References
- Saber, A. Y., & Venayagamoorthy, G. K. (2010). Plug-in vehicles and renewable energy sources for cost and emission reductions. IEEE Transactions on Industrial electronics, 58(4), 1229–1238. DOI: 10.1109/TIE.2010.2047828
- Muttaqi, K. M., Le, A. D., Negnevitsky, M., & Ledwich, G. (2014). An algebraic approach for determination of DG parameters to support voltage profiles in radial distribution networks. IEEE Transactions on Smart Grid, 5(3), 1351–1360. DOI: 10.1109/TSG.2014.2303194
- Saha, S., & Mukherjee, V. (2016). Optimal placement and sizing of DGs in RDS using chaos embedded SOS algorithm. IET Generation, Transmission & Distribution, 10(14), 3671–3680. DOI: 10.1049/iet-gtd.2016.0151
- Ayalew, M., Khan, B., Giday, I., Mahela, O. P., Khosravy, M., Gupta, N., & Senjyu, T. (2022). Integration of renewable based distributed generation for distribution network expansion planning. Energies, 15(4), 1378. DOI: 10.3390/en15041378
- Stanelytė, D., & Radziukynas, V. (2022). Analysis of voltage and reactive power algorithms in low voltage networks. Energies, 15(5), 1843. DOI: 10.3390/en15051843
- Georgilakis, P. S., & Hatziargyriou, N. D. (2013). Optimal distributed generation placement in power distribution networks: models, methods, and future research. IEEE Transactions on power systems, 28(3), 3420–3428. DOI: 10.1109/TPWRS.2012.2237043
- Dorostkar-Ghamsari, M. R., Fotuhi-Firuzabad, M., Lehtonen, M., & Safdarian, A. (2015). Value of distribution network reconfiguration in presence of renewable energy resources. IEEE Transactions on Power Systems, 31(3), 1879–1888. DOI: 10.1109/TPWRS.2015.2457954
- Ali, A., Raisz, D., & Mahmoud, K. (2019). Optimal oversizing of utility-owned renewable DG inverter for voltage rise prevention in MV distribution systems. International Journal of Electrical Power & Energy Systems, 105, 500–513. DOI: 10.1016/j.ijepes.2018.08.040
- Ufa, R. A., Malkova, Y. Y., Rudnik, V. E., Andreev, M. V., & Borisov, V. A. (2022). A review on distributed generation impacts on electric power system. International journal of hydrogen energy, 47(47), 20347–20361. DOI: 10.1016/j.ijhydene.2022.04.142
- Viral, R., & Khatod, D. K. (2015). An analytical approach for sizing and siting of DGs in balanced radial distribution networks for loss minimization. International Journal of Electrical Power & Energy Systems, 67, 191–201. DOI: 10.1016/j.ijepes.2014.11.017
- Mahmoud, K., Yorino, N., & Ahmed, A. (2015). Optimal distributed generation allocation in distribution systems for loss minimization. IEEE Transactions on power systems, 31(2), 960–969. DOI: 10.1109/TPWRS.2015.2418333
- Kayal, P., Chanda, S., & Chanda, C. K. (2017). An analytical approach for allocation and sizing of distributed generations in radial distribution network. International Transactions on Electrical Energy Systems, 27(7), e2322. DOI: 10.1002/etep.2322
- El-Fergany, A. (2015). Optimal allocation of multi-type distributed generators using backtracking search optimization algorithm. International Journal of Electrical Power & Energy Systems, 64, 1197–1205. DOI: 10.1016/j.ijepes.2014.09.020
- Abou El-Ela, A. A., El-Sehiemy, R. A., & Abbas, A. S. (2018). Optimal placement and sizing of distributed generation and capacitor banks in distribution systems using water cycle algorithm. IEEE Systems Journal, 12(4), 3629–3636. DOI: 10.1109/JSYST.2018.2796847
- Pham, T. D., Nguyen, T. T., & Dinh, B. H. (2021). Find optimal capacity and location of distributed generation units in radial distribution networks by using enhanced coyote optimization algorithm. Neural Computing and Applications, 33(9), 4343–4371. DOI: 10.1007/s00521-020-05239-1
- Sultana, S., & Roy, P. K. (2014). Multi-objective quasi-oppositional teaching learning based optimization for optimal location of distributed generator in radial distribution systems. International Journal of Electrical Power & Energy Systems, 63, 534–545. DOI: 10.1016/j.ijepes.2014.06.031
- Nagaballi, S., & Kale, V. S. (2020). Pareto optimality and game theory approach for optimal deployment of DG in radial distribution system to improve techno-economic benefits. Applied Soft Computing, 92, 106234. DOI: 10.1016/j.asoc.2020.106234
- Sharma, S., Bhattacharjee, S., & Bhattacharya, A. (2016). Quasi-Oppositional Swine Influenza Model Based Optimization with Quarantine for optimal allocation of DG in radial distribution network. International Journal of Electrical Power & Energy Systems, 74, 348–373. DOI: 10.1016/j.ijepes.2015.07.034
- Imran, A. M., Kowsalya, M., & Kothari, D. P. (2014). A novel integration technique for optimal network reconfiguration and distributed generation placement in power distribution networks. International Journal of Electrical Power & Energy Systems, 63, 461–472. DOI: 10.1016/j.ijepes.2014.06.011
- Rao, R. S., Ravindra, K., Satish, K., & Narasimham, S. V. L. (2012). Power loss minimization in distribution system using network reconfiguration in the presence of distributed generation. IEEE transactions on power systems, 28(1), 317–325. DOI: 10.1109/TPWRS.2012.2197227
