Integration of 5G Technologies in Smart Grid Communication-A Short Survey

Yaspy Joshva Chandrasekaran -  Department of Electronics and Communication Engineering, Karunya Institute of Technology and Sciences, Coimbatore, India
*Shine Let Gunamony -  Department of Electronics and Communication Engineering, Karunya Institute of Technology and Sciences, Coimbatore, India
Benin Pratap Chandran -  Department of Electrical and Electronics Engineering, Karunya Institute of Technology and Sciences, Coimbatore,, India
Received: 12 Mar 2019; Revised: 19 Sep 2019; Accepted: 5 Oct 2019; Published: 27 Oct 2019; Available online: 30 Oct 2019.
Open Access Copyright (c) 2019 International Journal of Renewable Energy Development
Citation Format:
Cover Image
Article Info
Section: Original Research Article
Language: EN
Full Text:
In Vol 8, No 3 (2019): October 2019
Statistics: 277 137
Abstract
Smart grid is an intelligent power distribution system that employs dual communication between the energy devices and the substation. Dual communication helps to overseer the internet access points, energy meters, and power demand of the entire grid. Deployment of advanced communication and control technologies makes smart grid system efficient for energy availability and low-cost maintenance. Appropriate algorithms are analyzed first for the convenient grid to have proper routing and security with a high-level of power transmission and distribution. Information and Communication Technology plays a significant role in monitoring, demand response, and control of the energy distribution. This paper presents a broad review of communication and network technologies with regard to Internet of Things, Machine to Machine Communication, and Cognitive radio terminologies which comprises 5G technology. Networks suitable for future smart-grid are compared with respect to standard protocols, data rate, throughput, delay, security, and routing. Approaches adopted for the smart-grid system has been commended based on the performance and the parameters observed. ©2019. CBIORE-IJRED. All rights reserved
Keywords
Smart Grid; Information and Communication Technology; Home Area Network; Software Defined Network; Cognitive Radio; Internet of Things; Device-to-Device Communication

Article Metrics:

