access icon free Optimal charging of plug-in electric vehicles observing power grid constraints

Plug-in electric vehicles (PEVs) impose considerable loads to existing power grids, and consequently, they can challenge power quality and reliability of power systems if their charging is not coordinated. To use existing distribution systems for PEV charging without upgrading them, coordinated charging is inevitable. In this study, an optimal PEV dynamic charging method is proposed observing power grid thermal ratings and voltage quality. The problem is formulated as a standard non-linear programming with minimising energy losses over the charging span as objective function subject to PEVs and power system security constraints. Node voltages and power losses are explicitly and precisely formulated in the proposed method. Coordinated charging span of PEVs starts from evening, when PEV owners arrive home, to the next day morning, when the owners need their car charged and ready to use. The IEEE 31-bus distribution system in highly stressed conditions is used to evaluate the performance of the proposed method in the worst voltage status. According to obtained results, discussed in detail, voltage quality constraints are more restricting than equipment thermal rating in PEV optimal charging because of mostly radial structure of distribution systems. The results confirm the efficiency of the proposed method.

Inspec keywords: power distribution reliability; power supply quality; battery powered vehicles; nonlinear programming; power system security; power grids

Other keywords: plug-in electric vehicles; power grid constraint; node voltages; power grid thermal ratings; voltage quality; optimal PEV dynamic charging method; voltage quality constraint; power system reliability; distribution system radial structure; coordinated charging span; standard nonlinear programming; energy loss minimisation; power system security constraint; IEEE 31-bus distribution system; power quality; equipment thermal rating; power loss; highly-stressed condition

Subjects: Distribution networks; Reliability; Power supply quality and harmonics; Transportation; Optimisation techniques