- Kowsalya, M. (2014). Optimal size and siting of multiple distributed generators in distribution system using bacterial foraging optimization. Swarm and Evolutionary computation, 15, 58–65. DOI: 10.1016/j.swevo.2013.12.001
- Balu, K., & Mukherjee, V. (2021). Optimal siting and sizing of distributed generation in radial distribution system using a novel student psychology-based optimization algorithm. Neural Computing and Applications, 33(22), 15639–15667. DOI: 10.1007/s00521-021-06185-2
- Khasanov, M., Kamel, S., Rahmann, C., Hasanien, H. M., & Al-Durra, A. (2021). Optimal distributed generation and battery energy storage units integration in distribution systems considering power generation uncertainty. IET Generation, Transmission & Distribution, 15(24), 3400–3422. DOI: 10.1049/gtd2.12230
- Uniyal, A., & Sarangi, S. (2021). Optimal network reconfiguration and DG allocation using adaptive modified whale optimization algorithm considering probabilistic load flow. Electric Power Systems Research, 192, 106909. DOI: 10.1016/j.epsr.2020.106909
- El-maksoud, A., Ahmed, A. H., & Hasan, S. (2023). Simultaneous Optimal Network Reconfiguration and Allocation of Four Different Distributed Generation Types in Radial Distribution Networks Using a Graph Theory-Based MPSO Algorithm. International Journal of Intelligent Engineering & Systems, 16(2). DOI: 10.22266/ijies2023.0430.24
- 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: 10.1016/j.apenergy.2017.10.106
- Ameli, A., Bahrami, S., Khazaeli, F., & Haghifam, M. R. (2014). A multiobjective particle swarm optimization for sizing and placement of DGs from DG owner’s and distribution company’s viewpoints. IEEE Transactions on power delivery, 29(4), 1831–1840. DOI: 10.1109/TPWRD.2014.2300845
- Pon Ragothama Priya, P., Baskar, S., Tamil Selvi, S., & Babulal, C. K. (2023). Optimal allocation of distributed generation using evolutionary multi-objective optimization. Journal of Electrical Engineering & Technology, 18(2), 869–886. DOI: 10.1007/s42835-022-01269-y
- Settoul, S., Chenni, R., Zellagui, M., & Nouri, H. (2021). Optimal integration of renewable distributed generation using the whale optimization algorithm for techno-economic analysis. Lecture Notes in Electrical Engineering, 682, 513–532. DOI: 10.1007/978-981-15-6403-1_35
- Selim, A., Kamel, S., Jurado, F., Lopes, J. A. P., & Matos, M. (2021). Optimal setting of PV and battery energy storage in radial distribution systems using multi-objective criteria with fuzzy logic decision-making. IET generation, transmission & distribution, 15(1), 135–148. DOI: 10.1049/gtd2.12019
- Adepoju, G. A., Salimon, S. A., Adebayo, I. G., & Adewuyi, O. B. (2024). Impact of DSTATCOM penetration level on technical benefits in radial distribution network. e-Prime-Advances in Electrical Engineering, Electronics and Energy, 7, 100413. DOI: 10.1016/j.prime.2023.100413
- Gao, H., Diao, R., Zhong, Y., Zeng, R., Wu, Q., & Jin, S. (2024). Optimal allocation of distributed generation in active distribution power network considering HELM-based stability index. International Journal of Electrical Power & Energy Systems, 155, 109508. DOI: 10.1016/j.ijepes.2023.109508
- Adetunji, K. E., Hofsajer, I. W., Abu-Mahfouz, A. M., & Cheng, L. (2020). A review of metaheuristic techniques for optimal integration of electrical units in distribution networks. IEEE Access, 9, 5046–5068. DOI: 10.1109/ACCESS.2020.3048438
- Belbachir, N., Kamel, S., Hashim, F. A., Yu, J., Zeinoddini-Meymand, H., & Sabbeh, S. F. (2023). Optimizing the hybrid PVDG and DSTATCOM integration in electrical distribution systems based on a modified homonuclear molecules optimization algorithm. IET Renewable Power Generation, 17(12), 3075–3096. DOI: 10.1049/rpg2.12826
- Abdollahzadeh, B., Gharehchopogh, F. S., Khodadadi, N., & Mirjalili, S. (2022). Mountain gazelle optimizer: a new nature-inspired metaheuristic algorithm for global optimization problems. Advances in Engineering Software, 174, 103282. DOI: 10.1016/j.advengsoft.2022.103282
- Abdelsattar, M., Mesalam, A., Fawzi, A., & Hamdan, I. (2024). Mountain gazelle optimizer for standalone hybrid power system design incorporating a type of incentive-based strategies. Neural Computing and Applications, 36(12), 6839–6853. DOI: 10.1007/s00521-024-09433-3
- Mohammadzadeh, A., & Mirjalili, S. (2024). Eel and grouper optimizer: a nature-inspired optimization algorithm. Cluster Computing, 1–42. DOI: 10.1007/s10586-024-04545-w
- Kyrou, G., Charilogis, V., & Tsoulos, I. G. (2024). Refining the Eel and Grouper Optimizer with Intelligent Modifications for Global Optimization. Computation, 12(10). DOI: 10.3390/computation12100205
- Aman, M. M., Jasmon, G. B., Bakar, A. H. A., & Mokhlis, H. (2014). 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, 66, 202–215. DOI: 10.1016/j.energy.2013.12.037