Comparative analysis of unidirectional and bidirectional electric vehicle charging stations (EVCS) optimal configuration in an IEEE 37-bus feeder system using Genetic Algorithm
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Dec 11, 2023
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Abstract
Various power system problems and challenges may arise in the future due to the large scale of deployment of electric vehicles (EVs). Hence, the proper placement of EV charging stations (EVCS) effectively mitigates the impact of high EV loads connected to the grid. The research intends to explore and analyze differences between the regulation effectiveness of unidirectional and bidirectional charging technologies by utilizing different comparison evaluation indices. Moreover, considering their penetration level, this study tackles the impact analysis of EV and EVCS integration through time. Specifically, this paper aims to identify the optimal EVCS sites in an IEEE 37-bus test feeder system to minimize power loss brought by EV integration. Through MATLAB R2022b simulation and OpenDSS power flow analysis, the EVCS are optimally located near the supply bus. The findings show a direct relationship between the EV penetration level and system power loss. Due to the EV technology growth, there is an observed voltage profile degradation of up to 1.7094 p.u. The paper also highlights that although EV bidirectional charging technology (BCT) might reduce the load on the grid in the next few years of low penetration compared to unidirectional charging technology (UCT), it will give no significant difference due to the rapid increase of load connected during its high EV penetration.
How to Cite
Balmeo AA, Aguirre, Jr. RA, Castillo MDG, Maguindayao EJH, Manzano JPP. 2023. Comparative analysis of unidirectional and bidirectional electric vehicle charging stations (EVCS) optimal configuration in an IEEE 37-bus feeder system using Genetic Algorithm. The Palawan Scientist. 15(2):41–54. https://doi.org/10.69721/TPS.J.2023.15.2.05.
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Keywords
electric vehicles, MATLAB, optimization, power loss reduction, voltage profile improvement
References
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Bayani R, Soofi AF, Waseem M and Manshadi SD. 2022. Impact of transportation electrification on the electricity grid—a review. Vehicles, 4(4): 1042-1079. https://doi.org/10.3390/vehicles4040056
Bilal M, Rizwan M, Alsaidan I and Almasoudi FM. 2021. AI-based approach for optimal placement of EVCS and DG with reliability analysis. Institute of Electrical and Electronics Engineers, 9: 154204–154224. https://doi.org/10.1109/ACCESS.2021.3125135
Brenna M, Foiadelli F, Zaninelli D, Graditi G and Di Somma M. 2021. The integration of electric vehicles in smart distribution grids with other distributed resources. In: Graditi G and Di Somma M (eds). Distributed Energy Resources in Local Integrated Energy Systems. Elsevier, Amsterdam, Netherlands, pp. 315–345. https://doi.org/10.1016/B978-0-12-823899-8.00006-6
Chen L, Xu C, Song H and Jermsittiparsert K. 2021. Optimal sizing and sitting of EVCS in the distribution system using metaheuristics: a case study. Energy Reports, 7: 208–217. https://doi.org/10.1016/J.EGYR.2020.12.032
Clairan JM, Gonzales-Rodriguez M, Kumar R, Vyas S and Escriva-Escriva G. 2022. Optimal siting and sizing of electric taxi charging stations considering transportation and power system requirements. Energy, 256: 124572. https://doi.org/10.1016/j.energy.2022.124572
Danielis R, Giansoldati M and Rotaris L. 2018. A probabilistic total cost of ownership model to evaluate the current and future prospects of electric cars uptake in Italy. Energy Policy, 119: 268-281. https://doi.org/10.1016/j.enpol.2018.04.024
Fredriksson H, Dahl M and Holmgren J. 2019. Optimal placement of charging stations for electric vehicles in large-scale transportation networks. Procedia Computer Science, 160: 77–84. https://doi.org/10.1016/J.PROCS.2019.09.446
