Optimal location and sizing of distributed generation for distribution systems: An improved analytical technique

References

• Acharya, N., P. Mahat, and N. Mithulananthan. 2006. An analytical approach for DG allocation in primary distribution network. International Journal of Electrical Power & Energy Systems 28 (10):669–78. doi:10.1016/j.ijepes.2006.02.013.
   Web of Science ®Google Scholar
• Ali, E. S., S. M. Abd Elazim, and A. Y. Abdelaziz. 2017. Ant lion optimization algorithm for optimal location and sizing of renewable distributed generations. Renewable Energy 101:1311–24. doi:10.1016/j.renene.2016.09.023.
   Web of Science ®Google Scholar
• Ali, A., M. U. Keerio, and J. A. Laghari. 2021. Optimal site and size of distributed generation allocation in radial distribution network using multi-objective optimization. Journal of Modern Power Systems and Clean Energy 9 (2):404–15. doi:10.35833/MPCE.2019.000055.
   Web of Science ®Google Scholar
• Babu, P. V., and S. P. Singh. 2016. Optimal placement of DG in distribution network for power loss minimization using NLP & PLS technique. Energy Procedia 90 (December 2015):441–54. doi:10.1016/j.egypro.2016.11.211.
   Google Scholar
• Bawazir, R. O., and N. S. Cetin. 2020. Comprehensive overview of optimizing PV-DG allocation in power system and solar energy resource potential assessments. Energy Reports 6:173–208. doi:10.1016/j.egyr.2019.12.010.
   Web of Science ®Google Scholar
• Bayat, A., and A. Bagheri. 2019a. Optimal active and reactive power allocation in distribution networks using a novel heuristic approach. Applied Energy 233-234 (August 2018):71–85. doi:10.1016/j.apenergy.2018.10.030.
   Google Scholar
• Bayat, A., and A. Bagheri. 2019b. Optimal active and reactive power allocation in distribution networks using a novel heuristic approach. Applied Energy 233-234 (October 2018):71–85. doi:10.1016/j.apenergy.2018.10.030.
   Google Scholar
• Camilo, F. M., R. Castro, M. E. Almeida, and V. F. Pires. 2016. Self-consumption and storage as a way to facilitate the integration of renewable energy in low voltage distribution networks. IET Generation, Transmission & Distribution 10 (7):1741–48. doi:10.1049/iet-gtd.2015.0431.
   Web of Science ®Google Scholar
• ChithraDevi, S. A., L. Lakshminarasimman, and R. Balamurugan. 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):748–59. doi:10.1016/j.jestch.2016.11.009.
   Google Scholar
• Daud, S., A. F. A. Kadir, C. K. Gan, A. Mohamed, and T. Khatib. 2016. A comparison of heuristic optimization techniques for optimal placement and sizing of photovoltaic based distributed generation in a distribution system. Solar Energy 140:219–26. doi:10.1016/j.solener.2016.11.013.
   Web of Science ®Google Scholar
• Elattar, E. E., S. Member, A. M. Shaheen, A. M. El-Sayed, R. A. El-Sehiemy, and S. Member. 2021. Optimal operation of automated distribution networks based-MRFO algorithm. Institute of Electrical and Electronics EngineersAccess 9:19586–601. doi:10.1109/ACCESS.2021.3053479.
   Google Scholar
• El-Fergany, A. 2015. Optimal allocation of multi-type distributed generators using backtracking search optimization algorithm. International Journal of Electrical Power & Energy Systems 64:1197–205. doi:10.1016/j.ijepes.2014.09.020.
   Web of Science ®Google Scholar
• Eo, O., A. To, O. Ik, and A. I. Oo. 2019. Optimal sitting and sizing of shunt capacitor for real power loss reduction on radial distribution system using firefly algorithm: A case study of Nigerian system. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects 00 (00):1–13. doi:10.1080/15567036.2019.1673507.
   Google Scholar
• Gampa, S. R., K. Jasthi, P. Goli, D. Das, and R. C. Bansal. 2020. Grasshopper optimization algorithm based two stage fuzzy multiobjective approach for optimum sizing and placement of distributed generations, shunt capacitors and electric vehicle charging stations. Journal of Energy Storage 27 (November 2019):101117. doi:10.1016/j.est.2019.101117.
   Google Scholar
• Hadidian-Moghaddam, M. J., S. Arabi-Nowdeh, M. Bigdeli, and D. Azizian. 2018. A multi-objective optimal sizing and siting of distributed generation using ant lion optimization technique. Ain Shams Engineering Journal 9 (4):2101–09. doi:10.1016/j.asej.2017.03.001.
   Web of Science ®Google Scholar
• Hemeida, M. G., A. A. Ibrahim, A. A. A. Mohamed, S. Alkhalaf, and A. M. B. El-Dine. 2021. Optimal allocation of distributed generators DG based manta ray foraging optimization algorithm (MRFO). Ain Shams Engineering Journal 12 (1):609–19. doi:10.1016/j.asej.2020.07.009.
