Advertisement

Data Monitoring for Interconnecting Microgrids Based on IOT

  • Weihua DengEmail author
  • Shufen Wang
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 924)

Abstract

The real time monitoring is very important for the interconnecting microgrids. The power production status is not only grasped by watching the real time data, but also some optimization approach can be employed to improve operation mode thus dispatching power reasonably. But now a full range of monitoring of interconnecting microgrids is not implemented yet. In the present age of big data, the computing capability and storage space have been developing fast. These advanced techniques enable the large-scale data monitoring system. The big data from monitoring can be analyzed and applied into the optimization of production process. Motivated by this, a real-time data monitoring system simulation platform is developed. Specially, ThingSpeak platform is validated in our work.

Keywords

Microgrid IOT Thingspeak Monitoring 

References

  1. 1.
    Chowdhury, S., Chowdhury, S.P., Crossley, P.: Microgrids and Active Distribution Networks, Renewable Energy Series, vol. 6. Institution of Engineering and Technology, Stevenage (2009)CrossRefGoogle Scholar
  2. 2.
    Gil, N.J., Lopes, J.A.P.: Hierarchical frequency control scheme for islanded multi-microgrids operation. In: IEEE Lausanne Power Tech Lausanne, pp. 473–478 (2007)Google Scholar
  3. 3.
    Lopes, J.A.P., Hatziargyriou, N., Mutale, J., Djapic, P., Jenkins, N.: Integrating distributed generation into electric power systems: A review of drivers, challenges and opportunities. Lecct. Rower Syst. Rest. 77(9), 1189–1203 (2007)Google Scholar
  4. 4.
    Buayai, K., Ongsakul, W., Mithulananthan, N.: Multi-objective micro-grid planning by NSGA-II in primary distribution system. Eur. Trans. Elect. Power 22(2), 170–187 (2012)CrossRefGoogle Scholar
  5. 5.
    Koyanagi, K., et al.: Electricity cluster-oriented network: a gridindependent and autonomous aggregation of micro-grids. In: Proceedings of the International Symposium: Modern Electric Power System, Wroclaw, Poland, pp. 1–6, September 2010Google Scholar
  6. 6.
    Aditya, S.K., Das, D.: Load-frequency control of an interconnected hydro-thermal power system with new area control error considering battery energy storage facility. Int. J. Energy Res. 24, 525–538 (2000)CrossRefGoogle Scholar
  7. 7.
    Usama, M.U., Kelle, D., Baldwin, T.: Utilizing spinning reserves as energy storage for renewable energy integration. In: Power Systems Conference, pp. 1–5 (2014)Google Scholar
  8. 8.
    Ktiraei, F., Iravani, R., Hatziargyriou, N., Dimeas, A.: Microgrids Management: Controls and Operation Aspects of Microgrids. IEEE Power and Energy Magazine (2008)Google Scholar
  9. 9.
    Beerten, J., Cole, S., Belmans, R.: Modeling of multi-terminal VSC HVDC systems with distributed DC voltage control. IEEE Trans. Power Syst. 29(1), 34–42 (2014)CrossRefGoogle Scholar
  10. 10.
    Lu, W., Ooi, B.-T.: Optimal acquisition and aggregation of offshore wind power by multiterminal voltage-source HVDC. IEEE Trans Power Deliv. 18, 201–206 (2003)CrossRefGoogle Scholar
  11. 11.
    Maureira, G.A.M., Oldenhof, D., Teernstra, L.: ThingSpeak—an API and Web Service for the Internet of Things. World Wide Web, 7 November 2015Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Shanghai University of Electric PowerShanghaiChina

Personalised recommendations