[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
Main Menu
Home::
Journal Information::
Articles archive::
For Authors::
For Reviewers::
Registration::
Contact us::
Site Facilities::
::
Social Network Membership
Linkedin
Researchgate
..
Indexing Databases
..
DOI
کلیک کنید
..
ِDOR
..
Search in website

Advanced Search
..
Receive site information
Enter your Email in the following box to receive the site news and information.
..
:: Volume 10, Issue 3 (10-2021) ::
ieijqp 2021, 10(3): 1-13 Back to browse issues page
Optimal location and operation planning of charging and discharging stations of electric vehicles using metaheuristic algorithms
Monireh Ahmadi1 , Seyed hossein Hosseini * 2, Murtaza Farsadi3
1- Department of Electrical Engineering, Urmia Branch, Islamic Azad University, Urmia, Iran
2- The Engineering Faculty, Near East University, 99138Nicosia, North Cyprus, Mersin 10, Turkey
3- Istanbul Aydin University ,Engineering Faculty , Department of Electrical and Electronics Engineerin Istanbul, Turkey
Abstract:   (2176 Views)
Charging stations are one of the most important pieces of equipment for electric vehicles (EV). One of the most important challenges of charging stations is their optimal location, which practically puts the operation of the system components in the maximum area. Distribution networks are the final link in the electricity supply chain for consumers. Therefore, the economic and technical efficiency of these networks guarantees a stable and secure future in the electricity industry. In this regard, it is very important to study the role of EVstations. This paper investigates, the optimal location of charging and discharging stations and the optimal operation planning of Evs in a distribution network. The effective factors in choosing the location and the optimal charging and discharging rate in the stations are a combination of technical and economic issues. Regarding technical issues, the minimization of losses, the minimization of voltage drop in feeders and the uniformity of the network load curve were considered. In the economic field, the stations were located and the charging and discharging rates were determined in such a way that the charge and discharge costs in the stations and the total cost paid for the purchase of power were minimized as much as possible. In order To manage the load on the consumer side and to unify the load curve, the price-based demand response program was considered and implemented in the simulations.To find the optimal working point, genetic metaheuristic algorithms, genetic combination-particle swarm and genetic combination-colonial competition were used. All simulations were performed in MATLAB software To evaluate the proposed methods, validation was performed in each part on the IEEE standard testing system with a bus number of 69.
Keywords: Optimal placement, Electric Vehicles, Charging Stations, Load Response Program, Metaheuristic Algorithms
Full-Text [PDF 836 kb]   (1144 Downloads)    
Type of Study: Research |
Received: 2020/10/19 | Accepted: 2021/07/10 | Published: 2021/09/11
References
1. [1] Canale, Laura, et al. "An Overview on Functional Integration of Hybrid Renewable Energy Systems in Multi-Energy Buildings." Energies 14.4 (2021): 1078. [DOI:10.3390/en14041078]
2. [2] M. Zand, M. A. Nasab, A. Hatami, M. Kargar and H. R. Chamorro, "Using Adaptive Fuzzy Logic for Intelligent Energy Management in Hybrid Vehicles," 2020 28th ICEE, , pp. 1-7, doi: 10.1109/ICEE50131.2020.9260941. [DOI:10.1109/ICEE50131.2020.9260941]
3. [3] Hamed Ahmadi-Nezamabad, et al.. "Multi-objective optimization based robust scheduling of electric vehicles aggregator." Sustainable Cities and Society vol. 47,101494, 2019. [DOI:10.1016/j.scs.2019.101494]
