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Research Articles

Charging Coordination of Plug-in Electric Vehicles Considering Machine Learning Based State-of-Charge Prediction for Congestion Management in Distribution System

ORCID Icon, ORCID Icon, &
Pages 131-150 | Received 11 Jul 2021, Accepted 27 Dec 2022, Published online: 16 Jan 2023

References

  • K. Clement-Nyns, E. Haesen and J. Driesen, “The impact of charging plug-in hybrid electric vehicles on a residential distribution grid,” IEEE Trans. Power Syst., vol. 25, no. 1, pp. 371–380, 2010. DOI: 10.1109/TPWRS.2009.2036481.
  • M. Yilmaz and P. T. Krein, “Review of the impact of vehicle-to-grid technologies on distribution systems and utility interfaces,” IEEE Trans. Power Electron., vol. 28, no. 12, pp. 5673–5689, 2013. DOI: 10.1109/TPEL.2012.2227500.
  • J. A. P. Lopes, F. J. Soares and P. M. R. Almeida, “Integration of electric vehicles in the electric power system,” Proc. IEEE, vol. 99, no. 1, pp. 168–183, Jan. 2011. DOI: 10.1109/JPROC.2010.2066250.
  • Global EV Outlook 2019, Scaling-up the Transition to Electric Mobility, pp. 1–232. Paris, France: IEA, Jun. 2019.
  • D. Wu, D. C. Aliprantis and L. Ying, “Load scheduling and dispatch for aggregators of plug-in electric vehicles,” IEEE Trans. Smart Grid, vol. 3, no. 1, pp. 368–376, 2012. DOI: 10.1109/TSG.2011.2163174.
  • W. Su and M. Y. Chow, “Performance evaluation of an EDA-based large-scale plug-in hybrid electric vehicle charging algorithm,” IEEE Trans. Smart Grid, vol. 3, no. 1, pp. 308–315, 2012. DOI: 10.1109/TSG.2011.2151888.
  • E. Sortomme, M. M. Hindi, S. D. J. MacPherson and S. S. Venkata, “Coordinated charging of plug-in hybrid electric vehicles to minimize distribution system losses,” IEEE Trans. Smart Grid, vol. 2, no. 1, pp. 198–205, 2011. DOI: 10.1109/TSG.2010.2090913.
  • 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 Trans. Smart Grid, vol. 2, no. 3, pp. 456–467, Sep. 2011. DOI: 10.1109/TSG.2011.2159816.
  • S. Han, S. Han and K. Sezaki, “Estimation of achievable power capacity from plug-in electric vehicles for V2G frequency regulation: Case studies for market participation,” IEEE Trans. Smart Grid, vol. 2, no. 4, pp. 632–641, 2011. DOI: 10.1109/TSG.2011.2160299.
  • S. Han, S. Han and K. Sezaki, “Development of an optimal vehicle-to-grid aggregator for frequency regulation,” IEEE Trans. Smart Grid, vol. 1, no. 1, pp. 65–72, 2010. DOI: 10.1109/TSG.2010.2045163.
  • W. Kempton and J. Tomic, “Vehicle-to-grid power fundamentals: Calculating capacity and net revenue,” J. Power Sources, vol. 144, no. 1, pp. 268–279, 2005. DOI: 10.1016/j.jpowsour.2004.12.025.
  • Z. Tan, P. Yang and A. Nehorai, “An optimal and distributed demand response strategy with electric vehicles in the smart grid,” IEEE Trans. Smart Grid, vol. 5, no. 2, pp. 861–869, 2014. DOI: 10.1109/TSG.2013.2291330.
  • K. Clement-Nyns, E. Haesen and J. Driesen, “The impact of vehicle-to grid on the distribution grid,” Electric Power Syst. Research, vol. 81, no. 1, pp. 185–192, 2011. Jan DOI: 10.1016/j.epsr.2010.08.007.
  • B. Khorramdel, H. Khorramdel, J. Aghaei, A. Heidari and V. G. Agelidis, “Voltage security considerations in optimal operation of BEVs/PHEVs integrated microgrids,” IEEE Trans. Smart Grid, vol. 6, no. 4, pp. 1575–1587, 2015. DOI: 10.1109/TSG.2015.2394499.
  • S. Rezaee, E. Farjah and B. Khorramdel, “Probabilistic analysis of plug-in electric vehicles impact on electrical grid through homes and parking lots,” IEEE Trans. Sustain. Energy, vol. 4, no. 4, pp. 1024–1033, 2013. DOI: 10.1109/TSTE.2013.2264498.
