Abstract
The assimilation of distributed generators (DG) does play a critical role in modern distribution networks. Due to increasing demand for electrical energy, the DG sources are becoming more significant in distribution systems. The position and size of DG units will have an impact on losses and voltage profile of the distribution system. This work proposes implementing the Genetic Algorithm approach to determine the optimal site as well as the size of DG units in the distribution network to mitigate actual power losses and enhance the voltage profile. The optimal position and optimal capacity of DG unit is computed by GA algorithm and by using three indices namely PLRI, VDI and MORI we determine three solutions one for exclusively reduction in system loss, the second one for improvement of voltage profile and third one for combined benefit in minimization of losses and improved performance of the bus voltages, the proposed method is applied to the IEEE-33 bus test system. The programming is executed in the software MATLAB 2018α.
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References
Munson R (1988) Deregulation and the power struggle (electricity supply industry). IEEE Spectr 25(5):61–63
Acharya N, Mahat P, Mithulananthan N (2006) An analytical approach for DG allocation in primary distribution network. Int J Electr Power Energy Syst 28(10):669–678
Sandeep K, Ganesh K, Jaydev S (2014) A MINLP technique for optimal placement of multiple DG units in distribution systems. Int J Electr Power Energy Syst 63:609–617
Essallah S, Khedher A (2020) Optimization of distribution system operation by network reconfiguration and DG integration using MPSO algorithm. Renew Energy Focus 34:37–46. https://doi.org/10.1016/j.ref.2020.04.002
Das CK, Bass O, Thair GK, Mahmoud S, Habibi D (2018) Optimal placement of distributed energy storage systems in distribution networks using artificial bee colony algorithm. Appl Energy 232:212–228. https://doi.org/10.1016/j.apenergy.2018.07.100
Bilgundi SK, Kumar LMV (2017) Optimal capacitor placement in radial distribution system using artificial bee colony algorithm for voltage profile improvement and loss reduction. Int J Sci Res (IJSR) 6(11):2204–2208
Alhamali A, Farrag ME, Bevan G, Hepburn DM (2017) Determination of optimal site and capacity of DG systems in distribution network based on genetic algorithm.52nd International Universities Power Engineering Conference(UPEC). Heraklion 2017:1–6. https://doi.org/10.1109/UPEC.2017.8231996
Gopiya NS, Khatod DK (2018) Optimal siting and sizing of DG in Distributed networks for power loss saving. IOSR J Electr Electron Eng (IOSR-JEEE) 13(1):42–43
Yuvaraj T, Ravi K (2018) Multi-objective simultaneous DG and DSTATCOM allocation in radial distribution networks using cuckoo searching algorithm. Alex Eng J 57(4):2729–2742. https://doi.org/10.1016/j.aej.2018.01.001
Abdel-Rahman S, Mandour M, Ebtisam MS, Salama MM (2017) Optimal number size and location of distributed generation units in radial distribution systems using grey wolf optimizer. Int Electr Eng J (IEEJ) 7(9):2367–2376
Gopiya NS, Khatod DK, Sharma MP (2013) Optimal allocation of combined DG and capacitor for real power loss minimization in distribution networks. Int J Electr Power Energy Syst 53:967–973
Suresh MCV, Belwin EJ (2018) Optimal DG placement for benefit maximization in distribution networks by using Dragonfly algorithm. Renewables. https://doi.org/10.1186/s40807-018-0050-7
Mangla C, Ahmad M, Uddin M (2020) Optimization of complex nonlinear systems using genetic algorithm. Int J Inf Technol. https://doi.org/10.1007/s41870-020-00421-z
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Madhusudhan, M., Kumar, N. & Pradeepa, H. Optimal location and capacity of DG systems in distribution network using genetic algorithm. Int. j. inf. tecnol. 13, 155–162 (2021). https://doi.org/10.1007/s41870-020-00545-2
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DOI: https://doi.org/10.1007/s41870-020-00545-2