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Intra Smart Grid Management Frameworks for Control and Energy Saving in Buildings

  • Antonio Guerrieri
  • Jordi Serra
  • David Pubill
  • Christos Verikoukis
  • Giancarlo Fortino
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9258)

Abstract

In the context of Smart Grids and Internet of Things (IoT) Systems, distributed monitoring and actuation through Wireless Sensor and Actuator Networks (WSANs) is fundamental to control the energy usage in buildings. Moreover, the realization of algorithms for the optimization of the energy consumption is of paramount importance. This paper presents a loosely coupled integration between a flexible management framework for WSANs, namely the IGMF (Intra-Grid Management Framework), and a Dynamic Energy Scheduler with local control on sensors and actuators, namely the ITESS (IoTLAB Energy Scheduling System). The integrated system allows the users to manage whole buildings applying Dynamic Energy Schedulers for different environments.

Keywords

Smart grid Internet of things Wireless sensor and actuator networks Building management Energy scheduler 

Notes

Acknowledgments

This work has been partially supported by E2SG project, funded by ENIAC Joint Undertaking under grant agreement n. 296131 and from the national program/funding authority of Italy.paraThis work was partially supported by the Catalan Government under grant 2014-SGR-1551.

References

  1. 1.
    Snoonian, D.: Control systems: smart buildings. IEEE Spectr. 40(8), 18–23 (2003)CrossRefGoogle Scholar
  2. 2.
    Ceriotti, M., Mottola, L., Picco, G., Murphy, A., Guna, S., Corra, M., Pozzi, M., Zonta, D., Zanon, P.: Monitoring heritage buildings with wireless sensor networks: the Torre Aquila deployment. In: International Conference on Information Processing in Sensor Networks, IPSN 2009, pp. 277–288, April 2009Google Scholar
  3. 3.
    Guerrieri, A., Geretti, L., Fortino, G., Abramo, A.: A service-oriented gateway for remote monitoring of building sensor networks. In: Proceedings of the 2013 IEEE 18th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), pp. 139–143, September 2013Google Scholar
  4. 4.
    Liotta, A., Geelen, D., van Kempen, G., van Hoogstraten, F.: A survey on networks for smart-metering systems. Int. J. Pervasive Comput. Commun. 8(1), 23–52 (2012)CrossRefGoogle Scholar
  5. 5.
    Stankovic, J.: When sensor and actuator cover the world. ETRI J. 30(5), 627–633 (2008)CrossRefGoogle Scholar
  6. 6.
    Fortino, G., Guerrieri, A., O’Hare, G., Ruzzelli, A.: A flexible building management framework based on wireless sensor and actuator networks. J. Netw. Comput. Appl. 35, 1934–1952 (2012)CrossRefGoogle Scholar
  7. 7.
    Lu, G., De, D., Song, W.: Smartgridlab: a laboratory-based smart grid testbed. In: IEEE International Conference on Smart Grid Communications, pp. 143–148 (2010)Google Scholar
  8. 8.
    Mohsenian-Rad, A.H., Wong, V., Jatskevich, J., Schober, R., Leon-Garcia, A.: Autonomous demand-side management based on game-theoretic energy consumption scheduling for the future smart grid. IEEE Trans. Smart Grid 1(3), 320–331 (2010)CrossRefGoogle Scholar
  9. 9.
    Diakaki, C., Grigoroudis, E., Kolokotsa, D.: Towards a multi-objective optimization approach for improving energy efficiency in buildings. Energy Build. 40(9), 1747–1754 (2008)CrossRefGoogle Scholar
  10. 10.
    Wood, G., Newborough, M.: Dynamic energy-consumption indicators for domestic appliances: environment, behaviour and design. Energy Build. 35(8), 821–841 (2003)CrossRefGoogle Scholar
  11. 11.
    Avci, M., Erkoc, M., Asfour, S.: Residential HVAC load control strategy in real-time electricity pricing environment. In: 2012 IEEE Energytech, pp. 1–6, May 2012Google Scholar
  12. 12.
    Serra, J., Pubill, D., Antonopoulos, A., Verikoukis, C.: Smart HVAC Control in IoT: energy consumption minimization with user comfort constraints. Sci. World J. 2014, 1–11 (2014)CrossRefGoogle Scholar
  13. 13.
    Krafzig, D., Banke, K., Slama, D.: Enterprise SOA: service-oriented architecture best practices. Prentice Hall Professional, Upper Saddle River (2005)Google Scholar
  14. 14.
    Vlacheas, P., Giaffreda, R., Stavroulaki, V., Kelaidonis, D., Foteinos, V., Poulios, G., Demestichas, P., Somov, A., Biswas, A.R., Moessner, K.: Enabling smart cities through a cognitive management framework for the internet of things. IEEE Commun. Mag. 51(6), 102–111 (2013)CrossRefGoogle Scholar
  15. 15.
    An, S., Park, S., Oh, H., Yang, J., Park, H., Choi, J.: Lightweight web-based communication interface design for web of objects. In: 2013 15th International Conference on Advanced Communication Technology (ICACT), pp. 535–539. IEEE (2013)Google Scholar
  16. 16.
    Petrolo, R., Loscrì, V., Mitton, N.: Towards a smart city based on cloud of things. In: Proceedings of the 2014 ACM International Workshop on Wireless and MobileTechnologies for Smart Cities, pp. 61–66. ACM (2014)Google Scholar
  17. 17.
  18. 18.
    Sanchez, L., Muñoz, L., Galache, J.A., Sotres, P., Santana, J.R., Gutierrez, V., Ramdhany, R., Gluhak, A., Krco, S., Theodoridis, E., et al.: Smartsantander: Iot experimentation over a smart city testbed. Comput. Netw. 61, 217–238 (2014)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Antonio Guerrieri
    • 1
  • Jordi Serra
    • 2
  • David Pubill
    • 2
  • Christos Verikoukis
    • 2
  • Giancarlo Fortino
    • 1
  1. 1.Dipartimento di Ingegneria Informatica, Modellistica, Elettronica e SistemisticaUniversità della CalabriaCosenzaItaly
  2. 2.Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)BarcelonaSpain

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