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Gampa SR, Jasthi K, Goli P, Das D and Bansal RC. 2020. Grasshopper optimization algorithm based two stages fuzzy multi-objective approach for optimum sizing and placement of distributed generations, shunt capacitors and electric vehicle charging stations. Journal of Energy Storage, 27: 101117. https://doi.org/10.1016/J.EST.2019.101117
Gschwendtner C, Sinsel SR and Stepan A. 2021. Vehicle-to-X (V2X) implementation: An overview of predominate trial configurations and technical, social and regulatory challenges. Renewable and Sustainable Energy Reviews, 145: 110977. https://doi.org/10.1016/j.rser.2021.110977
Gupta K, Achathuparambil R, Narayanankutty, Sundaramoorthy K and Sankar A. 2020. Optimal location identification for aggregated charging of electric vehicles in solar photovoltaic powered microgrids with reduced distribution losses. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects. https://doi.org/10.1080/15567036.2020.1745335
Hadian E, Akbari H, Farzinfar M and Saeed S. 2020. Optimal allocation of electric vehicle charging stations with adopted smart charging/discharging schedule. Institute of Electrical and Electronics Engineers, 8: 196908–196919. https://doi.org/10.1109/ACCESS.2020.3033662
Isa NBM, Wei TC and Yatim AHM. 2015. Smart grid technology: communications, power electronics and control system. 2015 International Conference on Sustainable Energy Engineering and Application (ICSEEA), Bandung, Indonesia, pp. 10-14. https://doi.org/10.1109/ICSEEA.2015.7380737
Jacobson MZ. 2017. Roadmaps to transition countries to 100% clean, renewable energy for all purposes to curtail global warming, air pollution, and energy risk. Earth’s Future, 5(10): 948–952. https://doi.org/10.1002/2017EF000672
Janamala V. 2022. Optimal siting of capacitors in distribution grids considering electric vehicle load growth using improved flower pollination algorithm. Serbian Journal of Electrical Engineering, 19(3): 329-349. https://doi.org/10.2298/SJEE2203329J
Katoch S, Chauhan SS and Kumar V. 2021. A review on genetic algorithm: past, present, and future. Multimedia Tools and Applications, 80(5): 8091–8126. https://doi.org/10.1007/s11042-020-10139-6
Khalkali K, Abapour S, Moghaddas-Tafreshi SM and Abapour M. 2015. Application of data envelopment analysis theorem in plug-in hybrid electric vehicle charging station planning. Institute of Engineering and Technology (IET) Generation, Transmission and Distribution, 9(7): 666–676. https://doi.org/10.1049/IET-GTD.2014.0554
Khan R, Mehmood KK, Bukhari SBA, Imran K, Wadood A, Rhee SB and Park S. 2021. An optimization-based reliability enhancement scheme for active distribution systems utilizing electric vehicles. Institute of Electrical and Electronics Engineers, 9: 157247–157258. https://doi.org/10.1109/ACCESS.2021.3127802
Kunj T and Pal K. 2020. Optimal location planning of EV charging station in existing distribution network with stability condition. 2020 7th International Conference on Signal Processing and Integrated Networks (SPIN), Noida, India, pp. 1060-1065. https://doi.org/10.1109/SPIN48934.2020.9071396
Lazari V and Chassiakos A. 2023. Multi-objective optimization of electric vehicle charging station deployment using genetic algorithms. Applied Sciences. 13(8): 4867. https://doi.org/10.3390/app13084867
Lee JH, Chakraborty D, Hardman SJ and Tal G. 2020. Exploring electric vehicle charging patterns: Mixed usage of charging infrastructure. Transportation Research Part D: Transport and Environment, 79: 102249. https://doi.org/10.1016/J.TRD.2020.102249
Liu Z, Wen F and Ledwich G. 2013. Optimal planning of electric-vehicle charging stations in distribution systems. Institute of Electrical and Electronics Engineers Transactions on Power Delivery, 28(1): 102–110. https://doi.org/10.1109/TPWRD.2012.2223489
Mehouachi I, Trojette M and Grayaa K. 2022. Optimal placement of electric vehicle charging infrastructure: study case of an urban area of Tunisia. Institute of Electrical and Electronics Engineers, 8: 189-194. https://doi.org/10.1109/CoDIT55151.2022.9803893.