  • O. M. Abdelwahab, A. A. Shalaby and M. F. Shaaban, “An optimal resource allocation for future parking lots with charger assignment considering uncertainities,” Electric Power Syst. Research, vol. 200, pp. 107455, 2021. DOI: 10.1016/j.epsr.2021.107455.
  • C. Sabillón Antúnez, J. F. Franco, M. J. Rider and R. Romero, “A new methodology for the optimal charging coordination of electric vehicles considering vehicle-to-grid technology,” IEEE Trans. Sustain. Energy, vol. 7, no. 2, pp. 596–607, 2016. DOI: 10.1109/TSTE.2015.2505502.
  • C. B. Saner, A. Trivedi and D. Srinivasan, “A cooperative hierarchical multi-agent system for EV charging scheduling in presence of multiple charging stations,” IEEE Trans. Smart Grid, vol. 13, no. 3, pp. 2218–2233, 2022. DOI: 10.1109/TSG.2022.3140927,2022.
  • Y. Jiang, Q. Ye, B. Sun, Y. Wu and D. H. K. Tsang, “Data-driven coordinated charging for electric vehicles with continuous charging rates: A deep policy gradient approach,” IEEE Internet Things J, vol. 9DOI 10, no. 14, pp. 12395–12412, 2022. 1109/JIOT.20213135977 DOI: 10.1109/JIOT.2021.3135977.
  • J. Martinez-Piazuelo, N. Quijano and C. Ocampo-Martinez, “Decentralized charging coordination of electric vehicles under feeder capacity constraints,” IEEE Trans. Control Netw. Syst, vol. 9, no. 4, pp. 1600–1610, 2022. DOI 101109/TCNS.20213128498 DOI: 10.1109/TCNS.2021.3128498.
  • A. Rabiee, A. Keane and A. Soroudi, “Enhanced transmission and distribution network coordination to host more electric vehicles and PV,” IEEE Syst. J., vol. 16, no. 2, pp. 2705–2716, 2022. DOI 101109/JSYST20213092785 DOI: 10.1109/JSYST.2021.3092785.
  • R. Mehta, D. Srinivasan, A. M. Khambadkone, J. Yang and A. Trivedi, “Smart charging strategies for optimal integration of plug-in electric vehicles within existing distribution system infrastructure,” IEEE Trans. Smart Grid, vol. 9, no. 1, pp. 299–312, Apr. 2018. DOI: 10.1109/TSG.2016.2550559.
  • R. Mehta, D. Srinivasan and A. Trivedi, “Optimal charging scheduling of plug-in electric vehicles for maximizing penetration within a workplace car park,” 2016 IEEE Congress on Evolutionary Computation (CEC), Vancouver, BC, Canada. IEEE, pp. 3646–3653, Nov. 2016. DOI: 10.1109/CEC.2016.7744251.
  • J. Hu, S. You, M. Lind and J. Ostergard, “Coordinated charging of electric vehicles for congestion prevention in the distribution grid,” IEEE Trans. Smart Grid, vol. 5, no. 2, pp. 703–711, Mar. 2014. DOI: 10.1109/TSG.2013.2279007.
  • J. Hu, A. Saleem, S. You, L. Nordström, M. Lind and J. Østergaard, “A multi-agent system for distribution grid congestion management with electric vehicles,” Eng. Applicat. Arti. Intel., vol. 38, pp. 45–58, 2015. DOI: 10.1016/j.engappai.2014.10.017.
  • P. B. Andersen, J. Hu and K. Heussen, “Coordination strategies for distribution grid congestion management in a multi-actor, multi-objective setting,” 2012 3rd IEEE PES Innovative Smart Grid Technologies Europe, Berlin, Germany. IEEE, pp. 1–8, Oct. 2012.
  • S. Deb, P. Harsh, J. P. Sahoo and A. K. Goswami, “Charging coordination of plug-in electric vehicle for congestion management in distribution system,” Int. J. Emerg. Electric Power Syst., vol. 19, no. 5, pp. 1–17, Aug. 2018. DOI: 10.1515/ijeeps-2018-0050.
  • M. A. Lopez, S. Martin, J. A. Aguado and S. de la Torre, “V2G strategies for congestion management in microgrids with high penetration of electric vehicles,” Electric Power Syst. Research, vol. 104, pp. 28–34, 2013. DOI: 10.1016/j.epsr.2013.06.005.
