Technical and Economic Management of Energy Distribution to Reduce Charging Costs and Reduction

Subject Areas : Renewable energy

Meysam Saeedirad ¹ (Engineering Department- Islamic Azad University Lorestan Branch, Lorestan, Iran)
Esmaeel Rokrok ² (Engineering Department- Lorestan University, Lorestan, Iran)
Mahmoud Joorabian ³ (Engineering Department- Shahid Chamran University of Ahvaz, Ahvaz, Iran)

Received: 2021-11-23 Accepted : 2022-02-26 Published : 2023-08-23

Keywords: electric car charge management, home energy management, distribution network operation, energy electrical,

Abstract :

Proper management of electrical energy in the electricity distribution network is one of the main issues of network operation that high impact of reducing operating costs, reducing network losses, increasing the quality of updates, increasing customer satisfaction and etc. can have achieving these goals is possible when the elements of the distribution network act in coordination and awareness of each other. This paper considers this awareness among home subscribers, car charging parking lots and the network operating company has been taken and its benefits have been explored. A two-stage model of energy management in the distribution network is presented. The first stage is related to home energy management in the presence or absence of a load response program, taking into account tastes. Subscribers' personalization is done to bring the results closer to the real world then based on the information sent from these subscribers and determining the residential load profile of the network, electric car charging parking operators to manage according to their limitations electric vehicle to improve both charging costs and network operation parameters. Unlike traditional charging methods, in this method does not require a full charge of car batteries and only the final limit of the battery charge level in terms of energy required for drivers' future trips will be determined, and charging operations will be performed using the discrete charge rate. The results of a review of various case studies applied to a 37-bus distribution network shows that the proposed method has a high capability. In providing customer satisfaction, improving network operation parameters and reducing charging costs and meeting the needs of car drivers will had. This method can pave the way for expanding the level of vehicle penetration in distribution networks and the benefits of the load response program and smart charging maximizes productivity.

References:

[1]   Q. Wang, X. Liu, J. Du, F. Kong, "Smart charging for electric vehicles: A survey from the algorithmic perspective", IEEE Communications Surveys, Tutorials, vol. 18, no. 2, pp. 1500-1517, Jan. 2016 (doi: 10.1109/COMST.­2016­.25­18628).

[2]   I. Rahman, P.M. Vasant, B.S.M. Singh, M. Abdullah-Al-Wadud, N. Adnan, "Review of recent trends in optimization techniques for plug-in hybrid, and electric vehicle charging infrastructures", Renewable and Sustainable Energy Reviews, vol. 58, pp. 1039-1047, May 2016 (doi: 10.1016/j.rser.2015.12.353).

[3]   K.L. López, C. Gagné, M.A. Gardner, "Demand-side management using deep learning for smart charging of electric vehicles", IEEE Trans. on Smart Grid, vol. 10, no. 3, pp. 2683-2691, May 2019 (doi: 10.1109/TS­G.20­18.2808247).

[4]   F. Tuchnitz, N. Ebell, J. Schlund, M. Pruckner "Development and evaluation of a smart charging strategy for an EV fleet based on reinforcement learning", Applied Energy, vol. 285, Article Number: 116382, March 2021 (doi: 10.1016/j.apenergy.2020.116382).

[5]   S. Grammatico, "Fast convergence in electric vehicle smart charging", Intelligent Integrated Energy Systems, Springer, pp. 123-139, 2019 (doi: 10.1007/978-3-030-00057-8_6).

[6]   A. Ensslen, P. Ringler, L. Dörr, P. Jochem, F. Zimmermann, W. Fichtner, "Incentivizing smart charging: Modeling charging tariffs for electric vehicles in German and French electricity markets", Energy Research and Social Science, vol. 42, pp. 112-126, Aug. 2018 (doi: 10.1016/j.erss.2018.02.013).

[7]   S. Sachan, N. Adnan, "Stochastic charging of electric vehicles in smart power distribution grids", Sustainable Cities and Society, vol. 40, pp. 91-100, July 2018 (doi: 10.1016/j.scs.2018.03.031).

[8]   L. Jian, Z. Yongqiang, K. Hyoungmi, "The potential and economics of EV smart charging: A case study in Shanghai", Energy Policy, vol. 119, pp. 206-214, 2018 (doi: 10.1016/j.enpol.2018.04.037).

[9]   M.M. Hussain, M.S. Alam, M.S. Beg, H. Malik, "A risk averse business model for smart charging of electric vehicles", Proceedings of ICSSIC, pp. 749-759, Springer Singapore, Jan. 2018 (doi: 10.1007/978-981-10-5828-8_71).

[10] C.M. Affonso, M. Kezunovic, "Technical and economic impact of PV-BESS charging station on transformer life: A case study", IEEE Trans.con Smart Grid, vol. 10, no. 4, pp. 4683-4692, July 2019 (doi: 10.1­109/TSG.2018.2866938).

[11] J.M. Clairand, J. Rodríguez-García, C. Álvarez-Bel, "Smart charging for electric vehicle aggregators consid­e­ri­ng users’ preferences", IEEE Access, vol. 6, pp. 54624-54635, Oct. 2018 (do: 10.1109/ACCESS.­201­8.2­­872­7­2­5).