Mehrabi A, Nunna HSVSK, Dadlani A, Moon S and Kim K. 2020. Decentralized greedy-based algorithm for smart energy management in plug-in electric vehicle energy distribution systems. Institute of Electrical and Electronics Engineers, 8: 75666–75681. https://doi.org/10.1109/ACCESS.2020.2987970
Miras AJJ, Manzano JPP, Aguirre RA and Aquino KMV. 2019. Sizing and siting of a concentrating solar power plant in an unbalanced radial distribution system. 2019 Institute of Electrical and Electronics Engineers, Power and Energy Society, Asia-Pacific Power and Energy Engineering Conference, Macao, China, pp. 1-6. https://doi.org/10.1109/APPEEC45492.2019.8994631
Narasipuram RP and Mopidevi S. 2021. A technological overview & design considerations for developing electric vehicle charging stations. Journal of Energy Storage, 43:103225. https://doi.org/10.1016/j.est.2021.103225
Pal A, Bhattacharya A and Chakraborty AK. 2021. Allocation of electric vehicle charging station considering uncertainties. Sustainable Energy, Grids and Networks, 25: 100422. https://doi.org/10.1016/J.SEGAN.2020.100422
Qiao D, Wang G and Xu M. 2023. Mathematical program with equilibrium constraints approach with genetic algorithm for joint optimization of charging station location and discrete transport network design. The International Journal of Transportation Research: Transportation Letters. https://doi.org/10.1080/19427867.2023.2237740
Rajendran A and Hari Kumar R. 2022. Optimal placement of electric vehicle charging stations in utility grid - a case study of Kerala state highway network. PESGRE 2022 – Institute of Electrical and Electronics Engineering International Conference on Power Electronics, Smart Grid, and Renewable Energy, Trivandrum, India, pp. 1-6. https://doi.org/10.1109/PESGRE52268.2022.9715934.
Sanguesa JA, Torres-Sanz V, Garrido P, Martinez FJ and Marquez-Barja JM. 2021. A review on electric vehicles: technologies and challenges. Smart Cities, 4(1): 372–404. https://doi.org/10.3390/smartcities4010022
Shaikh MS, Hua C, Hassan M, Raj S, Jatoi MA and Ansari MM. 2021. Optimal parameter estimation of overhead transmission line considering different bundle conductors with the uncertainty of load modeling. Optimal Control Applications and Methods, 43(3): 652-666. https://doi.org/10.1002/oca.2772
Shaikh MS, Raj S, Babu R, Kumar S and Sagrolikar K. 2023. A hybrid moth–flame algorithm with particle swarm optimization with application in power transmission and distribution. Decision Analytics, 6: 100182. https://doi.org/10.1016/j.dajour.2023.100182
Shaikh MS, Raj S, Ikram M and Khan W. 2022. Parameters estimation of AC transmission line by an improved moth flame optimization method. Journal of Electrical Systems and Information Technology, 9: 25. https://doi.org/10.1186/s43067-022-00066-x
Sofana Reka S, Venugopal P, V R, Haes Alhelou H, Al-Hinai A and Pierluigi S. 2022. Analysis of electric vehicles with an economic perspective for the future electric market. Future Internet, 14(6): 172. https://doi.org/10.3390/fi14060172
Su J, Lin M, Wang S, Li J, Coffie-Ken J and Xie F. 2019. An equivalent circuit model analysis for the lithium-ion battery pack in pure electric vehicles. Measurement and Control, 52(3-4): 193-201. https://doi.org/10.1177/0020294019827338
US DOE EERE (United States Department of Energy Energy Efficiency and Renewable Energy). 2023. The electric vehicle charging stations locations. Version 2023. https://afdc.energy.gov/fuels/electricity_locations.html#/find/nearest?fuel=ELEC. Accessed on 29 April 2023.
