Operative Analysis of Controlled Charging Management for Electric Vehicles: Centralized and Decentralized Coordination

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Published: Oct 13, 2025
Updated: 2025-10-13
Versions:
2025-10-13 (3)
DOI: https://doi.org/10.17163/ings.n34.2025.04
Keywords:
Electric Vehicle Aggregators, Monte Carlo Simulation, Optimal Power Flow, Distribution Network Operator, Power System

Main Article Content

Carlos W. Villanueva-Machado
Universidad Nacional de Ingeniería
https://orcid.org/0000-0002-0925-2541
Jaime E. Luyo
Universidad Nacional de Ingeniería
https://orcid.org/0000-0002-1890-8127
Alberto Rios-Villacorta
Universidad Técnica de Ambato
https://orcid.org/0000-0001-7334-5681

Abstract

Electric vehicle (EV) charging management can be implemented through centralized or decentralized strategies. Strategic coordination between these approaches enhances system efficiency and balances energy loads, thereby supporting the widespread adoption of EVs and fostering a sustainable, emissions-free society. In this study, distribution network operators (DNOs), acting as centralized charging managers, are responsible for mitigating the lack of coordination among electric vehicle aggregators (EVAs), which represent decentralized managers. The primary objective of the centralized management in this research is to constrain each decentralized optimization model, characterized using Monte Carlo simulations. Three EV adoption scenarios--comprising 2,000, 2,500, and 3,750 vehicles--are evaluated by comparing decentralized charging management with an unregulated charging baseline in the IEEE 14-bus power system. Improvements are required only in the highest adoption scenario, where the proposed centralized coordination model is applied. The study models energy trading constraints for each EVA, assigning one aggregator per load-bearing bus in the system. Transmission-level results are analyzed and then synthesized for application in the IEEE 13-bus distribution power system. Findings demonstrate that coordinated centralized and decentralized charging management significantly improves operational conditions in both transmission and distribution networks without necessitating changes to travel behavior.

Article Details

Issue
No. 34 (2025): july-december
Section
Scientific Paper
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References

C. W. Villanueva-Machado, J. E. Luyo, and A. Rios-Villacorta, “Impacto de la simulación montecarlo de carga no controlada de vehículos eléctricos en la generación distribuida,” Ingenius, no. 30, pp. 120–134, Jul. 2023. [Online]. Available: https://doi.org/10.17163/ings.n30.2023.10

S. Li, P. Zhao, C. Gu, J. Li, S. Cheng, and M. Xu, “Battery protective electric vehicle charging management in renewable energy system,” IEEE Transactions on Industrial Informatics, vol. 19, no. 2, pp. 1312–1321, Feb. 2023. [Online]. Available: https://doi.org/10.1109/TII.2022.3184398

Y. Yang, Q.-S. Jia, G. Deconinck, X. Guan, Z. Qiu, and Z. Hu, “Distributed coordination of ev charging with renewable energy in a microgrid of buildings,” IEEE Transactions on Smart Grid, vol. 9, no. 6, pp. 6253–6264, Nov. 2018. [Online]. Available: https://doi.org/10.1109/TSG.2017.2707103

A. J. Cheng, B. Tarroja, B. Shaffer, and S. Samuelsen, “Comparing the emissions benefits of centralized vs. decentralized electric vehicle smart charging approaches: A case study of the year 2030 california electric grid,” Journal of Power Sources, vol. 401, pp. 175–185, Oct. 2018. [Online]. Available: https://doi.org/10.1016/j.jpowsour.2018.08.092

S. Zeynali, N. Rostami, A. Ahmadian, and A. Elkamel, “Two-stage stochastic home energy management strategy considering electric vehicle and battery energy storage system: An ann-based scenario generation methodology,” Sustainable Energy Technologies and Assessments, vol. 39, p. 100722, Jun. 2020. [Online]. Available: https://doi.org/10.1016/j.seta.2020.100722

M. R. Sarker, H. Pandžić, K. Sun, and M. A. Ortega-Vazquez, “Optimal operation of aggregated electric vehicle charging stations coupled with energy storage,” IET Generation, Transmission & Distribution, vol. 12, no. 5, pp. 1127–1136, Jan. 2018. [Online]. Available: https://doi.org/10.1049/iet-gtd.2017.0134

M. R. Sarker, Y. Dvorkin, and M. A. Ortega-Vazquez, “Optimal participation of an electric vehicle aggregator in day-ahead energy and reserve markets,” IEEE Transactions on Power Systems, vol. 31, no. 5, pp. 3506–3515, Sep. 2016. [Online]. Available: https://doi.org/10.1109/TPWRS.2015.2496551

