algorithms. Journal of Electrical Systems and Information Technology, 5(2), 175-191. DOI: 1016/j.jesit.2017.05.006
  7. Reddy, P. D. P., Reddy, V. C. V., & Manohar, T. G. (2018). Ant Lion optimization algorithm for optimal sizing of renewable energy resources for loss reduction in distribution systems. Journal of Electrical Systems and Information Technology, 5(3), 663-680. DOI: 1016/j.jesit.2017.06.001
  8. Suresh, M. C. V., & Belwin, E. J. (2018). Optimal DG placement for benefit maximization in distribution networks by using Dragonfly algorithm. Renewables: Wind, Water, and Solar, 5(1), 1-8. DOI: 1186/s40807-018-0050-7
  9. Reddy, P. D. P., Reddy, V. V., & Manohar, T. G. (2016). Application of flower pollination algorithm for optimal placement and sizing of distributed generation in distribution systems. Journal of Electrical Systems and Information Technology, 3(1), 14-22. DOI: 1016/j.jesit.2015.10.002
  10. Chithra Devi, S. A., Lakshminarasimman, L., & Balamurugan, R. (2017). Stud Krill herd Algorithm for multiple DG placement and sizing in a radial distribution system. Engineering Science and Technology, an International Journal, 20(2), 748-759. DOI: 1016/j.jestch.2016.11.009
  11. Ali, E. S., Abd Elazim, S. M., & Abdelaziz, A. Y. (2017). Ant Lion Optimization Algorithm for optimal location and sizing of renewable distributed generations. Renewable Energy, 101, 1311-1324. DOI: 1016/j.renene.2016.09.023
  12. Optimal allocation of distributed generators DG based Manta Ray Foraging Optimization algorithm (MRFO). (2021). Ain Shams Engineering Journal, 12(1), 609–619. DOI: 1016/j.asej.2020.07.009
  13. Optimal placement and sizing of multiple distributed generating units in distribution networks by invasive weed optimization algorithm. (2016). Ain Shams Engineering Journal, 7(2), 683–694. DOI: 1016/j.asej.2015.05.014
  14. Hemeida, M. G., Alkhalaf, S., Senjyu, T., Ibrahim, A., Ahmed, M., & Bahaa-Eldin, A. M. (2021). Optimal probabilistic location of DGs using Monte Carlo simulation based different bio-inspired algorithms. Ain Shams Engineering Journal, 12(3), 2735-2762. DOI: 1016/j.asej.2021.02.007
  15. Ali, M. H., Kamel, S., Hassan, M. H., Tostado-Véliz, M., & Zawbaa, H. M. (2022). An improved wild horse optimization algorithm for reliability based optimal DG planning of radial distribution networks. Energy Reports, 8, 582-604. DOI: 1016/j.egyr.2021.12.023
  16. Janamala, V., & Radha Rani, K. (2022). Optimal allocation of solar photovoltaic distributed generation in electrical distribution networks using Archimedes optimization algorithm. Clean Energy, 6(2), 271-287. DOI: 1093/ce/zkac010
  17. Selim, A., Kamel, S., Alghamdi, A. S., & Jurado, F. (2020). Optimal placement of DGs in distribution system using an improved harris hawks optimizer based on single-and multi-objective approaches. IEEE Access, 8, 52815-52829. 1109/access.2020.2980245
  18. Janamala, V., Kamal Kumar, U., & Pandraju, T. K. S. (2021). Future search algorithm for optimal integration of distributed generation and electric vehicle fleets in radial distribution networks considering techno-environmental aspects. SN Applied Sciences, 3(4), 464. DOI: 1007/s42452-021-04466-y
  19. Bhadoriya, J. S., & Gupta, A. R. (2021). A novel transient search optimization for optimal allocation of multiple distributed generator in the radial electrical distribution network. International Journal of Emerging Electric Power Systems, 23(1), 23-45. DOI: 1515/ijeeps-2021-0001
  20. Shahzad, M., Akram, W., Arif, M., Khan, U., & Ullah, B. (2021). Optimal siting and sizing of distributed generators by strawberry plant propagation algorithm. Energies, 14(6), 1744. DOI: 3390/en14061744
  21. Akbar, M. I., Kazmi, S. A. A., Alrumayh, O., Khan, Z. A., Altamimi, A., & Malik, M. M. (2022). A novel hybrid optimization-based algorithm for the single and multi-objective achievement with optimal DG allocations in distribution networks. IEEE Access, 10, 25669-25687. DOI: 1109/access.2022.3155484
  22. Das, H. S., Rahman, M. M., Li, S., & Tan, C. W. (2020). Electric vehicles standards, charging infrastructure, and impact on grid integration: A technological review. Renewable and Sustainable Energy Reviews, 120, 109618. 1016/j.rser.2019.109618
  23. Zeb, M. Z., Imran, K., Khattak, A., Janjua, A. K., Pal, A., Nadeem, M., ... & Khan, S. (2020). Optimal placement of electric vehicle charging stations in the active distribution network. IEEE Access, 8, 68124-68134. DOI: 1109/access.2020.2984127
  24. Khan, W., Ahmad, F., & Alam, M. S. (2019). Fast EV charging station integration with grid ensuring optimal and quality power exchange. Engineering Science and Technology, an International Journal, 22(1), 143-152. DOI: 1016/j.jestch.2018.08.005
  25. Dai, Q., Liu, J., & Wei, Q. (2019). Optimal photovoltaic/battery energy storage/electric vehicle charging station design based on multi-agent particle swarm optimization algorithm. Sustainability, 11(7), 1973. DOI: 3390/su11071973
  26. Injeti, S. K., & Thunuguntla, V. K. (2020). Optimal integration of DGs into radial distribution network in the presence of plug-in electric vehicles to minimize daily active power losses and to improve the voltage profile of the system using bio-inspired optimization algorithms. Protection and Control of Modern Power Systems, 5, 1-15. DOI: 1186/s41601-019-0149-xA new meta-heuristic optimizer: Pathfinder algorithm. (2019). Applied Soft Computing, 78, 545–568. DOI: 10.1016/j.asoc.2019.03.012
  27. An enhanced pathfinder algorithm for engineering optimization problems. (2021). Engineering with Computers, 38(S2), 1481–1503. DOI: 1007/s00366-021-01286-x
  28. A new power flow method for radial distribution systems including voltage dependent load models. (2005). Electric Power Systems Research, 76(1-3), 106–114. DOI: 1016/j.epsr.2005.05.008
  29. Abdel-Akher, M., Eid, A., & Ali, A. (2017). Effective demand side scheme for PHEVs operation considering voltage stability of power distribution systems. International Journal of Emerging Electric Power Systems, 18(2), 20160041. DOI: 1515/ijeeps-2016-0041
  30. Janamala, V., & Radha Rani, K. (2022). Optimal allocation of solar photovoltaic distributed generation in electrical distribution networks using Archimedes optimization algorithm. Clean Energy, 6(2), 271-287.
  31. Rani, K. R., Rani, P. S., Chaitanya, N., & Janamala, V. (2022). Improved Bald Eagle Search for Optimal Allocation of D-STATCOM in Modern Electrical Distribution Networks with Emerging Loads. International Journal of Intelligent Engineering & Systems, 15(2), 554-563. DOI: 10.22266/ijies2022.0430.49
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