Yenchamchalit K, Kongjeen Y, Bhumkittipich K and Mithulnanthan N. 2018. Optimal sizing and location of the charging station for plug-in electric vehicles using the particle swarm optimization technique. 2018 International Electrical Engineering Congress, Krabi, Thailand, pp. 1-4. https://doi.org/10.1109/IEECON.2018.8712336
Zambrano-Perilla S, Ramos G and Rodriguez DFC. 2016. Modeling and impacts of plug-in electric vehicles in residential distribution systems with coordinated charging schemes. International Review on Modelling and Simulations (IREMOS), 9(4): 227–237. https://doi.org/10.15866/IREMOS.V9I4.9198
Zeb MZ, Imran K, Khattak A, Janjua, AK, Pal A, Nadeem M, Zhang J and Khan S. 2020. Optimal placement of electric vehicle charging stations in the active distribution network. Institute of Electrical and Electronics Engineers, 8: 68124–68134. https://doi.org/10.1109/ACCESS.2020.2984127
Zhang X, Xu Y, Lu S, Lu C and Guo Y. 2021. Joint planning of distributed PV stations and EV charging stations in the distribution systems based on chance-constrained programming. Institute of Electrical and Electronics Engineers, 9: 6756- 6768. https://doi.org/10.1109/ACCESS.2021.3049568
Zheng Y, Niu S, Shang Y, Shao Z and Jian L. 2019. 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, 112: 424–439. https://doi.org/10.1016/J.RSER.2019.05.059
Zhou X, Zou L, Ma Y and Gao Z. 2017. Research on impacts of the electric vehicles charging and discharging on power grid. Proceedings of the 29th Chinese Control and Decision Conference, Chongqing, China, pp. 1398–1402. https://doi.org/10.1109/CCDC.2017.7978736
Arif SM, Lie TT, Seet BC, Ayyadi S and Jensen K. 2021. Review of electric vehicle technologies, charging methods, standards and optimization techniques. Electronics, 10(16):1910. https://doi.org/10.3390/electronics10161910
Bayani R, Soofi AF, Waseem M and Manshadi SD. 2022. Impact of transportation electrification on the electricity grid—a review. Vehicles, 4(4): 1042-1079. https://doi.org/10.3390/vehicles4040056
Bilal M, Rizwan M, Alsaidan I and Almasoudi FM. 2021. AI-based approach for optimal placement of EVCS and DG with reliability analysis. Institute of Electrical and Electronics Engineers, 9: 154204–154224. https://doi.org/10.1109/ACCESS.2021.3125135
Brenna M, Foiadelli F, Zaninelli D, Graditi G and Di Somma M. 2021. The integration of electric vehicles in smart distribution grids with other distributed resources. In: Graditi G and Di Somma M (eds). Distributed Energy Resources in Local Integrated Energy Systems. Elsevier, Amsterdam, Netherlands, pp. 315–345. https://doi.org/10.1016/B978-0-12-823899-8.00006-6
Chen L, Xu C, Song H and Jermsittiparsert K. 2021. Optimal sizing and sitting of EVCS in the distribution system using metaheuristics: a case study. Energy Reports, 7: 208–217. https://doi.org/10.1016/J.EGYR.2020.12.032
Clairan JM, Gonzales-Rodriguez M, Kumar R, Vyas S and Escriva-Escriva G. 2022. Optimal siting and sizing of electric taxi charging stations considering transportation and power system requirements. Energy, 256: 124572. https://doi.org/10.1016/j.energy.2022.124572
Danielis R, Giansoldati M and Rotaris L. 2018. A probabilistic total cost of ownership model to evaluate the current and future prospects of electric cars uptake in Italy. Energy Policy, 119: 268-281. https://doi.org/10.1016/j.enpol.2018.04.024
Fredriksson H, Dahl M and Holmgren J. 2019. Optimal placement of charging stations for electric vehicles in large-scale transportation networks. Procedia Computer Science, 160: 77–84. https://doi.org/10.1016/J.PROCS.2019.09.446
GITT and ISATT (Grid Integration Tech Team and Integrated Systems Analysis Tech Team). 2019. Summary report on EVs at scale and the U.S. electric power system. U.S. Department of Energy. 21pp. https://www.energy.gov/eere/vehicles/articles/summary-report-evs-scale-and-us-electric-power-system-2019. Accessed on 29 April 2023.
