References
- A. Azizivahed, H. Narimani, E. Naderi, M. Fathi and M. R. Narimani, “A hybrid evolutionary algorithm for secure multi-objective distribution feeder reconfiguration,” Energy, vol. 138, pp. 355–373, 2017. DOI: https://doi.org/10.1016/j.energy.2017.07.102.
- A. Lotfipour and H. Afrakhte, “A discrete Teaching–Learning-Based Optimization algorithm to solve distribution system reconfiguration in presence of distributed generation,” Int. J. Elect. Power Energy Syst., vol. 82, pp. 264–273, 2016. DOI: https://doi.org/10.1016/j.ijepes.2016.03.009.
- J. Siahbalaee, N. Rezanejad and G. B. Gharehpetian, “Reconfiguration and DG Sizing and Placement Using Improved Shuffled Frog Leaping Algorithm,” Electric Power Components Syst., vol. 47, no. 16-17, pp. 1475–1484, 2019. DOI: https://doi.org/10.1080/15325008.2019.1689449.
- 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. DOI: https://doi.org/10.1016/j.egyr.2015.03.002.
- K. S. Sambaiah and T. Jayabarathi, “Optimal reconfiguration and renewable distributed generation allocation in electric distribution systems,” Int. J. Ambient Energy, vol. 42, no. 9, pp. 1008–1014, 2021. DOI: https://doi.org/10.1080/01430750.2019.1583604.
- A. Landeros, S. Koziel and M. F. Abdel-Fattah, “Distribution network reconfiguration using feasibility-preserving evolutionary optimization,” J. Mod. Power Syst. Clean Energy, vol. 7, no. 3, pp. 589–598, 2019. DOI: https://doi.org/10.1007/s40565-018-0480-7.
- M. Esmaeili, M. Sedighizadeh and M. Esmaili, “Multi-objective optimal reconfiguration and DG (Distributed Generation) power allocation in distribution networks using Big Bang-Big Crunch algorithm considering load uncertainty,” Energy, vol. 103, pp. 86–99, 2016. DOI: https://doi.org/10.1016/j.energy.2016.02.152.
- A. Bayat, A. Bagheri and R. Noroozian, “Optimal siting and sizing of distributed generation accompanied by reconfiguration of distribution networks for maximum loss reduction by using a new UVDA-based heuristic method,” Int. J. Elect. Power Energy Syst., vol. 77, pp. 360–371, 2016. DOI: https://doi.org/10.1016/j.ijepes.2015.11.039.
- E. Mahboubi-Moghaddam, M. R. Narimani, M. H. Khooban, A. Azizivahed and M. Javid Sharifi, “Multi-objective distribution feeder reconfiguration to improve transient stability, and minimize power loss and operation cost using an enhanced evolutionary algorithm at the presence of distributed generations,” Int. J. Elect. Power Energy Syst., vol. 76, pp. 35–43, 2016. DOI: https://doi.org/10.1016/j.ijepes.2015.09.007.
- T. Niknam, “An efficient hybrid evolutionary algorithm based on PSO and HBMO algorithms for multi-objective distribution feeder reconfiguration,” Energy Conversion Manage., vol. 50, no. 8, pp. 2074–2082, 2009. DOI: https://doi.org/10.1016/j.enconman.2009.03.029.
- T. Niknam, “An efficient hybrid evolutionary algorithm based on PSO and ACO for distribution feeder reconfiguration,” Euro. Trans. Electr. Power, vol. 20, no. 5, pp. n/a–590, 2009. DOI: https://doi.org/10.1002/etep.339.
- M. R. Narimani, A. A. Vahed, R. Azizipanah-Abarghooee and M. Javidsharifi, “Enhanced gravitational search algorithm for multi-objective distribution feeder reconfiguration considering reliability, loss and operational cost,” IET Generat. Trans. Distribut., vol. 8, no. 1, pp. 55–69, 2014. DOI: https://doi.org/10.1049/iet-gtd.2013.0117.
- F. Alonso, D. Oliveira and A. Z. de Souza, “Artificial immune systems optimization approach for multiobjective distribution system reconfiguration,” IEEE Trans. Power Syst., vol. 30, no. 2, pp. 840–847, 2015. DOI: https://doi.org/10.1109/TPWRS.2014.2330628.
- M. Abdelaziz, “Distribution network reconfiguration using a genetic algorithm with varying population size,” Electric Power Syst. Res., vol. 142, pp. 9–11, 2017. DOI: https://doi.org/10.1016/j.epsr.2016.08.026.
- S. Das, D. Das and A. Patra, “Reconfiguration of distribution networks with optimal placement of distributed generations in the presence of remote voltage controlled bus,” Renew. Sustain. Energy Rev., vol. 73, pp. 772–781, 2017. DOI: https://doi.org/10.1016/j.rser.2017.01.055.
- M. Sedighizadeh, M. Dakhem, M. Sarvi and H. H. Kordkheili, “Optimal reconfiguration and capacitor placement for power loss reduction of distribution system using improved binary particle swarm optimization,” Int J Energy Environ Eng., vol. 5, no. 1, pp. 3, 2014. DOI: https://doi.org/10.1186/2251-6832-5-3.
- M. R. Babu, C. V. Kumar and S. Anitha, “Simultaneous Reconfiguration and Optimal Capacitor Placement Using Adaptive Whale Optimization Algorithm for Radial Distribution System,” J. Electr. Eng. Technol., vol. 16, no. 1, pp. 181–190, 2021. DOI: https://doi.org/10.1007/s42835-020-00593-5.
