Enhancement of Distribution System using Improved Real-Coded Genetic Algorithm

Tamer Mohamed Zayed Mohamed Ali, Sayed Hosny EL-Banna, Mahmoud Abbas El-Dabah, Mamdouh K. F. Ahmed

Abstract


Distributed generation (DG) implementation into power networks offers several technical and environmental advantages. These advantages include lessening power losses, improving voltage profiles, boosting power system reliability, and offering an easy determination to rapidly growing load needs. On the other hand, installing these DG units might have negative consequences if their distribution is not adequately sized. This research paper aims to allocate DGs optimally while improving the distribution network's voltage profile with decreased power losses. Several approaches have been developed to determine the optimal allocation of DGs in distribution networks.  Genetic Algorithm (GA) is one of the most used artificial, naturally inspired approaches. Recently an improved version of the GA was introduced that is called Improved Real Coaded Genetic Algorithm (IRGA) as a powerful optimization algorithm. The IRGA was utilized as a solution tool in this research. Two DG types were considered in this study, the first is DGs capable of injecting active power only while the second is DGs capable of injecting active and reactive power. The attained results show that the developed IRGA can successfully identify the optimum solutions by minimizing power loss and improving the voltage profile, outperforming other current literature approaches. Also, power losses and voltage profile enhancement have improved significantly as the number of DG units has increased.


Keywords


Distributed generation; Optimal allocation; Active Power loss; Voltage profile; Improved real coded genetic algorithm.

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References


S. Sahota, G. Shah, P. Ghosh, R. Kapoor, S. Sengupta, P. Singh, V. Vijay, A. Sahay, V. K. Vijay, I. S. Thakur, “Review of trends in biogas upgradation technologies and future perspectives”, Bioresour. Technol. Reports, vol. 1, pp. 79–88, Mar. 2018, doi: 10.1016/j.biteb.2018.01.002.

M. A. Darfoun and M. E. El-Hawary, “Multi-objective Optimization Approach for Optimal Distributed Generation Sizing and Placement”, Electr. Power Components Syst., vol. 43, no. 7, pp. 828–836, Apr. 2015, doi: 10.1080/15325008.2014.1002589.

K. H. Truong, P. Nallagownden, I. Elamvazuthi, and D. N. Vo, “A Quasi-Oppositional-Chaotic Symbiotic Organisms Search algorithm for optimal allocation of DG in radial distribution networks”, Appl. Soft Comput., vol. 88, p. 106067, Mar. 2020, doi: 10.1016/j.asoc.2020.106067.

K. Mahmoud, N. Yorino, and A. Ahmed, “Optimal Distributed Generation Allocation in Distribution Systems for Loss Minimization”, IEEE Trans. Power Syst., vol. 31, no. 2, pp. 960–969, Mar. 2016, doi: 10.1109/TPWRS.2015.2418333.

P. Mehta, P. Bhatt, and V. Pandya, “Optimal selection of distributed generating units and its placement for voltage stability enhancement and energy loss minimization”, Ain Shams Eng. J., vol. 9, no. 2, pp. 187–201, Jun. 2018, doi: 10.1016/j.asej.2015.10.009.

A. Ehsan and Q. Yang, “Optimal integration and planning of renewable distributed generation in the power distribution networks: A review of analytical techniques”, Appl. Energy, vol. 210, pp. 44–59, Jan. 2018, doi: 10.1016/j.apenergy.2017.10.106.

T. P. Nguyen, T. T. Tran, and D. N. Vo, “Improved stochastic fractal search algorithm with chaos for optimal determination of location, size, and quantity of distributed generators in distribution systems”, Neural Comput. Appl., vol. 31, no. 11, pp. 7707–7732, Nov. 2019, doi: 10.1007/s00521-018-3603-1.

A. Rezaee Jordehi, “Allocation of distributed generation units in electric power systems: A review”, Renew. Sustain. Energy Rev., vol. 56, pp. 893–905, Apr. 2016, doi: 10.1016/j.rser.2015.11.086.

M. Saric, J. Hivziefendic, and M. Tesanovic, “Optimal DG Allocation for Power Loss Reduction Considering Load and Generation Uncertainties”, in 2019 11th International Symposium on Advanced Topics in Electrical Engineering (ATEE), IEEE, Mar. 2019, pp. 1–6. doi: 10.1109/ATEE.2019.8724911.

