Skip to main content
Log in

Reduction of control signal overhead for electric vehicle charging operation in smart grid system

  • Regular Paper
  • Published:
International Journal of Precision Engineering and Manufacturing-Green Technology Aims and scope Submit manuscript

Abstract

Smart grid systems have been proposed to replace the conventional power distribution system in order to accommodate future market penetration of electric vehicles (EVs). Nevertheless, there are many factors to consider when large numbers of EVs require simultaneous charging in the smart grid. Among various optimization schemes, the most updated schemes proposed charging with coordination to optimize EV charging performance. In this case, huge amount of control signals are involved in the coordinated charging, therefore the charging performance is retarded. In this paper, a new threshold-based charging operation with historical average data of the EV charging system to improve the EV charging performance is proposed by minimizing control signal overhead, instead of maximum power delivery to all EVs. The moving average of historical data for BSOC levels of the EVs can properly approximate the charging profile of the EVs over time thus enabling the development of an optimization algorithm based on the threshold method. Up to 33% of the reduction in the control signal overhead is achieved with slight trade off in the power delivery to the EVs.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Herrmann, C., Schmidt, C., Kurle, D., Blume, S., and Thiede, S., “Sustainability in Manufacturing and Factories of the Future,” Int. J. Precis. Eng. Manuf.-Green Tech., Vol. 1, No. 4, pp. 283–292, 2014.

    Article  Google Scholar 

  2. Chen, Y.-C., Chu, C. N., Sun, H.-M., Chen, R.-S., Chen, L.-C., et al., “Application of Green Collaboration Operation on Network Industry,” Int. J. Precis. Eng. Manuf.-Green Tech., Vol. 2, No. 1, pp. 73–83, 2015.

    Article  Google Scholar 

  3. Kwon, O. and Yoon, Y.-J., “Optimizing Present Power Distribution System and Novel Renewable Energy Sources for Tamil Nadu in India Using Homer,” Int. J. Precis. Eng. Manuf., Vol. 15, No. 8, pp. 1695–1701, 2014.

    Article  Google Scholar 

  4. Bhandari, B., Ahn, S.-H., and Ahn, T.-B., “Optimization of Hybrid Renewable Energy Power System for Remote Installations: Case Studies for Mountain and Island,” Int. J. Precis. Eng. Manuf., Vol. 17, No. 6, pp. 815–822, 2016.

    Article  Google Scholar 

  5. Choi, H. J., Han, G. D., Min, J. Y., Bae, K., and Shim, J. H., “Economic Feasibility of a PV System for Grid-Connected Semiconductor Facilities in South Korea,” Int. J. Precis. Eng. Manuf., Vol. 14, No. 11, pp. 2033–2041, 2013.

    Article  Google Scholar 

  6. Sortomme, E., Hindi, M. M., MacPherson, S. J., and Venkata, S., “Coordinated Charging of Plug-in Hybrid Electric Vehicles to Minimize Distribution System Losses,” IEEE Transactions on Smart Grid, Vol. 2, No. 1, pp. 198–205, 2011.

    Article  Google Scholar 

  7. Acha, S., Green, T. C., and Shah, N., “Effects of Optimised Plug-in Hybrid Vehicle Charging Strategies on Electric Distribution Network Losses,” Proc. of Transmission and Distribution Conference and Exposition, pp. 1–6, 2010.

    Google Scholar 

  8. Sundstrom, O. and Binding, C., “Flexible Charging Optimization for Electric Vehicles Considering Distribution Grid Constraints,” IEEE Transactions on Smart Grid, Vol. 3, No. 1, pp. 26–37, 2012.

    Article  Google Scholar 

  9. Masoum, A. S., Deilami, S., Moses, P., Masoum, M., and 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,” Proc. of IET Generation, Transmission and Distribution, Vol. 5, No. 8, pp. 877–888, 2011.

    Article  Google Scholar 

  10. Clement-Nyns, K., Haesen, E., and Driesen, J., “The Impact of Charging Plug-in Hybrid Electric Vehicles on a Residential Distribution Grid,” IEEE Transactions on Power Systems, Vol. 25, No. 1, pp. 371–380, 2010.

    Article  Google Scholar 

  11. Richardson, P., Flynn, D., and Keane, A., “Optimal Charging of Electric Vehicles in Low-Voltage Distribution Systems,” IEEE Transactions on Power Systems, Vol. 27, No. 1, pp. 268–279, 2012.

    Article  Google Scholar 

  12. Zhang, P., Qian, K., Zhou, C., Stewart, B. G., and Hepburn, D. M., “A Methodology for Optimization of Power Systems Demand due to Electric Vehicle Charging Load,” IEEE Transactions on Power Systems, Vol. 27, No. 3, pp. 1628–1636, 2012.

    Article  Google Scholar 

  13. Gesbert, D. and Alouini, M.-S., “How Much Feedback is Multi-User Diversity Really Worth?” Proc. of 2004 IEEE International Conference on Communications, pp. 234–238, 2004.

    Google Scholar 

  14. Hayes, J. G. and Davis, K., “Simplified Electric Vehicle Powertrain Model for Range and Energy Consumption Based on EPA Coast-Down Parameters and Test Validation by Argonne National Lab Data on the Nissan Leaf,” Proc. of Transportation Electrification Conference and Expo, pp. 1–6, 2014.

    Google Scholar 

  15. Bellabdaoui, A. and Teghem, J., “A Mixed-Integer Linear Programming Model for the Continuous Casting Planning,” International Journal of Production Economics, Vol. 104, No. 2, pp. 260–270, 2006.

    Article  Google Scholar 

  16. Tesla Motors, “Model Specifications,” http://www.teslamotors.com/models/specs (Accessed 13 MAR 2017)

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yong-Jin Yoon.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kwon, O., Kim, P. & Yoon, YJ. Reduction of control signal overhead for electric vehicle charging operation in smart grid system. Int. J. of Precis. Eng. and Manuf.-Green Tech. 4, 191–197 (2017). https://doi.org/10.1007/s40684-017-0024-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40684-017-0024-z

Keywords

Navigation