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A smart sensor network localization for electric grids

  • V. Kavitha
  • P. Balamurugan
Article
  • 41 Downloads

Abstract

Smart grid refers to a sophisticated infrastructure that improvises the efficacy, safety and trustworthiness of an electric power grid. This is done alongside seamless integration of renewable and alternative energy sources by making use of sophisticated communication and automated control technologies. In recent times this WSNs technology has been recognized to be a very a promising one and it also enhances the various aspects of that of the electric power systems. Using the WSN in the smart grid is because of its low cost, low power dissipation, good delivery, good generation and utilization and high flexibility, which make them a vital aspect in the electric power system of the next generation of the smart grid. For this work a communication paradigm that is heterogeneous and based on the needs of the smart gird network has been proposed for supporting the smart grid and their applications. The glow swarm optimization protocol has been proposed and implemented as a data aggregation mechanism that has no energy constraints at the base station. This proposed method has outperformed the actual number of packets that are received at the base station, the number of the priority packets that are received at the base station and the number of such clusters formed.

Keywords

Wireless sensor networks (WSNs) Smart grid Glow swarm optimization (GSO) Clustering 

References

  1. 1.
    Matin, M.A., Islam, M.M.: Overview of wireless sensor network, pp. 3–24. INTECH Open Access Publisher, Croatia (2012)Google Scholar
  2. 2.
    Compte, S.S., Lloret, J., Pineda, M.G., Alarcón, J.F.T.: Power saving and energy optimization techniques for wireless sensor networks. J. Commun. 6(6), 439–459 (2011)Google Scholar
  3. 3.
    Kukreja, S., Dabas, P.: Clustering in WSN using data mining and classification technique. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 5(2), 66–70 (2015)Google Scholar
  4. 4.
    Chhaya, L., Sharma, P., Bhagwatikar, G., Kumar, A.: Wireless sensor network based smart grid communications: cyber attacks, intrusion detection system and topology control. Electronics 6(1), 1–22 (2017)Google Scholar
  5. 5.
    Organisation for Economic Co-operation and Development. (2009). Smart sensor networks: technologies and applications for green growth, pp. 1–48. OECD Publishing, ParisGoogle Scholar
  6. 6.
    Garcia-Hernandez, C.F., García Hernández, J., Meneses Ruiz, J., Rodríguez Rodríguez., Velázquez Hernández, J.C., Pérez Díaz, J.A., González Serna, J.G.: Wireless Sensor Networks within the Smart Grid, pp. 1–9 (2011)Google Scholar
  7. 7.
    Gao, J., Xiao, Y., Liu, J., Liang, W., Chen, C.P.: A survey of communication/networking in smart grids. Future Gener. Comput. Syst. 28(2), 391–404 (2012)CrossRefGoogle Scholar
  8. 8.
    Savvides, A., Srivastava, M., Girod, L., Estrin, D.: Localization in sensor networks. In: Wireless sensor networks, pp. 327–349. Springer, New York (2004)Google Scholar
  9. 9.
    Liu, Y.: Wireless sensor network applications in smart grid: recent trends and challenges. Int. J. Distrib. Sensor Netw. (2012)Google Scholar
  10. 10.
    Bhajantri, L.B.: Cluster based optimization of routing in distributed sensor networks using bayesian networks with tabu search. Int. J. Electron. Telecommun. 60(2), 199–208 (2014)Google Scholar
  11. 11.
    Burunkaya, M., Pars, T.: A smart meter design and implementation using ZigBee based wireless sensor network in smart grid. In: IEEE 4th International Conference on Electrical and Electronic Engineering (ICEEE), pp. 158–162 (2017)Google Scholar
  12. 12.
    Hui, W., Zhitao, G., Tingting, Y., Yue, X.: Top-k query framework in wireless sensor networks for smart grid. China Commun. 11(6), 89–98 (2014)CrossRefGoogle Scholar
  13. 13.