  1. Aijaz, A., & Aghvami, A. H. (2015). PRMA based Cognitive Machine-to-Machine Communications in Smart Grid Networks. IEEE Transactions on Vehicular Technology, 64(8), 3608–3623. https://doi.org/10.1109/TVT.2014.2359158
  2. Al-Ali, A. R., & Aburukba, R. (2015). Role of Internet of Things in the Smart Grid Technology. Journal of Computer and Communications, 03(05), 229–233. https://doi.org/10.4236/jcc.2015.35029
  3. Al-rubaye, S., Kadhum, E., Ni, Q., & Anpalagan, A. (2017). Industrial Internet of Things Driven by SDN Platform for Smart Grid Resiliency. IEEE Internet of Things Journal, 1–11. https://doi.org/10.1109/JIOT.2017.2734903
  4. Alam, S., Sohail, M. F., Ghauri, S. A., Qureshi, I. M., & Aqdas, N. (2017). Cognitive radio based Smart Grid Communication Network. Renewable and Sustainable Energy Reviews, 72(October 2015), 535–548. https://doi.org/10.1016/j.rser.2017.01.086
  5. Attia, M., Senouci, S. M., Sedjelmaci, H., Aglzim, E. H., & Chrenko, D. (2018). An efficient Intrusion Detection System against cyber-physical attacks in the smart grid. Computers and Electrical Engineering, 68(May), 499–512. https://doi.org/10.1016/j.compeleceng.2018.05.006
  6. Bag, G., Johansson, M., Lednicki, L., Neander, J., Eriksson, L., Bogati, R., … Torsner, J. (2018). Performance Evaluation of IEC 61850-90-5 over a latency optimized 3GPP LTE Network. 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), 1–7.
  7. Bekara, C. (2014). Security issues and challenges for the IoT-based smart grid. Procedia Computer Science, 34, 532–537. https://doi.org/10.1016/j.procs.2014.07.064
  8. Carr, J., Brissette, A., Ragaini, E., & Omati, L. (2017). Managing Smart Grids Using Price Responsive Smart Buildings. Energy Procedia, 134, 21–28. https://doi.org/10.1016/j.egypro.2017.09.593
  9. Dong, X., Lin, H., Tan, R., Iyer, R. K., & Kalbarczyk, Z. (2015). Software-Defined Networking for Smart Grid Resilience. Proceedings of the 1st ACM Workshop on Cyber-Physical System Security - CPSS ’15, 61–68. https://doi.org/10.1145/2732198.2732203
  10. Dorsch, N., Kurtz, F., Girke, F., & Wietfeld, C. (2016). Enhanced Fast Failover for Software-Defined Smart Grid Communication Networks. In 2016 IEEE Global Communications Conference (GLOBECOM) (pp. 1–6). IEEE. https://doi.org/10.1109/GLOCOM.2016.7841813
  11. Emmanuel, M., & Rayudu, R. (2016). Communication technologies for smart grid applications: A survey. Journal of Network and Computer Applications, 74, 133–148. https://doi.org/10.1016/j.jnca.2016.08.012
  12. Erdem, H. E., & Gungor, V. C. (2018). On the lifetime analysis of energy harvesting sensor nodes in smart grid environments. Ad Hoc Networks, 75–76, 98–105. https://doi.org/10.1016/j.adhoc.2018.03.002
  13. Erol-Kantarci, M., & Mouftah, H. T. (2015). Energy-Efficient Information and Communication Infrastructures in the Smart Grid: A Survey on Interactions and Open Issues. IEEE Communications Surveys and Tutorials, 17(1), 179–197. https://doi.org/10.1109/COMST.2014.2341600
  14. Faheem, M., Shah, S. B. H., Butt, R. A., Raza, B., Anwar, M., Ashraf, M. W., … Gungor, V. C. (2018). Smart grid communication and information technologies in the perspective of Industry 4.0: Opportunities and challenges. Computer Science Review, 30, 1–30. https://doi.org/10.1016/j.cosrev.2018.08.001
  15. Feng, F., Peng, F., Yan, B., Lin, S., & Zhang, J. (2017). QoS-Based LTE Downlink Scheduling Algorithm for Smart Grid Communication. In IEEE 9th international conference on communication software and networks (pp. 548–552).
  16. Fonseca, P. C. da R., & Mota, E. S. (2017). A Survey on Fault Management in Software-Defined Networks. IEEE Communications Surveys & Tutorials, 19(4), 2284–2321.
  17. Gozalvez, J. (2016). New 3GPP Standard for IoT [Mobile Radio]. IEEE Vehicular Technology Magazine, 11(1), 14–20. https://doi.org/10.1109/MVT.2015.2512358
  18. Hassebo, A., Obaidat, M., & Ali, M. A. (2018). Commercial 4G LTE Cellular Networks for Supporting Emerging IoT Applications. 2018 Advances in Science and Engineering Technology International Conferences (ASET), 1–6.
  19. Ibdah, D., Kanani, M., Lachtar, N., Allan, N., & Al-Duwairi, B. (2018). On the security of SDN-enabled smartgrid systems. 2017 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2017, 2018–Janua, 1–5. https://doi.org/10.1109/ICECTA.2017.8251983
  20. Jiang, T., Wang, H., Daneshmand, M., & Wu, D. (2017). Cognitive Radio-Based Smart Grid Traffic Scheduling with Binary Exponential Backoff. IEEE Internet of Things Journal, 4(6), 2038–2046. https://doi.org/10.1109/JIOT.2017.2665339
  21. Jumar, R., Maaß, H., & Hagenmeyer, V. (2018). Comparison of lossless compression schemes for high rate electrical grid time series for smart grid monitoring and analysis ☆. Computers and Electrical Engineering, 71(July), 465–476. https://doi.org/10.1016/j.compeleceng.2018.07.008
  22. Kalyani, V. L., & Sharma, D. (2015). IoT: Machine to Machine (M2M), Device to Device (D2D) Internet of Everything (IoE) and Human to Human (H2H): Future of Communication. Journal of Management Engineering and Information Technology, (26), 2394–8124.
  23. Le, T. N., Chin, W. L., & Chen, H. H. (2017). Standardization and Security for Smart Grid Communications Based on Cognitive Radio Technologies - A Comprehensive Survey. IEEE Communications Surveys and Tutorials, 19(1), 423–445. https://doi.org/10.1109/COMST.2016.2613892
  24. Lee, S., Lim, H., Go, W., Park, H., & Shon, T. (2015). Logical architecture of HAN-centric smartgrid model. Proceedings - 2015 International Conference on Platform Technology and Service, PlatCon 2015, 41–42. https://doi.org/10.1109/PlatCon.2015.18