Gampa SR, Jasthi K, Goli P, Das D and Bansal RC. 2020. Grasshopper optimization algorithm based two stages fuzzy multi-objective approach for optimum sizing and placement of distributed generations, shunt capacitors and electric vehicle charging stations. Journal of Energy Storage, 27: 101117. https://doi.org/10.1016/J.EST.2019.101117
Gschwendtner C, Sinsel SR and Stepan A. 2021. Vehicle-to-X (V2X) implementation: An overview of predominate trial configurations and technical, social and regulatory challenges. Renewable and Sustainable Energy Reviews, 145: 110977. https://doi.org/10.1016/j.rser.2021.110977
Gupta K, Achathuparambil R, Narayanankutty, Sundaramoorthy K and Sankar A. 2020. Optimal location identification for aggregated charging of electric vehicles in solar photovoltaic powered microgrids with reduced distribution losses. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects. https://doi.org/10.1080/15567036.2020.1745335
Hadian E, Akbari H, Farzinfar M and Saeed S. 2020. Optimal allocation of electric vehicle charging stations with adopted smart charging/discharging schedule. Institute of Electrical and Electronics Engineers, 8: 196908–196919. https://doi.org/10.1109/ACCESS.2020.3033662
Isa NBM, Wei TC and Yatim AHM. 2015. Smart grid technology: communications, power electronics and control system. 2015 International Conference on Sustainable Energy Engineering and Application (ICSEEA), Bandung, Indonesia, pp. 10-14. https://doi.org/10.1109/ICSEEA.2015.7380737
Jacobson MZ. 2017. Roadmaps to transition countries to 100% clean, renewable energy for all purposes to curtail global warming, air pollution, and energy risk. Earth’s Future, 5(10): 948–952. https://doi.org/10.1002/2017EF000672
Janamala V. 2022. Optimal siting of capacitors in distribution grids considering electric vehicle load growth using improved flower pollination algorithm. Serbian Journal of Electrical Engineering, 19(3): 329-349. https://doi.org/10.2298/SJEE2203329J
Katoch S, Chauhan SS and Kumar V. 2021. A review on genetic algorithm: past, present, and future. Multimedia Tools and Applications, 80(5): 8091–8126. https://doi.org/10.1007/s11042-020-10139-6
Khalkali K, Abapour S, Moghaddas-Tafreshi SM and Abapour M. 2015. Application of data envelopment analysis theorem in plug-in hybrid electric vehicle charging station planning. Institute of Engineering and Technology (IET) Generation, Transmission and Distribution, 9(7): 666–676. https://doi.org/10.1049/IET-GTD.2014.0554
Khan R, Mehmood KK, Bukhari SBA, Imran K, Wadood A, Rhee SB and Park S. 2021. An optimization-based reliability enhancement scheme for active distribution systems utilizing electric vehicles. Institute of Electrical and Electronics Engineers, 9: 157247–157258. https://doi.org/10.1109/ACCESS.2021.3127802
Kunj T and Pal K. 2020. Optimal location planning of EV charging station in existing distribution network with stability condition. 2020 7th International Conference on Signal Processing and Integrated Networks (SPIN), Noida, India, pp. 1060-1065. https://doi.org/10.1109/SPIN48934.2020.9071396
Lazari V and Chassiakos A. 2023. Multi-objective optimization of electric vehicle charging station deployment using genetic algorithms. Applied Sciences. 13(8): 4867. https://doi.org/10.3390/app13084867
Lee JH, Chakraborty D, Hardman SJ and Tal G. 2020. Exploring electric vehicle charging patterns: Mixed usage of charging infrastructure. Transportation Research Part D: Transport and Environment, 79: 102249. https://doi.org/10.1016/J.TRD.2020.102249
Liu Z, Wen F and Ledwich G. 2013. Optimal planning of electric-vehicle charging stations in distribution systems. Institute of Electrical and Electronics Engineers Transactions on Power Delivery, 28(1): 102–110. https://doi.org/10.1109/TPWRD.2012.2223489
Mehouachi I, Trojette M and Grayaa K. 2022. Optimal placement of electric vehicle charging infrastructure: study case of an urban area of Tunisia. Institute of Electrical and Electronics Engineers, 8: 189-194. https://doi.org/10.1109/CoDIT55151.2022.9803893.
Mehrabi A, Nunna HSVSK, Dadlani A, Moon S and Kim K. 2020. Decentralized greedy-based algorithm for smart energy management in plug-in electric vehicle energy distribution systems. Institute of Electrical and Electronics Engineers, 8: 75666–75681. https://doi.org/10.1109/ACCESS.2020.2987970
Miras AJJ, Manzano JPP, Aguirre RA and Aquino KMV. 2019. Sizing and siting of a concentrating solar power plant in an unbalanced radial distribution system. 2019 Institute of Electrical and Electronics Engineers, Power and Energy Society, Asia-Pacific Power and Energy Engineering Conference, Macao, China, pp. 1-6. https://doi.org/10.1109/APPEEC45492.2019.8994631
Narasipuram RP and Mopidevi S. 2021. A technological overview & design considerations for developing electric vehicle charging stations. Journal of Energy Storage, 43:103225. https://doi.org/10.1016/j.est.2021.103225
Pal A, Bhattacharya A and Chakraborty AK. 2021. Allocation of electric vehicle charging station considering uncertainties. Sustainable Energy, Grids and Networks, 25: 100422. https://doi.org/10.1016/J.SEGAN.2020.100422
Qiao D, Wang G and Xu M. 2023. Mathematical program with equilibrium constraints approach with genetic algorithm for joint optimization of charging station location and discrete transport network design. The International Journal of Transportation Research: Transportation Letters. https://doi.org/10.1080/19427867.2023.2237740
Rajendran A and Hari Kumar R. 2022. Optimal placement of electric vehicle charging stations in utility grid - a case study of Kerala state highway network. PESGRE 2022 – Institute of Electrical and Electronics Engineering International Conference on Power Electronics, Smart Grid, and Renewable Energy, Trivandrum, India, pp. 1-6. https://doi.org/10.1109/PESGRE52268.2022.9715934.