    He, D., Chan, S., Guizani, M.: Cyber security analysis and protection of wireless sensor networks for smart grid monitoring. IEEE Wirel. Commun. pp. 2–7 (2017)Google Scholar
  14. 14.
    Kurt, S., Yildiz, H.U., Yigit, M., Tavli, B., Gungor, V.C.: Packet size optimization in wireless sensor networks for smart grid applications. IEEE Trans. Industr. Electron. 64(3), 2392–2401 (2017)CrossRefGoogle Scholar
  15. 15.
    Wang, Y., Wang, X., Wang, H.: Target detection for wireless sensor networks in smart grid. In: IEEE International Conference on Smart City and Systems Engineering (ICSCSE), pp. 161–164 (2016)Google Scholar
  16. 16.
    Van, D.P., Rimal, B.P., Maier, M.: Fiber optic vs. wireless sensors in energy-efficient integrated FiWi smart grid networks: an energy-delay and TCO comparison. In: IEEE INFOCOM 2016-The 35th Annual IEEE International Conference on Computer Communications, pp. 1–9 (2016)Google Scholar
  17. 17.
    Nguyen, M.T., Nguyen, L.L., Nguyen, T.D.: A practical implementation of wireless sensor network based smart home system for smart grid integration. In International Conference on Advanced Technologies for Communications (ATC), pp. 604–609 (2015)Google Scholar
  18. 18.
    Li, F., He, G., Wang, X.: An improved hybrid time synchronization approach in wireless sensor networks for smart grid application. In: IEEE 17th International Conference on High performance computing and communications (HPCC), 2015 IEEE 7th International Symposium on Cyberspace Safety and Security (CSS), 2015 IEEE 12th International Conferen on Embedded Software and Systems (ICESS), pp. 798–801 (2015)Google Scholar
  19. 19.
    Santos, I.L., Pirmez, L., Delicato, F.C., da Costa Carmo, L.F.R.: Ensuring energy efficiency of power quality applications in smart grids through a framework based on wireless sensor and actuator networks. In: Wireless Communications and Mobile Computing Conference (IWCMC), pp. 763–768 (2015)Google Scholar
  20. 20.
    Kim, K., Bang, H., Jin, S.I.: Efficient data collection for smart grid using wireless sensor networks. In: IEEE 2nd Global Conference on Consumer Electronics (GCCE), pp. 231–232 (2013)Google Scholar
  21. 21.
    Zhang, Y., Zhang, S., Ding, Y.: Research on the influence of sensor network communication in the electromagnetic environment of smart grid. J. Electr. Comput. Eng. 2016, 4 (2016)Google Scholar
  22. 22.
    Wang, P., Hou, H., He, X., Wang, C., Xu, T., Li, Y.: Survey on application of wireless sensor network in smart grid. Procedia Comput. Sci. 52, 1212–1217 (2015)CrossRefGoogle Scholar
  23. 23.
    Zahurul, S., Mariun, N., Grozescu, I.V., Tsuyoshi, H., Mitani, Y., Othman, M.L., et al.: Future strategic plan analysis for integrating distributed renewable generation to smart grid through wireless sensor network: malaysia prospect. Renew. Sustain. Energy Rev. 53, 978–992 (2016)CrossRefGoogle Scholar
  24. 24.
    Faheem, M., Gungor, V.C.: Capacity and spectrum-aware communication framework for wireless sensor network-based smart grid applications. Comput. Stand. Interfaces 53, 48–58 (2017)CrossRefGoogle Scholar
  25. 25.
    Kumar, D., Aseri, T.C., Patel, R.B.: EEHC: energy efficient heterogeneous clustered scheme for wireless sensor networks. Comput. Commun. 32(4), 662–667 (2009)CrossRefGoogle Scholar
  26. 26.
    Karthikeyan, T., Subramani, B.: Hybrid glowworm swarm optimization (HGSO) agent for Qos based routing. Wirel. Netw. 5(6), 2011–2021 (2014)Google Scholar
  27. 27.
    Karegowda, A.G., Prasad, M.: A survey of applications of glowworm swarm optimization algorithm. In: International journal of computer applications (0975–8887). In: International Conference on Computing and Information Technology (IC2IT-2013), pp. 39–42 2013Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Electronics and Communication EngineeringSri Bharathi Engineering College for WomenPudukkottaiIndia
  2. 2.Mount Zion College of Engineering and TechnologyPudukkottaiIndia

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