4. [4] Ahmadi, S., Arabani, H.P., Haghighi, D.A., Guerrero, J.M., Ashgevari, Y. and Akbarimajd, A., "Optimal use of vehicle-to-grid technology to modify the load profile of the distribution system", Journal of Energy Storage, Vol. 31, p.101627,2020. [DOI:10.1016/j.est.2020.101627]
5. [5] Solanke, T.U., Ramachandaramurthy, V.K., Yong, J.Y., Pasupuleti, J., Kasinathan, P. and Rajagopalan, A., "A review of strategic charging-discharging control of grid-connected electric vehicles", Journal of Energy Storage, Vol. 28, p.101193, 2020. [DOI:10.1016/j.est.2020.101193]
6. [6] Nasri, Shohreh, et al, Maximum Power Point Tracking of Photovoltaic Renewable Energy System Using a New Method Based on Turbulent Flow of Water-based Optimization (TFWO) Under Partial Shading Conditions. 978-981-336-456-1
7. [7] Jannati, J. and Nazarpour, D., "Multi-objective scheduling of electric vehicles intelligent parking lot in the presence of hydrogen storage system under peak load management", Energy, Vol. 163, pp.338-350, 2018. [DOI:10.1016/j.energy.2018.08.098]
8. [8] Fathy, A. and Abdelaziz, A.Y., "Competition over resource optimization algorithm for optimal allocating and sizing parking lots in radial distribution network", Journal of Cleaner Production, p.121397, 2020. [DOI:10.1016/j.jclepro.2020.121397]
9. [9] Ghasemi M, et al. (2020). An Efficient Modified HPSO-TVAC-Based Dynamic Economic Dispatch of Generating Units, Electric Power Components and Systems doi.org/10.1080/15325008.2020.1731876
10. [10] Zand M, et. al "Robust Speed Control for Induction Motor Drives Using STSM Control",12th Annual power Electronic Drive Systems, & Technologies Conference (PEDSTC2021). IEEE Index [DOI:10.1109/PEDSTC52094.2021.9405912]
11. [11] Shamshirband, M., Salehi, J. and Gazijahani, F.S., " Look-ahead risk-averse power scheduling of heterogeneous electric vehicles aggregations enabling V2G and G2V systems based on information gap decision theory", Electric Power Systems Research, Vol. 173, pp.56-70,2019. [DOI:10.1016/j.epsr.2019.04.018]
12. [12] Rohani A, et al, "Three-phase amplitude adaptive notch filter control design of DSTATCOM under unbalanced/distorted utility voltage conditions," Journal of Intelligent & Fuzzy Systems, , 2020, 10.3233/JIFS-201667 [DOI:10.3233/JIFS-181521]
13. [13] Lilia Tightiz, Morteza Azimi Nasab, Hyosik Yang, Abdoljalil Addeh, An intelligent system based on optimized ANFIS and association rules for power transformer fault diagnosis, ISA Transactions, Volume 103, 2020, Pages 63-74,ISSN 0019-0578, https://doi.org/10.1016/j.isatra.2020.03.022 [DOI:10.1016/j.isatra.2020.03.022.]
14. [14] Zheng, Y., Niu, S., Shang, Y., Shao, Z. and Jian, L., "Integrating plug-in electric vehicles into power grids: A comprehensive review on power interaction mode, scheduling methodology and mathematical foundation", Renewable and Sustainable Energy Reviews, Vol. 112, pp.424-439, 2019. [DOI:10.1016/j.rser.2019.05.059]
15. [15] Mouli, G.C., Bauer, P. and Zeman, M., " System design for a solar powered electric vehicle charging station for workplaces", Applied Energy, Vol. 168, pp.434-443, 2016. [DOI:10.1016/j.apenergy.2016.01.110]
16. [16] Zand M, , et al "A Hybrid Scheme for Fault Locating in Transmission Lines Compensated by the Thyristor-Controlled Series Capacitors", IPAPS, 2021. IEEE Index [DOI:10.1109/IPAPS52181.2020.9375626]
17. [17] . Zand, M. A. Nasab, O. Neghabi, M. Khalili and A. Goli, "Fault locating transmission lines with thyristor-controlled series capacitors By fuzzy logic method," 2020 14th International Conference on Protection and Automation of Power Systems (IPAPS), Tehran, Iran, 2019, pp. 62-70, doi: 10.1109/IPAPS49326.2019.9069389. [DOI:10.1109/IPAPS49326.2019.9069389]
18. [18] Hafez, O. and Bhattacharya, K., "Optimal design of electric vehicle charging stations considering various energy resources", Renewable energy, Vol. 107, pp.576-589, 2017. [DOI:10.1016/j.renene.2017.01.066]
