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ISSN (Print): 2352-0965
ISSN (Online): 2352-0973

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Research Article

Effects of Optimization on User-based Charging/Discharging Control Strategy

Author(s): Zohaib Khan and Yang Wang*

Volume 15, Issue 2, 2022

Published on: 26 April, 2022

Page: [158 - 170] Pages: 13

DOI: 10.2174/2215083808666220324144603

Price: $65

Abstract

With the increase in the number of Electric Vehicles (EVs), more power will be needed from the grid. An increase in the load demand, losses, and grid operational costs will occur. Furthermore, with the increasing number of EVs, there comes a possibility of user dissatisfaction which can further lower the popularity of EVs.

Objective: This article focuses on EV battery charging and discharging control optimization, i.e., optimizing load demand to minimize power grid system losses and reduce charging costs. It also aids in the vehicle to grid (V2G) process while considering the "User Decision Variable" for each prospective EV.

Methods: As a load minimization problem, the optimal power flow model has been formulated first, then the problem has been formulated for each EV. The operational cost of the charging station is an objective function.

Results: Further investigation of the load minimization of the IEEE33-bus system has been carried out, and Particle Swarm Optimization (PSO) algorithm is proposed.

Conclusion: MATLAB results show that the proposed strategy to charge and discharge can decrease losses from the power grid, reduce the running operational cost while considering battery life and the user's sense of security.

Keywords: Charging station, electric vehicles, optimal power flow, particle swarm optimization, smart load, peak shaving.