  25. Li, Q., Jiang, H., Tang, Q., Chen, Y., Li, J., & Zhou, J. (2016). Smart Manufacturing Standardization: Reference Model and Standards Framework. OTM Confederated International Conferences" On the Move to Meaningful Internet Systems", 101(April 2017), 16–25.
  26. Luo, X., Yao, Q., Wang, X., & Guan, X. (2018). Observer-based cyber attack detection and isolation in smart grids. International Journal of Electrical Power and Energy Systems, 101(January), 127–138. https://doi.org/10.1016/j.ijepes.2018.02.039
  27. Mahmood, A., Javaid, N., & Razzaq, S. (2015). A review of wireless communications for smart grid. Renewable and Sustainable Energy Reviews, 41, 248–260. https://doi.org/10.1016/j.rser.2014.08.036
  28. Marah, R., & El Hibaoui, A. (2018). Algorithms for Smart Grid management. Sustainable Cities and Society, 38(January), 627–635. https://doi.org/10.1016/j.scs.2018.01.041
  29. Mourshed, M., Robert, S., Ranalli, A., Messervey, T., Reforgiato, D., Contreau, R., … Lennard, Z. (2015). Smart Grid Futures: Perspectives on the Integration of Energy and ICT Services. Energy Procedia, 75, 1132–1137. https://doi.org/10.1016/j.egypro.2015.07.531
  30. Nist, Publication, N. S., & National Institute of Standards and Technology. (2010). NIST Special Publication 1108 NIST Framework and Roadmap for Smart Grid Interoperability Standards. Nist Special Publication, 0, 1–90. https://doi.org/10.6028/NIST.SP.1108r3
  31. Niyato, D., Xiao, L., & Wang, P. (2011). Machine-to-Machine Communications for Home Energy Management System in Smart Grid.
  32. P.,M., F. (2012). Introduction to Smart Grid Security. Smart Grid Applications, Communications and Security, (March), 295–320. https://doi.org/10.1109/ISGWCP.2016.7548265
  33. Palak P. Parikh, Mitalkumar. G. Kanabar, T. S. S. (2010). Opportunities and Challenges of Wireless Communication Technologies for Smart Grid Applications. In In Power and Energy Society General Meeting (pp. 1–7).
  34. Panwar, N., Sharma, S., & Singh, A. K. (2016). A survey on 5G: The next generation of mobile communication. Physical Communication, 18, 64–84. https://doi.org/10.1016/j.phycom.2015.10.006
  35. Ranganathan, R., Qiu, R., Hu, Z., Hou, S., Pazos-Revilla, M., Zheng, G., … Guo, N. (2011). Cognitive radio for smart grid: Theory, algorithms, and security. International Journal of Digital Multimedia Broadcasting, 2011. https://doi.org/10.1155/2011/502087
  36. Rehmani, M. H., Akhtar, F., Davy, A., & Jennings, B. (2018). Achieving Resilience in SDN-Based Smart Grid : A Multi-Armed Bandit Approach. In 2018 4th IEEE Conference on Network Softwarization and Workshops (NetSoft) (pp. 366–371). IEEE. https://doi.org/10.1109/NETSOFT.2018.8459942
  37. Rehmani, M. H., Davy, A., Jennings, B., & Assi, C. (2018a). Software Defined Networks based Smart Grid Communication: A Comprehensive Survey, 1–32. Retrieved from http://arxiv.org/abs/1801.04613
  38. Rehmani, M. H., Davy, A., Jennings, B., & Assi, C. (2018b). Software Defined Networks based Smart Grid Communication: A Comprehensive Survey, 1–32. Retrieved from http://arxiv.org/abs/1801.04613
  39. Shine Let G, Josemin Bala G, B. P. C. (2018). Cooperative Communication in 5G Cognitive Radio Systems. Lambert Academic Publishing.
  40. Singh, S., Saxena, N., Roy, A., & Kim, H. S. (2017). A Survey on 5G Network Technologies from Social Perspective. IETE Technical Review (Institution of Electronics and Telecommunication Engineers, India), 34(1), 30–39. https://doi.org/10.1080/02564602.2016.1141077
  41. Tuna, G., Kogias, D. G., Gungor, V. C., Gezer, C., Taşkın, E., & Ayday, E. (2017). A survey on information security threats and solutions for Machine to Machine (M2M) communications. J. Parallel Distrib. Comput., 109, 142–154. https://doi.org/10.1016/j.jpdc.2017.05.021
  42. Yu, K., Davaasambuu, B., Nguyenand, N. H., Nguyen, Q., Mohammad, A., & Sato, T. (2016). COST-EFFICIENT RESIDENTIAL ENERGY MANAGEMENT SCHEME FOR INFORMATION-CENTRIC NETWORKING BASED HOME NETWORK IN SMART GRID, 8(2), 25–42.
  43. Zhou, Z., Gong, J., He, Y., & Zhang, Y. (2017). Software Defined Machine-to-Machine Communication for Smart Energy Management. IEEE Communications Magazine, 55(October), 52–60. https://doi.org/10.1109/MCOM.2017.1700169

Copyright (c) 2019 International Journal of Renewable Energy Development Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

The Authors submitting a manuscript do so on the understanding that if accepted for publication, copyright of the article shall be assigned to International Journal of Renewable Energy Development and Center of Biomass and Renewable Energy, Department of Chemical Engineering Diponegoro University as publisher of the journal.

Copyright encompasses exclusive rights to reproduce and deliver the article in all form and media, including reprints, photographs, microfilms and any other similar reproductions, as well as translations. The reproduction of any part of this journal, its storage in databases and its transmission by any form or media, such as electronic, electrostatic and mechanical copies, photocopies, recordings, magnetic media, etc. , will be allowed only with a written permission from International Journal of Renewable Energy Development and Center of Biomass and Renewable Energy, Department of Chemical Engineering Diponegoro University.

International Journal of Renewable Energy Development and Center of Biomass and Renewable Energy, Department of Chemical Engineering Diponegoro University, the Editors and the Advisory International Editorial Board make every effort to ensure that no wrong or misleading data, opinions or statements be published in the journal. In any way, the contents of the articles and advertisements published in the International Journal of Renewable Energy Development are sole and exclusive responsibility of their respective authors and advertisers.