19. [19] Tabatabaee, S., Mortazavi, S.S. and Niknam, T., "Stochastic scheduling of local distribution systems considering high penetration of plug-in electric vehicles and renewable energy sources", Energy, Vol. 121, pp.480-490, 2017.. [DOI:10.1016/j.energy.2016.12.115]
20. [20] Jiang, X., Wang, J., Han, Y. and Zhao, Q., "Coordination dispatch of electric vehicles charging/discharging and renewable energy resources power in microgrid", Procedia Computer Science, Vol. 107, No. 4, pp.157-163, 2017. [DOI:10.1016/j.procs.2017.03.072]
21. [21] Rahmani-andebili, M., "Modeling nonlinear incentive-based and price-based demand response programs and implementing on real power markets", Electric Power Systems Research, Vol. 132, pp.115-124, 2016. [DOI:10.1016/j.epsr.2015.11.006]
22. [22] Moradi, M.H., Abedini, M., Tousi, S.R. and Hosseinian, S.M., "Optimal siting and sizing of renewable energy sources and charging stations simultaneously based on Differential Evolution algorithm", International Journal of Electrical Power & Energy Systems, Vol. 73, pp.1015-1024, 2015. [DOI:10.1016/j.ijepes.2015.06.029]
23. [23] Kühnbach, Matthias, Anke Bekk, and Anke Weidlich. "Prepared for regional self-supply? On the regional fit of electricity demand and supply in Germany." Energy Strategy Reviews 34 (2021): 100609. [DOI:10.1016/j.esr.2020.100609]
24. [24] Chondrogiannis, Stamatios, et al. "Power system flexibility: A methodological analytical framework based on unit commitment and economic dispatch modelling." Mathematical Modelling of Contemporary Electricity Markets. Academic Press, 2021. 127-156. [DOI:10.1016/B978-0-12-821838-9.00008-6]
25. [25] Basu, M. "Heat and power generation augmentation planning of isolated microgrid." Energy 223 (2021): 120062. [DOI:10.1016/j.energy.2021.120062]
26. [26] Alismail, F., M. A. Abdulgalil, and M. Khalid. "Optimal Coordinated Planning of Energy Storage and Tie-Lines to Boost Flexibility with High Wind Power Integration. Sustainability 2021, 13, 2526." (2021). [DOI:10.3390/su13052526]
27. [27] Parsa, Navid, Bahman Bahmani-Firouzi, and Taher Niknam. "A social-economic-technical framework for reinforcing the automated distribution systems considering optimal switching and plug-in hybrid electric vehicles." Energy 220 (2021): 119703. [DOI:10.1016/j.energy.2020.119703]
28. [28] Lugovoy, Oleg, et al. "Feasibility study of China's electric power sector transition to zero emissions by 2050." Energy Economics (2021): 105176. [DOI:10.1016/j.eneco.2021.105176]
29. [29] Alshaalan, Abdullah. "Basic Concepts of Electric Power System Planning: Contracting for Reliability and Cost Effectiveness." Innovative and Agile Contracting for Digital Transformation and Industry 4.0. IGI Global, 2021. 306-325. [DOI:10.4018/978-1-7998-4501-0.ch016]
30. [30] Canale, Laura, et al. "An Overview on Functional Integration of Hybrid Renewable Energy Systems in Multi-Energy Buildings." Energies 14.4 (2021): 1078. [DOI:10.3390/en14041078]
31. [31] Chondrogiannis, Stamatios, et al. "Power system flexibility: A methodological analytical framework based on unit commitment and economic dispatch modelling." Mathematical Modelling of Contemporary Electricity Markets. Academic Press, 2021. 127-156. [DOI:10.1016/B978-0-12-821838-9.00008-6]


XML   Persian Abstract   Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

ahmadi M, hosseini S H, farsadi M. Optimal location and operation planning of charging and discharging stations of electric vehicles using metaheuristic algorithms. ieijqp 2021; 10 (3) :1-13
URL: http://ieijqp.ir/article-1-780-en.html


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 10, Issue 3 (10-2021) Back to browse issues page
نشریه علمی- پژوهشی کیفیت و بهره وری صنعت برق ایران Iranian Electric Industry Journal of Quality and Productivity
Persian site map - English site map - Created in 0.06 seconds with 40 queries by YEKTAWEB 4645