   Web of Science ®Google Scholar
• Hung, D. Q., and N. Mithulananthan. 2013. Multiple distributed generator placement in primary distribution networks for loss reduction. IEEE Transactions on Industrial Electronics 60 (4):1700–08. doi:10.1109/TIE.2011.2112316.
   Web of Science ®Google Scholar
• Hussain, A., S. D. A. Shah, and S. M. Arif. 2019. Heuristic optimisation-based sizing and siting of DGs for enhancing resiliency of autonomous microgrid networks. IET Smart Grid 2 (2):269–82. doi:10.1049/iet-stg.2018.0209.
   Google Scholar
• Injeti, S. K., and N. Prema Kumar. 2013. A novel approach to identify optimal access point and capacity of multiple DGs in a small, medium and large scale radial distribution systems. International Journal of Electrical Power & Energy Systems 45 (1):142–51. doi:10.1016/j.ijepes.2012.08.043.
   Web of Science ®Google Scholar
• Jafar-Nowdeh, A., M. Babanezhad, and S. Arabi-Nowdeh. 2020. Meta-heuristic matrix moth–flame algorithm for optimal reconfiguration of distribution networks and placement of solar and wind renewable sources considering reliability. Environmental Technology & Innovation 20:101118. doi:10.1016/j.eti.2020.101118.
   Web of Science ®Google Scholar
• Kamel, S., A. Selim, W. Ahmed, and F. Jurado. 2020. Single- and multi-objective optimization for photovoltaic distributed generators implementation in probabilistic power flow algorithm. Electrical Engineering 102 (1):331–47. doi:10.1007/s00202-019-00878-7.
   Web of Science ®Google Scholar
• Kansal, S., V. Kumar, and B. Tyagi. 2016. Hybrid approach for optimal placement of multiple DGs of multiple types in distribution networks. International Journal of Electrical Power & Energy Systems 75:226–35. doi:10.1016/j.ijepes.2015.09.002.
   Web of Science ®Google Scholar
• Meena, N. K., S. Parashar, A. Swarnkar, N. Gupta, and K. R. Niazi. 2018. Improved elephant herding optimization for multiobjective der accommodation in distribution systems. IEEE Transactions on Industrial Informatics 14 (3):1029–39. doi:10.1109/TII.2017.2748220.
   Web of Science ®Google Scholar
• Meena, N. K., A. Swarnkar, N. Gupta, and K. R. Niazi. 2017. Multi-objective Taguchi approach for optimal DG integration in distribution systems. IET Generation, Transmission & Distribution 11 (9):2418–28. doi:10.1049/iet-gtd.2016.2126.
   Web of Science ®Google Scholar
• Mohanty, B., and S. Tripathy. 2016. A teaching learning based optimization technique for optimal location and size of DG in distribution network. Journal of Electrical Systems and Information Technology 3 (1):33–44. doi:10.1016/j.jesit.2015.11.007.
   Google Scholar
• Mohapatra, M., B. C. Babu, and K. B. Mohanty. 2016. Modeling and experimental investigation on vector control of grid-connected inverter-based distributed generation. Distributed Generation & Alternative Energy Journal 31 (4):6–26. doi:10.1080/21563306.2016.11781078.
   Google Scholar
• Montoya, O. D., W. Gil-González, and L. F. Grisales-Noreña. 2020. An exact MINLP model for optimal location and sizing of DGs in distribution networks: A general algebraic modeling system approach. Ain Shams Engineering Journal 11 (2):409–18. doi:10.1016/j.asej.2019.08.011.
   Web of Science ®Google Scholar
• Moradi, M. H., and M. Abedini. 2012. A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems. International Journal of Electrical Power & Energy Systems 34 (1):66–74. doi:10.1016/j.ijepes.2011.08.023.
   Web of Science ®Google Scholar
• Mosbah, M., A. Khattara, M. Becherif, and S. Arif. 2017. Optimal PV location choice considering static and dynamic constraints. International Journal of Emerging Electric Power Systems 18 (1). doi:10.1515/ijeeps-2016-0141.
   Google Scholar
• Naderipour, A., and Z. Abdul-Malek. 2020. Environmental technology & innovation carrier wave optimization for multi-level photovoltaic system to improvement of power quality in industrial environments based on salp swarm algorithm. Environmental Technology & Innovation 21 (xxxx):101197. doi:10.1016/j.eti.2020.101197.
   Google Scholar
• Naderipour, A., Z. Abdul-Malek, and S. A. Nowdeh. A multi-objective optimization problem for optimal site selection of wind turbines for reduce losses.
   Google Scholar
• Naderipour, A., S. A. Nowdeh, P. B. Saftjani, Z. Abdul-Malek, M. W. B. Mustafa, H. Kamyab, and I. F. Davoudkhani. 2021. Deterministic and probabilistic multi-objective placement and sizing of wind renewable energy sources using improved spotted hyena optimizer. Journal of Cleaner Production 286:124941. doi:10.1016/j.jclepro.2020.124941.