H. Kikusato, K. Mori, S. Yoshizawa, Y. Fujimoto, H. Asano, Y. Hayashi, A. Kawashima, S. Inagaki, and T. Suzuki, “Electric vehicle charge–discharge management for utilization of photovoltaic by coordination between home and grid energy management systems,” IEEE Transactions on Smart Grid, vol. 10, no. 3, pp. 3186–3197, May 2019. [Online]. Available: http://dx.doi.org/10.1109/TSG.2018.2820026

M. F. Shaaban, M. Ismail, E. F. El-Saadany, and W. Zhuang, “Real-time pev charging/discharging coordination in smart distribution systems,” IEEE Transactions on Smart Grid, vol. 5, no. 4, pp. 1797–1807, Jul. 2014. [Online]. Available: http://dx.doi.org/10.1109/TSG.2014.2311457

M. M. Hoque, M. Khorasany, R. Razzaghi, H. Wang, and M. Jalili, “Transactive coordination of electric vehicles with voltage control in distribution networks,” IEEE Transactions on Sustainable Energy, vol. 13, no. 1, pp. 391–402, Jan. 2022. [Online]. Available: https://doi.org/10.1109/TSTE.2021.3113614

N. Rahbari-Asr and M.-Y. Chow, “Cooperative distributed demand management for community charging of phev/pevs based on kkt conditions and consensus networks,” IEEE Transactions on Industrial Informatics, vol. 10, no. 3, pp. 1907–1916, Aug. 2014. [Online]. Available: https://doi.org/10.1109/TII.2014.2304412

D. Said and H. T. Mouftah, “A novel electric vehicles charging/discharging management protocol based on queuing model,” IEEE Transactions on Intelligent Vehicles, vol. 5, no. 1, pp. 100–111, Mar. 2020. [Online]. Available: https://doi.org/10.1109/TIV.2019.2955370

X. Yang, C. Xu, Y. Zhang, W. Yao, J. Wen, and S. Cheng, “Real-time coordinated scheduling for adns with soft open points and charging stations,” IEEE Transactions on Power Systems, vol. 36, no. 6, pp. 5486–5499, Nov. 2021. [Online]. Available: https://doi.org/10.1109/TPWRS.2021.3070036

M. Shafie-Khah, P. Siano, D. Z. Fitiwi, N. Mahmoudi, and J. P. S. Catalao, “An innovative two-level model for electric vehicle parking lots in distribution systems with renewable energy,” IEEE Transactions on Smart Grid, vol. 9, no. 2, pp. 1506–1520, Mar. 2018. [Online]. Available: https://doi.org/10.1109/TSG.2017.2715259

M. Mohiti, H. Monsef, and H. Lesani, “A decentralized robust model for coordinated operation of smart distribution network and electric vehicle aggregators,” International Journal of Electrical Power & Energy Systems, vol. 104, pp. 853–867, Jan. 2019. [Online]. Available: https://doi.org/10.1016/j.ijepes.2018.07.054

M. S. H. Nizami, M. J. Hossain, and K. Mahmud, “A coordinated electric vehicle management system for grid-support services in residential networks,” IEEE Systems Journal, vol. 15, no. 2, pp. 2066–2077, Jun. 2021. [Online]. Available: https://doi.org/10.1109/JSYST.2020.3006848

F. L. D. Silva, C. E. H. Nishida, D. M. Roijers, and A. H. R. Costa, “Coordination of electric vehicle charging through multiagent reinforcement learning,” IEEE Transactions on Smart Grid, vol. 11, no. 3, pp. 2347–2356, May 2020. [Online]. Available: https://doi.org/10.1109/TSG.2019.2952331

S. Deilami, A. S. Masoum, P. S. Moses, and M. A. S. Masoum, “Real-time coordination of plug-in electric vehicle charging in smart grids to minimize power losses and improve voltage profile,” IEEE Transactions on Smart Grid, vol. 2, no. 3, pp. 456–467, Sep. 2011. [Online]. Available: https://doi.org/10.1109/TSG.2011.2159816

J. Hu, S. You, M. Lind, and J. Ostergaard, “Coordinated charging of electric vehicles for congestion prevention in the distribution grid,” IEEE Transactions on Smart Grid, vol. 5, no. 2, pp. 703–711, Mar. 2014. [Online]. Available: https://doi.org/10.1109/TSG.2013.2279007

M. R. Sarker, M. A. Ortega-Vazquez, and D. S. Kirschen, “Optimal coordination and scheduling of demand response via monetary incentives,” IEEE Transactions on Smart Grid, vol. 6, no. 3, pp. 1341–1352, May 2015. [Online]. Available: https://doi.org/10.1109/TSG.2014.2375067