[12] S. Hardman, A. Jenn, G. Tal, J. Axsen, G. Beard, N. Daina, E. Figenbaum, N. Jakobsson, P. Jochem, N. Kinnear, P. Plötz, J. Pontes, N. Refa, F. Sprei, T. Turrentine, B. Witkamp, "A review of consumer preferences of and interactions with electric vehicle charging infrastructure", Transportation Research Part D: Transport and Environment, vol. 62, pp. 508-523, July 2018 (doi: 10.1109/ACCESS.2018.2872725).

[13] E. Kamal, L. Adouane, "Intelligent energy management strategy based on artificial neural fuzzy for hybrid vehicle", IEEE Trans. on Intelligent Vehicles, vol. 3, no. 1, pp. 112-125, March 2018 (doi: 10.1109/T­IV.2­0­17.­2788185).

[14] E. Kamal, L. Adouane, "Hierarchical energy optimization strategy and its integrated reliable battery fault management for hybrid hydraulic-electric vehicle", IEEE Trans. on Vehicular Technology, vol. 67, no. 5, pp. 3740-3754, May 2018 (doi: 10.1109/TVT.2018.2805353).

[15] X. Qi, G. Wu, K. Boriboonsomsin, M.J. Barth, "Development and evaluation of an evolutionary algorithm-based online energy management system for plug-in hybrid electric vehicles", IEEE Trans. on Intelligent Transportation Systems, vol. 18, no. 8, pp. 2181-2191, Aug. 2017 (doi: 10.1109/TITS.2016.2633542).

[16] L. Guo, B. Gao, Y. Gao, H. Chen, "Optimal energy management for HEVs in eco-driving applications using bi-level MPC", IEEE Trans. on Intelligent Transportation Systems, vol. 18, no. 8, pp. 2153-2162, Aug. 2017 (doi: 10.1109/TITS.2016.2634019).

[17] L. Qiu, L. Qian, H. Zomorodi, P. Pisu, "Global optimal energy management control strategies for connected four-wheel-drive hybrid electric vehicles", IET Intelligent Transport Systems, vol. 11, no. 5, pp. 264-272, June 2017 (doi: 10.1049/iet-its.2016.0197).

[18] G. Binetti, A. Davoudi, D. Naso, B. Turchiano, F.L. Lewis, "Scalable real-time electric vehicles charging with discrete charging rates," IEEE Trans. on Smart Grid, vol. 6, no. 5, pp. 2211-2220, Sept. 2015 (doi: 10.1109/TS­G.2015.2396772).

[19] H. Eskandari, M.R. Moradian, "Direct torque compound control of induction motors to increase the battery operating life in electric vehicles", Journal of Intelligent Procedures in Electrical Technology, vol. 11, no. 42, pp.1-13, Sept. 2020 (dor: 20.1001.1.23223871.1399.11.42.1.2, 2020).

[20] M.A. Hormozi, B. Bahmani-Firoozi, "Bi-level energy management optimization in multi-area smart grids", Journal of Intelligent Procedures in Electrical Technology, vol. 11, no. 42, pp. 29-40, Sept. 2020 (dor: 20.1001.1.232­23871.1399 .11.42.3.4) (in Persian).

[21] V. Aravinthan, W. Jewell, "Controlled electric vehicle charging for mitigating impacts on distribution assets," IEEE Trans. on Smart Grid, vol. 6, no. 2, pp. 999-1009, Sept. 2015 (doi: 10.1109/TSG.­2015.2­389­875).

[22] N. Chen, C.W. Tan, T.Q. Quek, "Electric vehicle charging in smart grid: Optimality and valley-filling algo­ri­thms," IEEE Journal of Selected Topics in Signal Processing, vol. 8, no. 6, pp. 1073-1083, Dec. 2014 (doi: 10.1109/JSTSP.2014.2334275).

[23] D. Singh, R.K. Misra, D. Singh, " Effect of load models in distributed generation planning", IEEE Trans. on Power Systems, vol. 22, no. 4, pp. 2204-2212, Nov. 2007 (doi: 10.1109/TPWRS.2007.907582).

[24] M.L. Crow, "Electric vehicle scheduling considering co-optimized customer and system objectives", IEEE Trans. on Sustainable Energy, vol. 9, no. 1, pp. 410-419, Jan. 2018 (doi: 10.1109/TSTE.2017.2737146).

[25] A. Safdarian, M. Fotuhi-Firuzabad, M. Lehtonen, "Benefits of demand response on operation of distribution networks: A case study," IEEE Systems Journal, vol. 10, no. 1, pp. 189-197, March 2016 (doi: 10.1109/JS­YST.2­013.2297792).

[26] S. Paudyal, C.A. Cañizares, K. Bhattacharya, "Optimal operation of industrial energy hubs in smart grids", IEEE Trans. on Smart Grid, vol. 6, no. 2, pp. 684-694, March 2015 (doi: 10.1109/COMST.2016.2518628).

[27] S.J. Ramchunder, D.D. Voutchkova, "Flowpath influence on stream acid events in tropical urban streams in Singapore", www.lta.gov.sg/content/ltagov/en/who_we_are/statistics_and_publications/statistics.html (doi: 10­.­­1­0­02­/hyp.14467).

[28] M. Saeedirad, E. Rokrok, M. Joorabian, "A smart discrete charging method for optimum electric vehicles integration in the distribution system in presence of demand response program," Journal of Energy Storage, Article Number: 103577, Nov. 2021 (doi: 10.1016/j.est.2021.103577).