Optimization of Energy Distribution with Demand Response Control in 6G Next Generation Smart Grids

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Wireless Internet (WiCON 2023)

Abstract

The transition to an intelligent electrical network that is more respectful to the environment and consumers’ needs requires the adoption of renewable energies. However, and despite the progress made in this area, renewable energies present significant constraints, such as their intermittency. Therefore, the convergence between the worlds of energy and 5G/6G network techniques offers relevant solutions, including the use of Virtual Power Plants, SDN technology coupled with network slicing. As a way to achieve power balancing between power generation and demands, this study offers a unique architecture for a smart grid that makes full use of optimization techniques to rationalize the distribution of energy resources. Performance evaluation shows the optimization of resource consumption.

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References

  1. International Energy Agency IEA. World Energy Outlook, 2021. www.iea.org/weo

  2. Patil, S., Deshmukh, S.R.: Development of control strategy to demonstrate load priority system for demand response program. In: 2019 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE), pp. 1–6 (2019). https://doi.org/10.1109/WIECON-ECE48653.2019.9019950

  3. Zhao, J., Hammad, E., Farraj, A., Kundur, D.: Network-aware QoS routing for smart grids using software defined networks. In: Leon-Garcia, A., et al. (eds.) Smart City \(360^\circ\). SmartCity 360 SmartCity 360 2016 2015. LNICS, Social Informatics and Telecommunications Engineering, vol. 166, pp. 384–394. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-33681-7_32

  4. Dorsch, N., Kurtz, F., Girke, F., Wietfeld, C.: Enhanced fast failover for software-defined smart grid communication networks. In: IEEE Global Communications Conference (GLOBECOM), pp. 1–6, December 2016

    Google Scholar 

  5. Ghosh, U., Chatterjee, P., Shetty, S.: A security framework for SDNEnabled smart power grids. In: IEEE 37th International Conference on Distributed Computing Systems Workshops (ICDCSW), pp. 113–118, June 2017

    Google Scholar 

  6. Lin, H., et al.: Self-healing attack-resilient PMU network for power system operation. IEEE Trans. Smart Grid 9(3), 1551–1565 (2018)

    Article  Google Scholar 

  7. Mouawad, N., Naja, R., Tohmé, S.: Inter-slice handover management in a V2X slicing environment using bargaining games. Wirel. Netw. 26(5), 3883–3903 (2020)

    Article  Google Scholar 

  8. Bessem, S., Marco, G., Vasilis, F., Dirk von, H., Paul, A.: SDN for 5G mobile networks: norma perspective. In: Proceedings of the 11th International Conference on Cognitive Radio Oriented Wireless Networks, CROWNCOM, Grenoble, France (2016)

    Google Scholar 

  9. Ersue, M.: ETSI NFV management and orchestration-an overview. In: Proceedings of 88th IETF Meeting (2013)

    Google Scholar 

  10. Elayoubi, S., Maternia, M.: 5G-PPP use cases and performance evaluation modeling. 5G PPP white paper (2016)

    Google Scholar 

  11. Campolo, C., Molinaro, A., Iera, A., Menichella, F.: 5G network slicing for vehicle-to-everything services. IEEE Wirel. Commun. 24(6), 38–45 (2017)

    Article  Google Scholar 

  12. Campolo, C., Molinaro, A., Iera, A., Fontes, R.R., Rothenberg, C.E.: Towards 5G network slicing for the v2x ecosystem. In: Proceedings of the 4th IEEE Conference on Network Softwarization and Workshops (NetSoft), pp. 400–405 (2018)

    Google Scholar 

  13. Seremet, I., Causevic, S.: Benefits of using 5G network slicing to implement vehicle-to-everything (V2X) technology. In: Proceedings of the 18th International Symposium INFOTEHJAHORINA (INFOTEH), pp. 1–6 (2019)

    Google Scholar 

  14. Khan, H., Luoto, P., Bennis, M., Latva-aho, M.: On the application of network slicing for 5G-V2X. In: European Wireless 2018; 24th European Wireless Conference, VDE, pp. 1–6 (2018)

    Google Scholar 

  15. ADEME. Rapport sur L’effacement de consommation électrique en France. Evaluation du potentiel d’effacement par modulation de process dans l’industrie et le tertiaire en France métropolitaine, 2017

    Google Scholar 

  16. Strielkowski, W., Dvořák, M., Rovný, P., Tarkhanova, E.: 5G wireless networks in the future renewable energy systems. Front. Energy Res. 9 (2021). https://doi.org/10.3389/fenrg.2021.714803

  17. Chekired, D.A., Khoukhi, L., Mouftah, H.T.: Decentralized cloud-SDN architecture in smart grid: a dynamic pricing model. IEEE Trans. Ind. Inf. 14(3), 1220–1231 (2018)

    Article  Google Scholar 

  18. Nafi, N.S., Ahmed, K., Datta, M., Gregory, M.A.: A novel software defined wireless sensor network based grid to vehicle load management system. In: 10th International Conference on Signal Processing and Communication Systems (ICSPCS), pp. 1–6, December 2016

    Google Scholar 

  19. Olatomiwa, L., Blanchard, R., Mekhilef, S., Akinyele, D.: Hybrid Renewable Energy Supply for Rural Healthcare Facilities: An Approach to Quality Healthcare Delivery, Loughborough University. Journal contribution (2018). https://hdl.handle.net/2134/35194

  20. Melhem, F.: Optimization methods and energy management in smart grids, Thesis, Université Bourgogne Franche-Comté, 2018

    Google Scholar 

  21. Arango, J., Rajan Velayutha, H., Rohde, A., Denhof, D., Freitag, M.: Design and simulation of a control algorithm for peakload shaving using vehicle to grid technology, Controller design for vehicle to grid technology (2019). https://doi.org/10.1007/s424520190999x

  22. Ullah, K., Hafeez, G., Khan, I., Jan, S., Javaid, N.: A multi-objective energy optimization in smart grid with high penetration of renewable energy sources

    Google Scholar 

  23. Wind turbine parameters. https://www.windpowercn.com/new-15kw-wind-turbine.asp

  24. Solar systems parameters. https://kenbrooksolar.com/system/25kw-solar-system-price#:~:text=About%2020kW%20Solar%20System,on%20average%20throughout%20the%20year

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Correspondence to Rola Naja .

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The authors have no relevant financial or non-financial interests to disclose.

Authors’ Contributions

All authors contributed to the study conception and design. Material preparation was performed by Asma Tannous. The manuscript was written by Rola Naja and all authors read and approved the final paper version.

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The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

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The datasets generated during and/or analysed during the current study are not publicly available due to confidential reasons but are available from the corresponding author on reasonable request.

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Naja, R., Tannous, A., Mouawad, N., Moubayed, N. (2024). Optimization of Energy Distribution with Demand Response Control in 6G Next Generation Smart Grids. In: Maglaras, L.A., Douligeris, C. (eds) Wireless Internet. WiCON 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 527. Springer, Cham. https://doi.org/10.1007/978-3-031-58053-6_10

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  • DOI: https://doi.org/10.1007/978-3-031-58053-6_10

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  • Online ISBN: 978-3-031-58053-6

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