- C.-T. Su and C.-S. Lee, “Feeder reconfiguration and capacitor setting for loss reduction of distribution systems,” Electric Power Syst. Res., vol. 58, no. 2, pp. 97–102, 2001. DOI: https://doi.org/10.1016/S0378-7796(01)00124-9.
- A. N. Hussain, W. K. Shakir Al-Jubori and H. F. Kadom, “Hybrid design of optimal capacitor placement and reconfiguration for performance improvement in a radial distribution system,” J. Eng., vol. 2019, pp. 1–15, 2019. vol. DOI: https://doi.org/10.1155/2019/1696347.
- M. A. Guimarães and C. A. Castro, “An efficient method for distribution systems reconfiguration and capacitor placement using a Chu-Beasley based genetic algorithm,” in 2011 IEEE Trondheim PowerTech, 2011., pp. 1–7. IEEE.
- R. E. Ramli, M. Awad and R. A. Jabr, “Ordinal optimization for optimal Capacitor Placement and network reconfiguration in radial distribution networks,” in 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2012., pp. 1712–1717. IEEE.
- M. Sedighizadeh and R. Bakhtiary, “Optimal multi-objective reconfiguration and capacitor placement of distribution systems with the Hybrid Big Bang–Big Crunch algorithm in the fuzzy framework,” Ain Shams Eng. J., vol. 7, no. 1, pp. 113–129, 2016. DOI: https://doi.org/10.1016/j.asej.2015.11.018.
- H. Lotfi, R. Ghazi and M. Bagher Naghibi-Sistani, “Multi-objective dynamic distribution feeder reconfiguration along with capacitor allocation using a new hybrid evolutionary algorithm,” Energy Syst., vol. 11, no. 3, pp. 729–731, 2020. DOI: https://doi.org/10.1007/s12667-019-00333-3.
- H. Lotfi, A. Azizivahed, A. A. Shojaei, S. Seyedi and M. F. B. Othman, “Multi-objective Distribution Feeder Reconfiguration Along with Optimal Sizing of Capacitors and Distributed Generators Regarding Network Voltage Security,” Electric Power Components Syst., vol. 49, no. 6-7, pp. 652–657, 2021. DOI: https://doi.org/10.1080/15325008.2021.2011486.
- H. Lotfi, “Optimal sizing of distributed generation units and shunt capacitors in the distribution system considering uncertainty resources by the modified evolutionary algorithm,” J. Ambient Intell. Human Comput., vol. 2021, pp. 1–20, 2021. DOI: https://doi.org/10.1007/s12652-021-03194-w.
- H. Lotfi, “Multi‐objective energy management approach in distribution grid integrated with energy storage units considering the demand response program,” Int. J. Energy Res., vol. 44, no. 13, pp. 10662–10681, 2020. DOI: https://doi.org/10.1002/er.5709.
- H. Lotfi and R. Ghazi, “Optimal participation of demand response aggregators in reconfigurable distribution system considering photovoltaic and storage units,” J. Ambient. Intell. Human Comput., vol. 12, no. 2, pp. 2223–2233, 2021. DOI: https://doi.org/10.1007/s12652-020-02322-2.
- R. Akbari, R. Hedayatzadeh, K. Ziarati and B. Hassanizadeh, “A multi-objective artificial bee colony algorithm,” Swarm Evol. Comput., vol. 2, pp. 39–52, 2012. DOI: https://doi.org/10.1016/j.swevo.2011.08.001.
- H. Lotfi and R. Ghazi, “An optimal co-operation of distributed generators and capacitor banks in dynamic distribution feeder reconfiguration,” in 2019 24th Electrical Power Distribution Conference (EPDC), 2019. pp. 60–65: IEEE. DOI: https://doi.org/10.1109/EPDC.2019.8903872.
- H. Lotfi, R. Ghazi and M. B. N. Sistani, “Providing an optimal energy management strategy in distribution network considering distributed generators and energy storage units,” in 2019 International Power System Conference (PSC), 2019. pp. 293–299: IEEE. DOI: https://doi.org/10.1109/PSC49016.2019.9081459.
- A. Saffar, R. Hooshmand and A. Khodabakhshian, “A new fuzzy optimal reconfiguration of distribution systems for loss reduction and load balancing using ant colony search-based algorithm,” Appl. Soft Comput., vol. 11, no. 5, pp. 4021–4028, 2011. DOI: https://doi.org/10.1016/j.asoc.2011.03.003.
- J. Moshtagh and S. Ghasemi, “Optimal distribution system reconfiguration using non-dominated sorting genetic algorithm (NSGA-II),” J. Operat. Auto. Power Eng., vol. 1, no. 1, pp. 12–21, 2007.
- J.-P. Chiou, C.-F. Chang and C.-T. Su, “Variable scaling hybrid differential evolution for solving network reconfiguration of distribution systems,” IEEE Trans. Power Syst., vol. 20, no. 2, pp. 668–674, 2005. DOI: https://doi.org/10.1109/TPWRS.2005.846096.
- A. Ahuja, S. Das and A. Pahwa, “An AIS-ACO hybrid approach for multi-objective distribution system reconfiguration,” IEEE Trans. Power Syst., vol. 22, no. 3, pp. 1101–1111, 2007. DOI: https://doi.org/10.1109/TPWRS.2007.901286.