N. Kanwar, N. Gupta, K. R. Niazi, A. Swarnkar, and R. C. Bansal, “Simultaneous allocation of distributed energy resource using improved particle swarm optimization”, Appl. Energy, vol. 185, pp. 1684–1693, Jan. 2017, doi: 10.1016/j.apenergy.2016.01.093.

A. A. Hassan, F. H. Fahmy, A. E.-S. A. Nafeh, and M. A. Abu-elmagd, “Hybrid genetic multi objective/fuzzy algorithm for optimal sizing and allocation of renewable DG systems”, Int. Trans. Electr. Energy Syst., vol. 26, no. 12, pp. 2588–2617, Dec. 2016, doi: 10.1002/etep.2223.

M. Vatani, D. Solati Alkaran, M. J. Sanjari, and G. B. Gharehpetian, “Multiple distributed generation units allocation in distribution network for loss reduction based on a combination of analytical and genetic algorithm methods”, IET Gener. Transm. Distrib., vol. 10, no. 1, pp. 66–72, Jan. 2016, doi: 10.1049/iet-gtd.2015.0041.

A. Bayat and A. Bagheri, “Optimal active and reactive power allocation in distribution networks using a novel heuristic approach”, Applied Energy, vol. 233–234. pp. 71–85, 2019. doi: 10.1016/j.apenergy.2018.10.030.

O. D. Montoya, W. Gil-González, and L. F. Grisales-Noreña, “An exact MINLP model for optimal location and sizing of DGs in distribution networks: A general algebraic modeling system approach”, Ain Shams Eng. J., vol. 11, no. 2, pp. 409–418, Jun. 2020, doi: 10.1016/j.asej.2019.08.011.

M. A. Mohamed, M.A.; El-Sehiemy, R.A.; El-Dabah, “Optimal operation of electrical distribution networks including distributed generation units using trader optimization algorithm”, In Proceedings of the CIRED 2021 Conference, online, 20–23 September, 2021.

A. Hussain, S. D. A. Shah, and S. M. Arif, “Heuristic optimisation?based sizing and siting of DGs for enhancing resiliency of autonomous microgrid networks”, IET Smart Grid, vol. 2, no. 2, pp. 269–282, Jun. 2019, doi: 10.1049/iet-stg.2018.0209.

S. R. Gampa, K. Jasthi, P. Goli, D. Das, and R. C. Bansal, “Grasshopper optimization algorithm based two stage fuzzy multiobjective approach for optimum sizing and placement of distributed generations, shunt capacitors and electric vehicle charging stations”, J. Energy Storage, vol. 27, p. 101117, Feb. 2020, doi: 10.1016/j.est.2019.101117.

O. Khoubseresht and H. Shayanfar, “The role of demand response in optimal sizing and siting of distribution energy resources in distribution network with time-varying load: An analytical approach”, Electr. Power Syst. Res., vol. 180, p. 106100, Mar. 2020, doi: 10.1016/j.epsr.2019.106100.

M. Dehghani, Z. Montazeri, and O. P. Malik, “Optimal Sizing and Placement of Capacitor Banks and Distributed Generation in Distribution Systems Using Spring Search Algorithm”, International Journal of Emerging Electric Power Systems, vol. 21, no. 1. 2020. doi: 10.1515/ijeeps-2019-0217.

G. BATTAPOTHULA, C. YAMMANI, and S. MAHESWARAPU, “Multi-objective simultaneous optimal planning of electrical vehicle fast charging stations and DGs in distribution system”, J. Mod. Power Syst. Clean Energy, vol. 7, no. 4, pp. 923–934, Jul. 2019, doi: 10.1007/s40565-018-0493-2.

A. Selim, S. Kamel, and F. Jurado, “Efficient optimization technique for multiple DG allocation in distribution networks”, Appl. Soft Comput., vol. 86, p. 105938, Jan. 2020, doi: 10.1016/j.asoc.2019.105938.

H. Su, “Siting and sizing of distributed generators based on improved simulated annealing particle swarm optimization”, Environ. Sci. Pollut. Res., vol. 26, no. 18, pp. 17927–17938, Jun. 2019, doi: 10.1007/s11356-017-0823-3.

D. H. Wolpert and W. G. Macready, “No free lunch theorems for optimization”, IEEE Trans. Evol. Comput., vol. 1, no. 1, pp. 67–82, 1997, doi: 10.1109/4235.585893.

S. Vadhera and S. Mahajan, “Optimal allocation of dispersed generation unit in a network system”, in 2016 International Conference on Microelectronics, Computing and Communications (MicroCom), IEEE, Jan. 2016, pp. 1–5. doi: 10.1109/MicroCom.2016.7522519.

A. Ahmed, M. F. N. Khan, I. Khan, H. Alquhayz, M. A. Khan, and A. T. Kiani, “A Novel Framework to Determine the Impact of Time Varying Load Models on Wind DG Planning”, IEEE Access, vol. 9. pp. 11342–11357, 2021. doi: 10.1109/ACCESS.2021.3050307.

Z. Ullah, M. R. Elkadeem, S. Wang, S. W. Sharshir, and M. Azam, “Planning optimization and stochastic analysis of RE-DGs for techno-economic benefit maximization in distribution networks”, Internet of Things, vol. 11, p. 100210, Sep. 2020, doi: 10.1016/j.iot.2020.100210.

T. M. C. Le, X. C. Le, N. N. P. Huynh, A. T. Doan, T. V. Dinh, and M. Q. Duong, “Optimal power flow solutions to power systems with wind energy using a highly effective meta-heuristic algorithm”, Int. J. Renew. Energy Dev., vol. 12, no. 3, pp. 467–477, May 2023, doi: 10.14710/ijred.2023.51375.

H. Manafi, N. Ghadimi, M. Ojaroudi, and P. Farhadi, “Optimal Placement of Distributed Generations in Radial Distribution Systems Using Various PSO and DE Algorithms”, Electronics and Electrical Engineering, vol. 19, no. 10. 2013. doi: 10.5755/j01.eee.19.10.1941.

B. Zhao and Y. J. Cao, “An improved particle swarm optimization algorithm for power system unit commitment”, Power System Technology, vol. 28, no. 21. pp. 6–10, 2004.

K. Balu and V. Mukherjee, “Optimal siting and sizing of distributed generation in radial distribution system using a novel student psychology-based optimization algorithm”, Neural Comput. Appl., vol. 33, no. 22, pp. 15639–15667, Nov. 2021, doi: 10.1007/s00521-021-06185-2.

M. H. Ali, S. Kamel, M. H. Hassan, M. Tostado-Véliz, and H. M. Zawbaa, “An improved wild horse optimization algorithm for reliability based optimal DG planning of radial distribution networks”, Energy Reports, vol. 8, pp. 582–604, Nov. 2022, doi: 10.1016/j.egyr.2021.12.023.

M. A. El-Dabah, R. A. El-Sehiemy, and A. Abdelbaset, “An improved RCGA for Parameter extraction of three-diode PV model”, in 2022 23rd International Middle East Power Systems Conference (MEPCON), IEEE, Dec. 2022, pp. 1–6. doi: 10.1109/MEPCON55441.2022.10021732.

S. A. ChithraDevi, L. Lakshminarasimman, and R. Balamurugan, “Stud Krill herd Algorithm for multiple DG placement and sizing in a radial distribution system”, Eng. Sci. Technol. an Int. J., vol. 20, no. 2, pp. 748–759, Apr. 2017, doi: 10.1016/j.jestch.2016.11.009.

A. Ali, M. U. Keerio, and J. A. Laghari, “Optimal Site and Size of Distributed Generation Allocation in Radial Distribution Network Using Multi-objective Optimization”, J. Mod. Power Syst. Clean Energy, vol. 9, no. 2, pp. 404–415, 2021, doi: 10.35833/MPCE.2019.000055.

S. K. Injeti and N. Prema Kumar, “A novel approach to identify optimal access point and capacity of multiple DGs in a small, medium and large scale radial distribution systems”, Int. J. Electr. Power Energy Syst., vol. 45, no. 1, pp. 142–151, Feb. 2013, doi: 10.1016/j.ijepes.2012.08.043.

C. Venkatesan, R. Kannadasan, M. H. Alsharif, M.-K. Kim, and J. Nebhen, “A Novel Multiobjective Hybrid Technique for Siting and Sizing of Distributed Generation and Capacitor Banks in Radial Distribution Systems”, Sustainability, vol. 13, no. 6, p. 3308, Mar. 2021, doi: 10.3390/su13063308.




DOI (PDF): https://doi.org/10.20508/ijrer.v15i1.14760.g9032

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