  • Y. He, B. Venkatesh and L. Guan, “Optimal scheduling for charging and discharging of electric vehicles,” IEEE Trans. Smart Grid, vol. 3, no. 3, pp. 1095–1105, 2012. DOI: 10.1109/TSG.2011.2173507.
  • Z. Ma, N. Yang, S. Zou and Y. Shao, “Charging coordination of plug-in electric vehicles in distribution networks with capacity constrained feeder lines,” IEEE Trans. Contr. Syst. Technol., vol. 26, no. 5, pp. 1917–1924, 2018. DOI: 10.1109/TCST.2017.2730825.
  • A. Asrari, M. Ansari, J. Khazaei and P. Fajri, “A market framework for decentralized congestion management in smart distribution grids considering collaboration among electric vehicle aggregators,” IEEE Trans. Smart Grid, vol. 11, no. 2, pp. 1147–1158, 2020. DOI: 10.1109/TSG.2019.2932695.
  • M. Abdul Quddus, M. Yavuz, J. M. Usher and M. Marufuzzaman, “Managing load congestion in electric vehicle charging stations under power demand uncertainty,” Expert Syst. Appl., vol. 125, pp. 195–220, 2019. DOI: 10.1016/j.eswa.2019.02.003.
  • S. Huang and Q. Wu, “Dynamic Tariff-subsidy method for PV and V2G congestion management in distribution networks,” IEEE Trans. Smart Grid, vol. 10, no. 5, pp. 5851–5860, 2019. DOI: 10.1109/TSG.2019.2892302.
  • J. Zhao, Y. Wang, G. Song, P. Li, C. Wang and J. Wu, “Congestion management method of low-voltage active distribution networks based on distribution locational marginal price,” IEEE Access, vol. 7, pp. 32240–32255, 2019. DOI: 10.1109/ACCESS.2019.2903210.
  • J. Hu, C. Si, M. Lind and R. Yu, “Preventing distribution grid congestion by integrating indirect control in a hierarchical electric vehicles’ management system,” IEEE Trans. Transp. Electrific, vol. 2, no. 3, pp. 290–299, 2016. DOI: 10.1109/TTE.2016.2554469.
  • J. Tan and L. Wang, “Integration of plug-in hybrid electric vehicles into residential distribution grid based on two-layer intelligent optimization,” IEEE Trans. Smart Grid, vol. 5, no. 4, pp. 1774–1784, 2014. DOI: 10.1109/TSG.2014.2313617.
  • T. Ma and O. A. Mohammed, “Optimal charging of plug-in electric vehicles for a car-park infrastructure,” IEEE Trans. Ind. Appl., vol. 50, no. 4, pp. 2323–2330, 2014. DOI: 10.1109/TIA.2013.2296620.
  • U. C. Chukwu and S. M. Mahajan, “V2G parking lot with PV rooftop for capacity enhancement of distribution system,” IEEE Trans. Sustain. Ener., vol. 5, no. 1, pp. 119–127, January 2014. DOI: 10.1109/TSTE.2013.2274601.
  • A. Mohamed, V. Salehi, T. Ma and O. Mohammed, “Real-time energy management algorithm for plug-in hybrid electric vehicle charging parks involving sustainable energy,” IEEE Trans. Sustain. Ener., vol. 5, no. 2, pp. 577–586, 2014. DOI: 10.1109/TSTE.2013.2278544.
  • N. Neyestani, M. Yazdani Damavandi, M. Shafie-Khah, J. Contreras and J. P. S. Catalao, “Allocation of plug-in vehicles’ parking lots in distribution systems considering network-constrained objectives,” IEEE Trans. Power Syst., vol. 30, no. 5, pp. 2643–2656, 2015. DOI: 10.1109/TPWRS.2014.2359919.
  • E. Veldman and R. A. Verzijlbergh, “Distribution grid impacts of smart electric vehicle charging from different perspectives,” IEEE Trans. Smart Grid, vol. 6, no. 1, pp. 333–342, 2015. DOI: 10.1109/TSG.2014.2355494.
  • C. Hutson, G. K. Venayagamoorthy and K. A. Corzine, “Intelligent scheduling of hybrid and electric vehicle storage capacity in a parking lot for profit maximization in grid power transactions,” Energy2030 Conference, 2008 ENERGY 2008, 2008. IEEE, pp. 1–8.