   Web of Science ®Google Scholar
• Nagaraju, K., S. Sivanagaraju, T. Ramana, and V. Ganesh. 2012. Enhancement of voltage stability in distribution systems by optimal placement of distribution generator. Distributed Generation & Alternative Energy Journal 27 (2):25–41. doi:10.1080/21563306.2012.10505410.
   Google Scholar
• Nguyen, T. P., V. N. Dieu, and P. Vasant. 2017. Symbiotic organism search algorithm for optimal size and siting of distributed generators in distribution systems. International Journal of Energy Optimization and Engineering 6 (3):1–28. doi:10.4018/ijeoe.2017070101.
   Google Scholar
• Nowdeh, S. A., I. F. Davoudkhani, M. J. H. Moghaddam, and E. S. Najmi. 2019. Fuzzy multi-objective placement of renewable energy sources in distribution system with objective of loss reduction and reliability improvement using a novel hybrid method. Applied Soft Computing 77:761–79. doi:10.1016/j.asoc.2019.02.003.
   Web of Science ®Google Scholar
• Pesaran, H. A. M., M. Nazari-Heris, B. Mohammadi-Ivatloo, and H. Seyedi. 2020. A hybrid genetic particle swarm optimization for distributed generation allocation in power distribution networks. Energy 209:118218. doi:10.1016/j.energy.2020.118218.
   Web of Science ®Google Scholar
• Rakočević, S., M. Ćalasan, and S. H. E. Abdel Aleem. 2021. Smart and coordinated allocation of static VAR compensators, shunt capacitors and distributed generators in power systems toward power loss minimization. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects 00 (00):1–19. doi:10.1080/15567036.2021.1930289.
   Google Scholar
• Sa’ed, J. A., M. Amer, A. Bodair, A. Baransi, S. Favuzza, and G. Zizzo. 2019. A simplified analytical approach for optimal planning of distributed generation in electrical distribution networks. Applied Sciences 9 (24):5446. doi:10.3390/app9245446.
   Google Scholar
• Selim, A., S. Kamel, A. S. Alghamdi, and F. Jurado. 2020. Optimal placement of DGs in distribution system using an improved Harris Hawks optimizer based on single- and multi-objective approaches. Institute of Electrical and Electronics Engineers Access 8:52815–29. doi:10.1109/ACCESS.2020.2980245.
   Google Scholar
• Selim, A., S. Kamel, and F. Jurado. 2020. Efficient optimization technique for multiple DG allocation in distribution networks. Applied Soft Computing 86:105938. doi:10.1016/j.asoc.2019.105938.
   Web of Science ®Google Scholar
• Shafiullah, G. M., M. T. Arif, and A. M. T. Oo. 2018. Mitigation strategies to minimize potential technical challenges of renewable energy integration. Sustainable Energy Technologies and Assessments 25 (October 2014):24–42. doi:10.1016/j.seta.2017.10.008.
   Google Scholar
• Shaheen, A. M., A. M. Elsayed, and A. R. Ginidi. 2021. Effective automation of distribution systems with joint integration of DGs/SVCs considering reconfiguration capability by jellyfish search algorithm. Institute of Electrical and Electronics EngineersAccess 9:92053–69. doi:10.1109/ACCESS.2021.3092337.
   Google Scholar
• Shaheen, A., A. Elsayed, A. Ginidi, and R. El-Sehiemy. 2022. Reconfiguration of electrical distribution network-based DG and capacitors allocations using artificial ecosystem optimizer: Practical case study. Alexandria Engineering Journal 61 (8):6105–18. doi:10.1016/j.aej.2021.11.035.
   Web of Science ®Google Scholar
• Shaheen, A. M., A. Elsayed, A. Ginidi, R. El-Sehiemy, and E. Elattar. 2022. Improved heap-based optimizer for DG allocation in reconfigured radial feeder distribution systems. IEEE Systems Journal 16 (4):6371–80. doi:10.1109/JSYST.2021.3136778.
   Web of Science ®Google Scholar
• Sudabattula, S. K., V. Suresh, U. Subramaniam, D. Almakhles, S. Padmanaban, and A. Iqbal. 2019. Optimal allocation of multiple distributed generators and shunt capacitors in distribution system using flower pollination algorithm. 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) (1):0–4. doi:10.1109/EEEIC.2019.8783417.
   Google Scholar
• Teng, J. H. 2003. A direct approach for distribution system load flow solutions. IEEE Transactions on Power Delivery 18 (3):882–87. doi:10.1109/TPWRD.2003.813818.
   Web of Science ®Google Scholar
• Willis, H. L. 2000. Analytical methods and rules of thumb for modeling DG-distribution interaction. 2000 Power Engineering Society Summer Meeting (Cat. No.00CH37134), 16–20 July 2000, Seattle, WA, USA. IEEE. 1643–44. doi:10.1109/PESS.2000.868774.
   Google Scholar