Sanguesa JA, Torres-Sanz V, Garrido P, Martinez FJ and Marquez-Barja JM. 2021. A review on electric vehicles: technologies and challenges. Smart Cities, 4(1): 372–404. https://doi.org/10.3390/smartcities4010022
Shaikh MS, Hua C, Hassan M, Raj S, Jatoi MA and Ansari MM. 2021. Optimal parameter estimation of overhead transmission line considering different bundle conductors with the uncertainty of load modeling. Optimal Control Applications and Methods, 43(3): 652-666. https://doi.org/10.1002/oca.2772
Shaikh MS, Raj S, Babu R, Kumar S and Sagrolikar K. 2023. A hybrid moth–flame algorithm with particle swarm optimization with application in power transmission and distribution. Decision Analytics, 6: 100182. https://doi.org/10.1016/j.dajour.2023.100182
Shaikh MS, Raj S, Ikram M and Khan W. 2022. Parameters estimation of AC transmission line by an improved moth flame optimization method. Journal of Electrical Systems and Information Technology, 9: 25. https://doi.org/10.1186/s43067-022-00066-x
Sofana Reka S, Venugopal P, V R, Haes Alhelou H, Al-Hinai A and Pierluigi S. 2022. Analysis of electric vehicles with an economic perspective for the future electric market. Future Internet, 14(6): 172. https://doi.org/10.3390/fi14060172
Su J, Lin M, Wang S, Li J, Coffie-Ken J and Xie F. 2019. An equivalent circuit model analysis for the lithium-ion battery pack in pure electric vehicles. Measurement and Control, 52(3-4): 193-201. https://doi.org/10.1177/0020294019827338
US DOE EERE (United States Department of Energy Energy Efficiency and Renewable Energy). 2023. The electric vehicle charging stations locations. Version 2023. https://afdc.energy.gov/fuels/electricity_locations.html#/find/nearest?fuel=ELEC. Accessed on 29 April 2023.
Yenchamchalit K, Kongjeen Y, Bhumkittipich K and Mithulnanthan N. 2018. Optimal sizing and location of the charging station for plug-in electric vehicles using the particle swarm optimization technique. 2018 International Electrical Engineering Congress, Krabi, Thailand, pp. 1-4. https://doi.org/10.1109/IEECON.2018.8712336
Zambrano-Perilla S, Ramos G and Rodriguez DFC. 2016. Modeling and impacts of plug-in electric vehicles in residential distribution systems with coordinated charging schemes. International Review on Modelling and Simulations (IREMOS), 9(4): 227–237. https://doi.org/10.15866/IREMOS.V9I4.9198
Zeb MZ, Imran K, Khattak A, Janjua, AK, Pal A, Nadeem M, Zhang J and Khan S. 2020. Optimal placement of electric vehicle charging stations in the active distribution network. Institute of Electrical and Electronics Engineers, 8: 68124–68134. https://doi.org/10.1109/ACCESS.2020.2984127
Zhang X, Xu Y, Lu S, Lu C and Guo Y. 2021. Joint planning of distributed PV stations and EV charging stations in the distribution systems based on chance-constrained programming. Institute of Electrical and Electronics Engineers, 9: 6756- 6768. https://doi.org/10.1109/ACCESS.2021.3049568
Zheng Y, Niu S, Shang Y, Shao Z and Jian L. 2019. 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, 112: 424–439. https://doi.org/10.1016/J.RSER.2019.05.059
Zhou X, Zou L, Ma Y and Gao Z. 2017. Research on impacts of the electric vehicles charging and discharging on power grid. Proceedings of the 29th Chinese Control and Decision Conference, Chongqing, China, pp. 1398–1402. https://doi.org/10.1109/CCDC.2017.7978736
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