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Energy management of WSN-based charge measurement system of ultra high-voltage direct-current transmission line

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Abstract

With the construction of ultra-high-voltage direct current (UHVDC) transmission lines, the complex electromagnetic environment around the lines has been a widespread concern. The ZigBee-based field measurement system is widely used in ground space charge density measurements of HVDC transmission projects. In actual use, the power consumption of the space charge density measurement system is a key limitation of the device performance.Research on low-power and energy-management strategies of this measurement system can improve the device lifetimes. This capability is very important for improving monitoring efficiency of the surrounding electromagnetic environment of HVDC transmission projects.

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References

  1. Antolin, D., Medrano, N., & Calvo. B. (2016). Reliable lifespan evaluation of a remote environment monitoring system based on wireless sensor networks and global system for mobile communications. Journal of Sensors.

  2. Abdul-Salaam, G., Abdullah, A. H., Anisi, M. H., Gani, A., & Alelaiwi, A. (2016). A comparative analysis of energy conservation approaches in hybrid wireless sensor networks data collection protocols. Telecommunication Systems, 61(1), 159–179.

    Article  Google Scholar 

  3. Egarter, D., Monacchi, A., Khatib, T., & Elmenreich, W. (2016). Integration of legacy appliances into home energy management systems. Journal of Ambient Intelligence and Humanized Computing, 7(2), 171–185.

    Article  Google Scholar 

  4. Anisi, M. H., Abdul-Salaam, G., & Abdullah, A. H. (2015). A survey of wireless sensor network approaches and their energy consumption for monitoring farm fields in precision agriculture. Precision Agriculture, 16(2), 216–238.

    Article  Google Scholar 

  5. Shahzad, G., Yang, H., Ahmad, A. W., & Lee, C. (2016). Energy-efficient intelligent street lighting system using traffic-adaptive control. IEEE Sensors Journal, 16(13), 5397–5405.

    Article  Google Scholar 

  6. Anisi, M. H., Abdul-Salaam, G., Idris, M. Y. I., Wahab, A. W. A., & Ahmedy, I. (2015). Energy harvesting and battery power based routing in wireless sensor networks. Wireless Networks 1–18.

  7. Srbinovski, B., Magno, M., Edwards-Murphy, F., Pakrashi, V., & Popovici, E. (2016). An energy aware adaptive sampling algorithm for energy harvesting WSN with energy hungry sensors. Sensors, 16(4), 448.

    Article  Google Scholar 

  8. Chandrakasan, A., Amirtharajah, R., & Cho, S. H. (1999). Design considerations for distributed microsensor systems. Custom Integrated Circuits 279–286.

  9. Srie, V. J. E., Ganeshkumar, P., & Vasantha, S. G. (2013). A survey on algorithms for cluster head selection in WSN. International Journal of Advanced Research in Computer Engineering & Technology, 2(5), 2278.

    Google Scholar 

  10. Abhishek, C., & Sumedha, S. (2014). Minimization of average energy consumption to prolong lifetime of wireless sensor network. In IEEE Global conference on wireless computing and networking.

  11. Amrit, A. R., Shikha, N., & Sanjay, P. (2014). Achieving energy efficiency and increasing network life in wireless sensor networks. In IEEE International advance computing conference 171–175.

  12. Kumar, V., Jain, S., & Tiwari, S. (2011). Energy efficient clustering algorithms in wireless sensor networks: A survey. International Journal of Computer Science Issues, 8(5), 259–268.

    Google Scholar 

  13. Ljiljana, S., Stevan, M. B., & Kevin, W. S. (2008). Partner choice and power allocation for energy efficient cooperation in wireless sensor networks. ICC, 2008, 4255–4260.

    Google Scholar 

  14. Bruno, B., Francky, C., & Denis, C. (2008). Energy efficiency of the IEEE 802.15.4 Standard in dense wireless microsensor networks: Modeling and improvement perspectives. Europe: Springer.

  15. Wang, Q., & Yang, W. (2007). Energy consumption model for power management in wireless sensor networks (pp. 142–151). San Diego: IEEE Press.

    Google Scholar 

  16. Wang, C., Shih, J., & Pan, B. (2014). A network lifetime enhancement method for sink relocation and its analysis in wireless sensor networks. IEEE Sensors Journal, 14(6), 1932–1942.

    Article  Google Scholar 

  17. Wang, Q., Hempstead, M., & Yang, W. (2006). A realistic power consumption model for wireless sensor network devices. IEEE Secon, 2006(1), 286–295.

    Google Scholar 

  18. Cigdem, E., Merve, S. V., & Cagri, G. (2014). Lifetime analysis of wireless sensor nodes in different smart grid environments. Wireless Networks, 20, 2053–2062.

    Article  Google Scholar 

  19. Sallabi, F. M., Gaouda, A. M., & EI-Hag, A. H. (2014). Evaluation of Zigbee wireless sensor networks under high power disturbances. IEEE Transactions on Power Delivery, 29(1), 13–20.

    Article  Google Scholar 

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Acknowledgements

This research is supported by State Grid Corporation of China (GYB17201400178).

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Authors and Affiliations

  1. School of Automation Science and Electrical Engineering, Beihang University, Beijing, 100191, China

    Dawei Deng, Haiwen Yuan, Yong Cui & Yong Ju

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  1. Dawei Deng
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  2. Haiwen Yuan
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  3. Yong Cui
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  4. Yong Ju
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Correspondence to Dawei Deng.

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Deng, D., Yuan, H., Cui, Y. et al. Energy management of WSN-based charge measurement system of ultra high-voltage direct-current transmission line. Wireless Netw 24, 1667–1681 (2018). https://doi.org/10.1007/s11276-016-1419-4

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  • DOI: https://doi.org/10.1007/s11276-016-1419-4

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