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[1]
" Electric Transportation, "Electric vehicle sales: Facts & figures"", Cust. Solut, pp. 1-4, 2019.
[2]
U.C. Chukwu, The impact of V2G on power factors.In: 2020 Clemson University Power Systems Conference., PSC, 2020, pp. 1-4.
[http://dx.doi.org/10.1109/PSC50246.2020.9131328]
[3]
H. Qi, X. Gao, Y. Gao, H. Zhong, and Z. Li, "Optimization of the active distribution network operation considering the V2G mode of electric vehicles",", In: 2018 IEEE International Conference on Power System Technology (POWERCON), 2018, pp. 4488-4493.
[4]
K. Adetunji, I. Hofsajer, and L. Cheng, "A coordinated charging model for electric vehicles in a smart grid using whale optimization algorithm", In: 2020 IEEE 23rd International Conference on Information Fusion, 2020, pp. 1-7.
[http://dx.doi.org/10.23919/FUSION45008.2020.9190284]
[5]
E. Saberbari, H. Saboori, and S. Saboori, " Utilizing PHEVs for peak-shaving, loss reduction and voltage profile improvement via v2b mode ", In: 2014 19th Conference on Electrical Power Distribution Networks (EPDC)., 2014, pp. 59-65.
[http://dx.doi.org/10.1109/EPDC.2014.6867499]
[6]
Y. Ma, T. Houghton, A. Cruden, and D. Infield, "Modeling the benefits of vehicle-to-grid technology to a power system", IEEE Trans. Power Syst., vol. 27, no. 2, pp. 1012-1020, 2012.
[http://dx.doi.org/10.1109/TPWRS.2011.2178043]
[7]
W. Zhong, R. Yu, and Y. Zhang, "Fair energy scheduling in vehicle-to-grid networks in the smart grid", In: 2014 IEEE International Conference on Communications (ICC), 2014, pp. 4246-4251.
[http://dx.doi.org/10.1109/ICC.2014.6883987]
[8]
S.A. Amamra, and J. Marco, "Vehicle-to-grid aggregator to support power grid and reduce electric vehicle charging cost", IEEE Access, vol. 7, pp. 178528-178538, 2019.
[http://dx.doi.org/10.1109/ACCESS.2019.2958664]
[9]
J. Yusuf, and S. Ula, Impact of building loads on cost optimization strategy for a plug-in electric vehicle operation.In: 2019 IEEE Transportation Electrification Conference and Expo., ITEC, 2019, pp. 1-5.
[http://dx.doi.org/10.1109/ITEC.2019.8790555]
[10]
H. Turker, and S. Bacha, "Optimal minimization of plug-in electric vehicle charging cost with vehicle-to-home and vehicle-to-grid concepts", IEEE Trans. Vehicular Technol., vol. 67, no. 11, pp. 10281-10292, 2018.
[http://dx.doi.org/10.1109/TVT.2018.2867428]
[11]
K. Ginigeme, and Z. Wang, "Distributed optimal vehicle-to-grid approaches with consideration of battery degradation cost under real-time pricing", IEEE Access, vol. 8, pp. 5225-5235, 2020.
[http://dx.doi.org/10.1109/ACCESS.2019.2963692]
[12]
S. Jaiswal, and M.S. Ballal, Optimal load management of plug-in electric vehicles with demand side management in vehicle to grid application.In: 2017 IEEE Transportation Electrification Conference., ITEC-India, 2017, pp. 1-5.
[http://dx.doi.org/10.1109/ITEC-India.2017.8356942]
[13]
O. Kolawole, and I. Al-Anbagi, Optimizing electric vehicles charging cost for frequency regulation support in a smart grid.In: 2017 IEEE Electrical Power and Energy Conference., EPEC, 2017, pp. 1-6.
[http://dx.doi.org/10.1109/EPEC.2017.8286190]
[14]
L. Igualada, C. Corchero, M. Cruz-Zambrano, and F.J. Heredia, "Optimal energy management for a residential microgrid including a vehicle-to-grid system", IEEE Trans. Smart Grid, vol. 5, no. 4, pp. 2163-2172, 2014.
[http://dx.doi.org/10.1109/TSG.2014.2318836]
[15]
R. Mehta, D. Srinivasan, A. Trivedi, and J. Yang, "Hybrid planning method based on cost-benefit analysis for smart charging of plug-in electric vehicles in distribution systems", IEEE Trans. Smart Grid, vol. 10, no. 1, pp. 523-534, 2019.
[http://dx.doi.org/10.1109/TSG.2017.2746687]
[16]
I.K.A. Aswantara, K.S. Ko, and D.K. Sung, A centralized EV charging scheme based on user satisfaction fairness and cost.In: 2013 Innovative Smart Grid Technologies-Asia., ISGT Asia, 2013, pp. 8-11.
[http://dx.doi.org/10.1109/ISGT-Asia.2013.6698730]
[17]
U.C. Chukwu, S.M. Mahajan, I. Spina, and R. Rizzo, "A nomogram for estimating energy loss in a distribution network due to penetration of V2G", In: 2013 IEEE 4th International Conference on Clean Electrical Power (ICCEP)., 2013, pp. 476-481.
[http://dx.doi.org/10.1109/ICCEP.2013.6586920]
[18]
V. Gupta, "Optimal V2G and G2V operation of electric vehicles using binary hybrid particle swarm optimization and gravitational search algorithm", In: 2017 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE), 2017, pp. 157-160.
[http://dx.doi.org/10.1109/WIECON-ECE.2017.8468892]
[19]
J. Prasomthong, W. Ongsakul, and J. Meyer, "Optimal placement of vehicle-to-grid charging station in distribution system using particle swarm optimization with time varying acceleration coefficient", In: 2014 International Conference and Utility Exhibition on Green Energy for Sustainable Development (ICUE), 2014, pp. 1-8.
[20]
A.G. Bakirtzis, P.N. Biskas, C.E. Zoumas, and V. Petridis, "Optimal power flow by enhanced genetic algorithm", IEEE Trans. Power Syst., vol. 17, no. 2, pp. 229-236, 2002.
[http://dx.doi.org/10.1109/TPWRS.2002.1007886]
[21]
I. Boussaïd, J. Lepagnot, and P. Siarry, "A survey on optimization metaheuristics", Inf. Sci., vol. 237, pp. 82-117, 2013.
[http://dx.doi.org/10.1016/j.ins.2013.02.041]
[22]
T. Dokeroglu, E. Sevinc, T. Kucukyilmaz, and A. Cosar, "A survey on new generation metaheuristic algorithms", Comput. Ind. Eng., vol. 137, 2019.106040
[http://dx.doi.org/10.1016/j.cie.2019.106040]
[23]
K. Hussain, M.N. Mohd Salleh, S. Cheng, and Y. Shi, "Metaheuristic research: A comprehensive survey", Artif. Intell. Rev., vol. 52, no. 4, pp. 2191-2233, 2019.
[http://dx.doi.org/10.1007/s10462-017-9605-z]

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