Skip to main content

Optimal Scheduling of On/Off Cycles: A Decentralized IoT-Microgrid Approach

  • Conference paper
  • First Online:

Abstract

The current energy scenario requires actions towards the reduction of energy consumptions and the use of renewable resources. To this end, the energy grid is evolving towards a distributed architecture called Smart Grid (SG). Moreover, new communication paradigms, such as the Internet of Things (IoT), are being applied to the SG providing advanced communication capabilities for management and control. In this context, a microgrid is a self-sustained network that can operate connected to the SG (or in isolation). In such networks, the long-term scheduling of on/off cycles of devices is a problem that has been commonly addressed by centralized approaches. In this paper, we propose a novel IoT-microgrid architecture to model the long-term optimization scheduling problem as a distributed constraint optimization problem (DCOP). We compare different multi-agent DCOP algorithms using different window sizes showing that the proposed architecture can find optimal and near-optimal solutions for a specific case study.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   44.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   60.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Notes

  1. 1.

    We implemented the DCOP algorithms in FRODO2 and JaCoP. Both available in http://frodo2.sourceforge.net and http://www.jacop.eu respectively.

References

  1. Gungor, V., Sahin, D., Kocak, T., Ergut, S., Buccella, C., Cecati, C., Hancke, G.: A survey on smart grid potential applications and communication requirements. IEEE Trans. Ind. Inf. 9(1), 28–42 (2013)

    Article  Google Scholar 

  2. Yan, Y., Qian, Y., Sharif, H., Tipper, D.: A survey on smart grid communication infrastructures: motivations, requirements and challenges. IEEE Commun. Surv. Tutorials 15(1), 5–20 (2013)

    Article  Google Scholar 

  3. Karnouskos, S.: The cooperative internet of things enabled smart grid. In: IEEE International Symposium on Consumer Electronics (2010)

    Google Scholar 

  4. Vega, A., Santamaria, F., Rivas, E.: Modeling for home electric energy management: a review. Renew. Sustain. Energy Rev. 52, 948–959 (2015)

    Article  Google Scholar 

  5. Han, J., sic Choi, C., Park, W.K., Lee, I., Kim, S.H.: Smart home energy management system including renewable energy based on ZigBee and PLC. IEEE Trans. Consum. Electron. 60(2), 198–202 (2014)

    Article  Google Scholar 

  6. Karnouskos, S.: Smart houses in the smart grid and the search for value-added services in the cloud of things era. In: IEEE International Conference on Industrial Technology, pp. 2016–2021, February 2013

    Google Scholar 

  7. Morais, H., Kádár, P., Faria, P., Vale, Z.A., Khodr, H.M.: Optimal Scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming. Renew. Energy 35, 151–156 (2010)

    Article  Google Scholar 

  8. Bazmohammadi, N., Karimpour, A., Bazmohammadi, S.: Optimal operation management of a microgrid based on MOPSO and differential evolution algorithms. In: IEEE Iranian Conference on Smart Grids, pp. 1–6 (2012)

    Google Scholar 

  9. Chaouachi, A., Kamel, R.M., Andoulsi, R., Nagasaka, K.: Multiobjective intelligent energy management for a microgrid. IEEE Trans. Ind. Electron. 60(4), 1688–1699 (2013)

    Article  Google Scholar 

  10. Su, W., Wang, J., Roh, J.: Stochastic energy scheduling in microgrids with intermittent renewable energy resources. IEEE Trans. Smart Grid 5(4), 1876–1883 (2014)

    Article  Google Scholar 

  11. Hiremath, R., Shikha, S., Ravindranath, N.: Decentralized energy planning; modeling and application - a review. Renew. Sustain. Energy Rev. 11(5), 729–752 (2007)

    Article  Google Scholar 

  12. Logenthiran, T., Srinivasan, D., Khambadkone, A.M.: Multi-agent system for energy resource scheduling of integrated microgrids in a distributed system. Electr. Power Syst. Res. 81(1), 138–148 (2011)

    Article  Google Scholar 

  13. Miller, S., Ramchurn, S.D., Rogers, A.: Optimal decentralised dispatch of embedded generation in the smart grid. In: Proceedings of the International Conference on Autonomous Agents and Multiagent Systems, pp. 281–288 (2012)

    Google Scholar 

  14. Petcu, A., Faltings, B.: Superstabilizing, fault-containing distributed combinatorial optimization. In: Proceedings of the National Conference on Artificial Intelligence, pp. 449–454 (2005)

    Google Scholar 

  15. Nguyen, D.T., Yeoh, W., Lau, H.C., Zilberstein, S., Zhang, C.: Decentralized multi-agent reinforcement learning in average-reward dynamic DCOPs. In: Proceedings of the International Conference on Autonomous Agents and Multi-agent Systems, pp. 1341–1342 (2014)

    Google Scholar 

  16. Petcu, A.: A Class of Algorithms for Distributed Constraint Optimization, vol. 194. IOS Press, Amsterdam (2009)

    MATH  Google Scholar 

  17. Chvatal, V.: Linear Programming: Series of Books in the Mathematical Sciences. W.H. Freeman, New York (1983)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Fernando Lezama .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Cite this paper

Lezama, F., Palominos, J., Rodríguez-González, A.Y., Farinelli, A., de Cote, E.M. (2017). Optimal Scheduling of On/Off Cycles: A Decentralized IoT-Microgrid Approach. In: Sucar, E., Mayora, O., Munoz de Cote, E. (eds) Applications for Future Internet. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 179. Springer, Cham. https://doi.org/10.1007/978-3-319-49622-1_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-49622-1_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49621-4

  • Online ISBN: 978-3-319-49622-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics