Enhancing the Voltage Profile and Net Profit of Reconfigured Distribution Networks with the Optimal Integration of EVCS and Capacitor Banks with Chaotic HBA
Keywords:
Capacitor banks, Chaotic HBA, Electric Vehicle Charging Stations, net profit maximization, Network reconfiguration (NR), Radial distribution system (RDS)Abstract
Nowadays, plug-in electric vehicles (PEVs) are increasing very fast because people are worried about pollution caused by petrol and diesel vehicles. As the number of electric vehicles (EVs) is growing quickly, there is a need to provide proper and efficient charging stations. But installing many charging stations creates some problems in the distribution system, such as voltage becoming unstable and increase in power losses. In this paper, a complete optimization method is proposed to improve the voltage level and increase overall profit in radial distribution networks (RDNs). This is done by placing electric vehicle charging stations (EVCS), capacitor banks, and by changing the network connections (network reconfiguration) together at the same time. In this work, a Chaotic Honey Badger Algorithm (CHBA) is used to solve the complex optimization problem which has nonlinear and mixed-integer variables. By adding chaotic mapping, the search ability of the algorithm improves and it helps to avoid getting stuck at a wrong early solution. The objective function considers both technical and economic factors. It aims to reduce power loss, improve voltage condition, decrease installation and operating cost, and increase the benefit by reducing energy losses. The proposed method is tested on the IEEE 33-bus test system under different conditions. The results show good improvement in voltage level, reduction in power losses, and increase in net profit when compared with other existing methods like PSO, GWO, and AGWOPSO. The CHBA method behaves steadily and yields consistent results under various test situations, according to the statistical analysis. The results obtained indicate that the recommended strategy is appropriate for practical implementation in present-day power distribution systems, especially in networks where electric vehicles (EVs) are highly prevalent.
Downloads
References
İnci, Mustafa & Çelik, Özgür & Lashab, Abderezak & Bayindir, Kamil & Vasquez, Juan & Guerrero, Josep. Power System Integration of Electric Vehicles: A Review on Impacts and Contributions to the Smart Grid. Applied Sciences. vol.14, no.6, pp.2246,2024, doi:10.3390/app14062246.
Pawelek, R., K. PAWEL and I. WASIAK. Experimental analysis of DC electric vehicles charging station operation and its impact on the supplying grid. In: IEEE International Electric Vehicle Conference (IEVC). Florence: IEEE, 2014. pp. 1–5. ISBN 978-1-4799-6075-0. doi: 10.1109/IEVC.2014.7056152
M. Z. Zeb et al., "Optimal Placement of Electric Vehicle Charging Stations in the Active Distribution Network," in IEEE Access, vol. 8, pp. 68124-68134, 2020, doi:10.1109/ACCESS.2020.2984127.
Golla, N.K., Sudabattula, S.K., Suresh, V. (2022). Optimal placement of electric vehicle charging station in distribution system using meta-heuristic techniques. Mathematical Modelling of Engineering Problems, Vol. 9, No. 1, pp. 60-66, doi:10.18280/mmep.090108
Ahmad, Fareed & Iqbal, Atif & Ashraf, Imtiaz & Marzband, Mousa & Khan, Irfan. (2022). Placement of electric vehicle fast-charging stations in distribution network considering power loss, land cost, and electric vehicle population. Energy Sources, Part A: Recovery, Utilization and Environmental Effects. vol.44, no.1, pp.1693-1709, doi:10.1080/15567036.2022.2055233.
Salau, Ayodeji & Gebru, Yalew & Aeggegn, Dessalegn. (2020). Optimal network reconfiguration for power loss minimization and voltage profile enhancement in distribution systems. Heliyon. vol.6, no.6, pp.e04233, doi: 10.1016/j.heliyon.2020.e04233.
Salkuti, Surender Reddy & Battu, Neelakanteshwar. (2021). An effective network reconfiguration approach of radial distribution system for loss minimization and voltage profile improvement. Bulletin of Electrical Engineering and Informatics. vol.10, no.4, pp.1819-1827, doi:10.11591/eei.v10i4.2867.
M. Mahdavi, H. H. Alhelou, N. D. Hatziargyriou and A. Al-Hinai, "An Efficient Mathematical Model for Distribution System Reconfiguration Using AMPL," in IEEE Access, vol. 9, pp. 79961-79993, 2021, doi: 10.1109/ACCESS.2021.3083688.
Merzoug, Yahiaoui & Abdelkrim, Bouanane & Boumediene, Larbi. (2020). Distribution network reconfiguration for loss reduction using PSO method. International Journal of Electrical and Computer Engineering (IJECE). vol.10, no.5, pp.5009-5015, doi: 10.11591/ijece.v10i5.pp5009-5015.
Ramesh Babu, Muthu & Kumar, C. & Anitha, S.. (2020). Simultaneous Reconfiguration and Optimal Capacitor Placement Using Adaptive Whale Optimization Algorithm for Radial Distribution System. Journal of Electrical Engineering & Technology. vol.16, no.3, pp.181-190, doi:10.1007/s42835-020-00593-5.
Lotfi, H. (2022). Multi-Objective Network Reconfiguration and Allocation of Capacitor Units in Radial Distribution System Using an Enhanced Artificial Bee Colony Optimization. Electric Power Components and Systems, vol.49, no.9, pp.1130–1142, doi:10.1080/15325008.2022.2049661.
Rajesh, P. & Shajin, Francis. (2021). Optimal allocation of EV charging spots and capacitors in distribution network improving voltage and power loss by Quantum-Behaved and Gaussian Mutational Dragonfly Algorithm (QGDA). Electric Power Systems Research. vol.194, no.1, pp.107049, doi:10.1016/j.epsr.2021.107049.
J. Tabatabaei, M. S. Moghaddam and J. M. Baigi, "Retracted: Rearrangement of Electrical Distribution Networks With Optimal Coordination of Grid-Connected Hybrid Electric Vehicles and Wind Power Generation Sources," in IEEE Access, vol. 8, pp. 219513-219524, 2020, doi:10.1109/ACCESS.2020.3042763.
Mejia, M. & Macedo, Leonardo H. & Muñoz-Delgado, Gregorio & Contreras, J. & Padilha-Feltrin, Antonio. (2023). Active distribution system planning considering non-utility-owned electric vehicle charging stations and network reconfiguration. Sustainable Energy, Grids and Networks. vol.35, no.1, pp.101101. doi:10.1016/j.segan.2023.101101.
Kothona, Despoina & Bouhouras, Aggelos. (2022). A Two-Stage EV Charging Planning and Network Reconfiguration Methodology towards Power Loss Minimization in Low and Medium Voltage Distribution Networks. Energies. vol.15, no.10, pp.3808, doi:10.3390/en15103808.
Amin, Adil & Tareen, Wajahat & Usman, Muhammad & Ali, Kamran & Horan, B. & Mahmood, Anzar & Mekhilef, Saad. (2020). An Integrated Approach to Optimal Charging Scheduling of Electric Vehicles Integrated with Improved Medium-Voltage Network Reconfiguration for Power Loss Minimization. Sustainability. vol.12, pp.9211, doi:10.3390/su12219211.
Karimianfard, Hossein & Haghighat, Hossein. (2019). An initial-point strategy for optimizing distribution system reconfiguration. Electric Power Systems Research. vol.176, no.3, pp.105943, doi:10.1016/j.epsr.2019.105943.
Tahir, Muhammad Junaid & Rasheed, Muhammad B. & Rahmat, Mohd. (2022). Optimal Placement of Capacitors in Radial Distribution Grids via Enhanced Modified Particle Swarm Optimization. Energies. vol.15, no.7, pp.2452, doi:10.3390/en15072452.
Adeyemo, Ismail & AKINROGUNDE, Oluwadare & Salimon, Sunday & Adebiyi, Oluwaseyi. (2022). Adaptive particle swarm optimization approach to simultaneous reconfiguration and shunt capacitor allocation in radial distribution network. Global Journal of Engineering and Technology Advances. vol.12, no.3, pp.077-094, doi:10.30574/gjeta.2022.12.3.0162.
Oonsivilai, Anant & Boribun, Banyat & Pao-la-or, Padej. (2023). Integration of Distributed Generation and Plug-in Electric Vehicles on Power Distribution System by Using Queuing Theory. Energies. vol.16, no.7, pp.3146, doi:10.3390/en16073146.
Goli, P. & Gampa, Srinivasa & Manoj Kumar, Nallapaneni & Jasthi, Kiran & Parimi, Alivelu & Das, D. & Bansal, Ramesh & Siano, Pierluigi & Guerrero, Josep. (2023). Strategic planning of distribution network integrated with EV charging stations using fuzzy pareto optimality for performance improvement and grid-side emission reduction benefits. Sustainable Energy Grids and Networks. vol.36, pp. 101199, doi:10.1016/j.segan.2023.101199.
Thangaraj, Yuvaraj & Suresh, Thirukoilur & Christy, Arokiasamy & Thanikanti, Sudhakar Babu & Nastasi, Benedetto. (2023). Modelling and Allocation of Hydrogen-Fuel-Cell-Based Distributed Generation to Mitigate Electric Vehicle Charging Station Impact and Reliability Analysis on Electrical Distribution Systems. Energies. vol.16, no.19, pp.6869. doi:10.3390/en16196869.
Ferraz, Rafael & Ferraz, Renato & Rueda-Medina, Augusto & Fardin, Jussara. (2023). Multi-objective approach for optimized planning of electric vehicle charging stations and distributed energy resources. Electrical Engineering. vol.105, no.6, pp.1-13, doi:10.1007/s00202-023-01942-z.
M. E. Baran and F. F. Wu, "Optimal capacitor placement on radial distribution systems," in IEEE Transactions on Power Delivery, vol. 4, no. 1, pp. 725-734, Jan. 1989, doi: 10.1109/61.19265.
R. A. Jabr, "Radial distribution load flow using conic programming," in IEEE Transactions on Power Systems, vol. 21, no. 3, pp. 1458-1459, Aug. 2006, doi: 10.1109/TPWRS.2006.879234.
Shareef, Hussain & Islam, Md Mainul & Mohamed, Azah. A review of the stage-of-the-art charging technologies, placement methodologies, and impacts of electric vehicles. Renewable and Sustainable Energy Reviews. vol.64, pp.403-420, 2016, doi:10.1016/j.rser.2016.06.033.
Deilami, Sara & Masoum, Amir & Moses, Paul & Masoum, Mohammad. Real-Time Coordination of Plug-In Electric Vehicle Charging in Smart Grids to Minimize Power Losses and Improve Voltage Profile. Smart Grid, IEEE Transactions on smart Grid,vol.2, no.3, pp.456-467, 2011, doi: 10.1109/TSG.2011.2159816.
A. A. Zaki Diab, V. N. Tulsky and M. A. Tolba, "Optimal shunt capacitors sittings and sizing in radial distribution systems using a novel hybrid optimization algorithm," 2016 Eighteenth International Middle East Power Systems Conference (MEPCON), Cairo, Egypt, 2016, pp. 445-452, doi: 10.1109/MEPCON.2016.7836929.
Prakash, D.B. & Lakshminarayana, C. Optimal siting of capacitors in radial distribution network using Whale Optimization Algorithm. Alexandria Engineering Journal. vol.56, no.4, pp.499-509, 2016, doi:10.1016/j.aej.2016.10.002.
F. A. Hashim, E. H. Houssein, K. Hussain, M. S. Mabrouk, and W. Al-Atabany, “Honey badger algorithm: new metaheuristic algorithm for solving optimization problems,” Mathematics and Computers in Simulation, vol. 192, pp. 84–110, 2022, doi: 10.1016/j.matcom.2021.08.013.
M. A. Elseify, S. Kamel, H. Abdel-Mawgoud, and E. E. Elattar, “A novel approach based on honey badger algorithm for optimal allocation of multiple DG and capacitor in radial distribution networks considering power loss sensitivity,” Mathematics, vol. 10, no. 12, pp. 2081, Jun. 2022, doi: 10.3390/math10122081.
G. Hu, J. Zhong, and G. Wei, “SaCHBA_PDN: modified honey badger algorithm with multi-strategy for UAV path planning,” Expert Systems with Applications, vol. 223, pp. 119941, 2023, doi: 10.1016/j.eswa.2023.119941.
Song, Bingbing & Ding, Qun. (2014). Comparisons of Typical Discrete Logistic Map and Henon Map. d0i: 10.1007/978-3-319-07776-5_28.
Reddy, S. S. 2016. Determination of Optimal Location and Size of Static VAR Compensator in a Hybrid Wind and Solar Power System. Int. J. Appl. Eng. Res vol.11, no.23, pp.11494–11500.
Bilal, M., & Rizwan, M. (2021). Integration of electric vehicle charging stations and capacitors in distribution systems with vehicle-to-grid facility. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, vol.47, no.1, pp.7700–7729, doi:10.1080/15567036.2021.1923870.