  • Y. Cao, et al., “An optimized EV charging model considering TOU price and SOC curve,” IEEE Trans. Smart Grid, vol. 3, no. 1, pp. 388–393, Mar. 2012. DOI: 10.1109/TSG.2011.2159630.
  • S. Singh, M. Singh and S. C. Kausik, “Feasibility study on a islanded microgrid in rural area consisting PV, wind, biomass and battery energy storage system,” Energy Conver. Manag., vol. 128, pp. 178–190, 2016. DOI: 10.1016/j.enconman.2016.09.046.
  • D. Tang and P. Wang, “Stocastic modelling of electric vehicle movable loads: nodal impact from transportation,” International Conference on Probabilistic Methods Applied to Power Systems (PMAPS), pp. 1–6. Jul. 2014.
  • Y. Zhang and A. Haghani, “A gradient boosting method to improve travel time prediction,” Transportation Res. Part C, vol. 58, pp. 308–324, 2015. DOI: 10.1016/j.trc.2015.02.019.
  • J. Kennedy and R. Eberhart, “Particle swarm optimization,” In Proceedings of the IEEE International Conference on Neural Networks IV, pp. 1942–1948, 1995.
  • D. Wang, D. Tan and L. Liu, “Particle swarm optimization algorithm: An overview,” Soft Comput., vol. 22, no. 2, pp. 387–408, 2018. DOI: 10.1007/s00500-016-2474-6.
  • T. Wang, et al., “Random forest-Bayesisn optimization for product quality prediction with large-scale dimensions in process industrial cyber physical systems,” IEEE Internet Things J, vol. 7, no. 9, pp. 8641–8653, Sep. 2020. DOI: 10.1109/JIOT.2020.2992811.
  • Z. Wang, F. Hutter, M. Zoghi, D. Matheson and N. de Feitas, “Bayesian optimization in a billion dimensions via random embeddings,” JAIR, vol. 55, no. 1, pp. 361–387, 2016. DOI: 10.1613/jair.4806.
  • S. Afshar, K. Morris and A. Khajepour, “State-of-charge estimation using an EKF-based adaptive observer,” IEEE Trans. Contr. Syst. Technol., vol. 27, no. 5, pp. 1907–1923, 2019. DOI: 10.1109/TCST.2018.2842038.
  • F. Zhao, Y. Li, X. Wang, L. Bai and T. Liu, “Lithium-ion batteries state of charge prediction of electric vehicles using RNNs-CNNs neural networks,” IEEE Access., vol. 8, pp. 98168–98180, 2020. DOI: 10.1109/ACCESS.2020.2996225.
  • L. Xuan, L. Qian, J. Chen, X. Bai and B. Wu, “State-of-charge prediction of battery management system based on principal component analysis and improved support vector machine for regression,” IEEE Access, vol. 8, pp. 164693–164704, 2020. DOI: 10.1109/ACCESS.2020.3021745.
  • B. S. Bhangu, P. Bentley, D. A. Stone and C. M. Bingham, “Nonlinear observers for predicting state-of-charge and state-of-health of lead-acid batteries for hybrid-electric vehicles,” IEEE Trans. Veh. Technol., vol. 54, no. 3, pp. 783–794, 2005. DOI: 10.1109/TVT.2004.842461.
  • T. Zahid, K. Xu, W. Li, C. Li and H. Li, “State of charge estimation for electric vehicle power battery using advanced machine learning algorithm under diversified drive cycles,” Energy, vol. 162, pp. 871–882, 2018. DOI: 10.1016/j.energy.2018.08.071.
  • A. Ashtari, E. Bibeau, S. Shahidinejad and T. Molinski, “PEV charging profile prediction and analysis based on vehicle usage data,” IEEE Trans. Smart Grid, vol. 3, no. 1, pp. 341–350, 2012. DOI: 10.1109/TSG.2011.2162009.
  • X. S. Yang, “Firefly algorithms for multimodal optimization,” in Stochastic Algorithms: Foundations and Applications. SAGA 2009. Lecture Notes in Computer Science, Watanabe, O., Zeugmann, T., Eds., vol. 5792, Berlin, Heidelberg: Springer, pp. 169–178, 2009. DOI: 10.1007/978-3-642-04944-6_14.
  • J. Li, X. Wei, B. Li and Z. Zeng, “A survey on firefly algorithms,” Neurocomputing, vol. 500, pp. 662–678, 2022. DOI: 10.1016/j.neucom.2022.05.100.

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