References

    1. 1)
    2. 2)
    3. 3)
    4. 4)
    5. 5)
    6. 6)
    7. 7)
    8. 8)
    9. 9)
    10. 10)
    11. 11)
    12. 12)
    13. 13)
    14. 14)
    15. 15)
    16. 16)
    17. 17)
      • 9. Jin, C., Tang, J., Ghosh, P.: ‘Optimizing electric vehicle charging: a customer's perspective’, IEEE Trans. Veh. Technol., 2013, 62, (7), pp. 29192927 (doi: 10.1109/TVT.2013.2251023).
    18. 18)
      • 15. Clement-Nyns, K., Haesen, E., Driesen, J.: ‘The impact of charging plug-in hybrid electric vehicles on a residential distribution grid’, IEEE Trans. Power Syst., 2010, 25, (1), pp. 371380 (doi: 10.1109/TPWRS.2009.2036481).
    19. 19)
      • 19. Ou, T.C.: ‘Ground fault current analysis with a direct building algorithm for microgrid distribution’, Int. J. Electr. Power Energy Syst., 2013, 53, pp. 867875 (doi: 10.1016/j.ijepes.2013.06.005).
    20. 20)
      • 10. Chenrui, J., Jian, T., Ghosh, P.: ‘Optimizing electric vehicle charging with energy storage in the electricity market’, IEEE Trans. Smart Grid, 2013, 4, (1), pp. 311320 (doi: 10.1109/TSG.2012.2218834).
    21. 21)
      • 2. Linni, J., Honghong, X., Guoqing, X., Xinyu, Z., Dongfang, Z., Shao, Z.Y.: ‘Regulated charging of plug-in hybrid electric vehicles for minimizing load variance in household smart microgrid’, IEEE Trans. Ind. Electron., 2013, 60, (8), pp. 32183226 (doi: 10.1109/TIE.2012.2198037).
    22. 22)
      • 18. Lin, W.M., Ou, T.C.: ‘Unbalanced distribution network fault analysis with hybrid compensation’, IET Gener. Transm. Distrib., 2011, 5, (1), pp. 92100 (doi: 10.1049/iet-gtd.2008.0627).
    23. 23)
      • 22. Rosenthal, R.E.: ‘General algebraic modeling system (GAMS) user guide’ (GAMS Development Corporation, Washington, DC, USA, 2013), www.gams.com.
    24. 24)
      • 8. Vandael, S., Claessens, B., Hommelberg, M., Holvoet, T., Deconinck, G.: ‘A scalable three-step approach for demand side management of plug-in hybrid vehicles’, IEEE Trans. Smart Grid, 2013, 4, (2), pp. 720728 (doi: 10.1109/TSG.2012.2213847).
    25. 25)
      • 16. Luenberger, D.G., Ye, Y.: ‘Linear and nonlinear programming’ (Springer, Stanford, CA, USA, 2008, 3rd edn.).
    26. 26)
      • 23. Zimmerman, R.D., Murillo-Sanchez, C.E.: ‘MatPower software package user guide’ (University of Cornell, USA, 2013), http://www.pserc.cornell.edu/matpower.
    27. 27)
      • 7. Zhongjing, M., Callaway, D.S., Hiskens, I.A.: ‘Decentralized charging control of large populations of plug-in electric vehicles’, IEEE Trans. Control Syst. Technol., 2013, 21, (1), pp. 6778 (doi: 10.1109/TCST.2011.2174059).
    28. 28)
      • 5. Kejun, Q., Chengke, Z., Allan, M., Yue, Y.: ‘Modeling of load demand due to EV battery charging in distribution systems’, IEEE Trans. Power Syst., 2011, 26, (2), pp. 802810 (doi: 10.1109/TPWRS.2010.2057456).
    29. 29)
      • 14. Masoum, A.S., Deilami, S., Moses, P.S., Masoum, M.A.S., Abu-Siada, A.: ‘Smart load management of plug-in electric vehicles in distribution and residential networks with charging stations for peak shaving and loss minimisation considering voltage regulation’, IET Gener. Transm. Distrib., 2011, 5, (8), pp. 877888 (doi: 10.1049/iet-gtd.2010.0574).
    30. 30)
      • 1. Zhipeng, L., Fushuan, W., Ledwich, G.: ‘Optimal planning of electric-vehicle charging stations in distribution systems’, IEEE Trans. Power Deliv., 2013, 28, (1), pp. 102110.
    31. 31)
      • 13. Richardson, P., Flynn, D., Keane, A.: ‘Optimal charging of electric vehicles in low-voltage distribution systems’, IEEE Trans. Power Syst., 2012, 27, (1), pp. 268279 (doi: 10.1109/TPWRS.2011.2158247).
    32. 32)
      • 11. Rotering, N., Ilic, M.: ‘Optimal charge control of plug-in hybrid electric vehicles in deregulated electricity markets’, IEEE Trans. Power Syst., 2011, 26, (3), pp. 10211029 (doi: 10.1109/TPWRS.2010.2086083).
    33. 33)
      • 12. Zhong, F.: ‘Distributed charging of PHEVs in a smart grid’. IEEE Int. Conf. on Smart Grid Communications (SmartGridComm), 2011, pp. 255260.
    34. 34)
      • 17. Juanuwattanakul, P., Masoum, M.A.S.: ‘Increasing distributed generation penetration in multiphase distribution networks considering grid losses, maximum loading factor and bus voltage limits’, IET Gener. Transm. Distrib., 2012, 6, (12), pp. 12621271 (doi: 10.1049/iet-gtd.2011.0841).
    35. 35)
      • 6. Geng, B., Mills, J.K., Sun, D.: ‘Two-stage charging strategy for plug-in electric vehicles at the residential transformer level’, IEEE Trans. Smart Grid, 2013, 4, (3), pp. 14421452 (doi: 10.1109/TSG.2013.2246198).
    36. 36)
      • 4. Gan, L., Topcu, U., Low, S.: ‘Optimal decentralized protocol for electric vehicle charging’, IEEE Trans. Power Syst., 2013, 28, (2), pp. 940951.
    37. 37)
      • 21. Fuchs, E., Masoum, M.A.S.: ‘Power quality in power systems and electrical machines’ (Academic Press, Burlington, 2008).
    38. 38)
      • 3. Sortomme, E., El-Sharkawi, M.A.: ‘Optimal scheduling of vehicle-to-grid energy and ancillary services’, IEEE Trans. Smart Grid, 2012, 3, (1), pp. 351359 (doi: 10.1109/TSG.2011.2164099).
    39. 39)
      • 20. Ou, T.C.: ‘A novel unsymmetrical faults analysis for microgrid distribution systems’, Int. J. Electr. Power Energy Syst., 2012, 43, (1), pp. 10171024 (doi: 10.1016/j.ijepes.2012.05.012).
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