J. Luyo*, C. Villanueva, A. Delgado*, and C. Carbajal, “Electric vehicles aggregator participation in energy markets considering uncertainty travel patterns,” International Journal of Innovative Technology and Exploring Engineering, vol. 8, no. 12, pp. 4994–4998, Oct. 2019. [Online]. Available: http://dx.doi.org/10.35940/ijitee.L3747.1081219

P. Harsh and D. Das, “Optimal coordination strategy of demand response and electric vehicle aggregators for the energy management of reconfigured grid-connected microgrid,” Renewable and Sustainable Energy Reviews, vol. 160, p. 112251, May 2022. [Online]. Available: https://doi.org/10.1016/j.rser.2022.112251

W. Yang, J. Guo, and A. Vartosh, “Retracted: Optimal economic-emission planning of multi-energy systems integrated electric vehicles with modified group search optimization,” Applied Energy, vol. 311, p. 118634, Apr. 2022. [Online]. Available: https://doi.org/10.1016/j.apenergy.2022.118634

S. Gupta, A. Maulik, D. Das, and A. Singh, “Coordinated stochastic optimal energy management of grid-connected microgrids considering demand response, plug-in hybrid electric vehicles, and smart transformers,” Renewable and Sustainable Energy Reviews, vol. 155, p. 111861, Mar. 2022. [Online]. Available: https://doi.org/10.1016/j.rser.2021.111861

A. Najafi, M. Pourakbari-Kasmaei, M. Jasinski, M. Lehtonen, and Z. Leonowicz, “A hybrid decentralized stochastic-robust model for optimal coordination of electric vehicle aggregator and energy hub entities,” Applied Energy, vol. 304, p. 117708, Dec. 2021. [Online]. Available: https://doi.org/10.1016/j.apenergy.2021.117708

EV Volumes. (2023) Global ev sales for 2023. EV Volumes Autovista Group. [Online]. Available: https://upsalesiana.ec/ing34ar4r26

PNUMA, Movilidad eléctrica: Avances 19 en américa latina y el caribe 2019. Programa de las Naciones Unidas para el MedioAmbiente, 2019. [Online]. Available: https://upsalesiana.ec/ing34ar4r27

LNE. (2023) Aumentó la penetración de vehículos eléctricos e híbridos en américa latina durante el 2022. La nota económica. [Online]. Available: https://upsalesiana.ec/ing34ar4r28

MOVELATAM, Interoperability for recharging electric vehicles in latin america and the caribbean, practical guide of recommendations. United Nations Environment Programme, 2022. [Online]. Available: https://upsalesiana.ec/ing34ar4r29

AAP. (2019) Los protagonistas de la nueva era automotriz: Vehículos eléctricos e hibrídos en el perú. Asociación Automotríz del Perú. [Online]. Available: https://upsalesiana.ec/ing34ar4r30

C. W. Villanueva. (2024) Operative analysis of electric vehicle controlled charging management: Centralized - decentralized coordination. Git-Hub. Inc. [Online]. Available: https://upsalesiana.ec/ing34ar4r37

L. Wang, S. Sharkh, and A. Chipperfield, “Optimal decentralized coordination of electric vehicles and renewable generators in a distribution network using a* search,” International Journal of Electrical Power & Energy Systems, vol. 98, pp. 474–487, Jun. 2018. [Online]. Available: https://doi.org/10.1016/j.ijepes.2017.11.036

S. Pirouzi, J. Aghaei, T. Niknam, H. Farahmand, and M. Korpas, “Exploring prospective benefits of electric vehicles for optimal energy conditioning in distribution networks,” Energy, vol. 157, pp. 679–689, Aug. 2018. [Online]. Available: https://doi.org/10.1016/j.energy.2018.05.195

J. Czyzyk, M. Mesnier, and J. More, “The neos server,” IEEE Computational Science and Engineering, vol. 5, no. 3, pp. 68–75, 1998. [Online]. Available: https://doi.org/10.1109/99.714603

E. D. Dolan, NEOS server 4.0 administrative guide., Jul. 2001. [Online]. Available: http://dx.doi.org/10.2172/822567

W. Gropp and J. J. More, “Optimization environments and the neos server,” in Conference: 3. international workshop on short term experiments under strongly reduced gravity conditions, Bremen (Germany), 8-11 Jul 1996. Argonne National Lab. (ANL), Argonne, IL (United States), 03 1997. [Online]. Available: https://upsalesiana.ec/ing34ar4r35

PSCAD. (2018) Ieee 14 bus system. Manitoba Hydro International Ltd. [Online]. Available https://upsalesiana.ec/ing34ar4r36