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A House Appliances-Level Co-simulation Framework for Smart Grid Applications

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Systems Modeling: Methodologies and Tools

Abstract

As the penetration of intelligent and ICT-enabled household devices grows, the need for better understanding of their benefits and threats rises. On the one hand, these devices enable new smart grid applications, such as demand response, which have the potential to improve the usage of energy supply and eventually lead to minimizing the electricity costs. On the other hand, the fine-grained consumption readings can be exploited to reveal private information about the household such as the type of devices and inhabitants behavior. In this paper, we present a co-simulation framework that captures two important worlds of the smart grid, namely the communication world and power world. Real data as well as simulation models are used to simulate several home appliances. The power grid simulator OpenDSS is used to implement the home level power grid, and the data communication simulator OMNeT++ is used to control the behavior of the devices as well as to implement the data communication network. Through a case study, we show how it is possible to integrate privacy approaches inside demand response for a better privacy-preserving smart metering.

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References

  1. A. Awad, P. Bazan, R. German, SGsim: a simulation framework for smart grid applications, in Proceedings of the IEEE International Energy Conference (ENERGYCON 2014), Dubrovnik, Croatia, May 2014, pp. 730–736

    Google Scholar 

  2. A. Awad, P. Bazan, R. German, Privacy aware demand response and smart metering, in Proceedings of the IEEE 81st Vehicular Technology Conference: VTC2015-Spring, First International Workshop on Integrating Communications, Control, Computing Technologies for Smart Grid (ICT4SG), Glasgow, May 2015, pp. 1–15

    Google Scholar 

  3. A. Awad, P. Bazan, R. German, SGsim: co-simulation framework for ICT-enabled power distribution grids, in 18th International GI/ITG Conference on Measurement, Modelling and Evaluation of Computing Systems and Dependability and Fault-Tolerance (MMB & DFT 2016), Münster, April 2016

    Google Scholar 

  4. A. Awad, P. Bazan, R. Kassem, R. German, Co-simulation-based evaluation of volt-VAR control. In 2016 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), October 2016, pp. 1–6

    Google Scholar 

  5. A. Awad, P. Bazan, R. German, A short tutorial on using SGsim framework for smart grid applications, in Proceedings of the 10th EAI International Conference on Performance Evaluation Methodologies and Tools on 10th EAI International Conference on Performance Evaluation Methodologies and Tools, Valuetools16 (2017), pp. 143–148

    Google Scholar 

  6. P. Barbosa, A. Brito, H. Almeida, S. Clauß, Lightweight privacy for smart metering data by adding noise, in Proceedings of the 29th Annual ACM Symposium on Applied Computing, SAC ’14, New York, NY, 2014, pp. 531–538

    Google Scholar 

  7. C. Beckel, L. Sadamori, T. Staake, S. Santini, Revealing household characteristics from smart meter data. Energy 78, 397–410 (2014)

    Article  Google Scholar 

  8. A. Bokhari, A. Alkan, R. Dogan, M. Diaz-Aguilo, F. de Leon, D. Czarkowski, Z. Zabar, L. Birenbaum, A. Noel, R. Uosef, Experimental determination of the ZIP coefficients for modern residential, commercial, and industrial loads. IEEE Trans. Power Delivery 29(3), 1372–1381 (2014)

    Article  Google Scholar 

  9. D.P. Chassin, K. Schneider, C. Gerkensmeyer Gridlab-d: an open-source power systems modeling and simulation environment, in 2008 IEEE/PES Transmission and Distribution Conference and Exposition (2008), pp. 1–5

    Google Scholar 

  10. J. Dede, K. Kuladinithi, A. Förster, O. Nannen, S. Lehnhoff, Omnet++ and mosaik: Enabling simulation of smart grid communications. arXiv preprint arXiv:1509.03067 (2015)

    Google Scholar 

  11. M. Diaz-Aguiló, J. Sandraz, R. Macwan, F. de León, D. Czarkowski, C. Comack, D. Wang, Field-validated load model for the analysis of CVR in distribution secondary networks: energy conservation. IEEE Trans. Power Delivery 28(4), 2428–2436 (2013)

    Article  Google Scholar 

  12. DIgSILENT power factory, DIgSILENT GmbH, Gomaringen (2016). http://www.digsilent.de/index.php/products-powerfactory.html

  13. EPRI Electrical Power Research Institute, Home page, October 2015

    Google Scholar 

  14. P. Fritzson, P. Aronsson, H. Lundvall, K. Nyström, A. Pop, L. Saldamli, D. Broman, The openmodelica modeling, simulation, and development environment. in 46th Conference on Simulation and Modelling of the Scandinavian Simulation Society (SIMS2005), Trondheim, October 13–14, 2005

    Google Scholar 

  15. C. Gisler, A. Ridi, D. Zufferey, O.A. Khaled, J. Hennebert, Appliance consumption signature database and recognition test protocols, in 2013 8th International Workshop on Systems, Signal Processing and their Applications (WoSSPA), pp. 336–341, May 2013

    Google Scholar 

  16. International Energy Agency. Global EV Outlook 2016: Beyond one million electric cars. OECD/IEA, Frankreich, 2016

    Google Scholar 

  17. C. Laughman, K. Lee, R. Cox, S. Shaw, S. Leeb, L. Norford, P. Armstrong, Power signature analysis. IEEE Power Energ. Mag. 1(2), 56–63 (2003)

    Article  Google Scholar 

  18. M. Lévesque, D.Q. Xu, G. Joós, M. Maier, Communications and power distribution network co-simulation for multidisciplinary smart grid experimentations, in Proceedings of the 45th Annual Simulation Symposium (Society for Computer Simulation International, San Diego, 2012), p. 2

    Google Scholar 

  19. F. Li, B. Luo, P. Liu, Secure information aggregation for smart grids using homomorphic encryption, in 2010 First IEEE International Conference on Smart Grid Communications (SmartGridComm), October 2010, pp. 327–332

    Google Scholar 

  20. P. Palensky, E. Widl, M. Stifter, A. Elsheikh, Modeling intelligent energy systems: co-simulation platform for validating flexible-demand EV charging management. IEEE Trans. Smart Grid 4(4), 1939–1947 (2013)

    Article  Google Scholar 

  21. Pecan street database, Home page, October 2015

    Google Scholar 

  22. A. Reinhardt, F. Englert, D. Christin, Enhancing user privacy by preprocessing distributed smart meter data. In Sustainable Internet and ICT for Sustainability (SustainIT), 2013, October 2013, pp. 1–7

    Google Scholar 

  23. REN21. 2015, Renewables 2015 Global Status Report. REN21 Secretariat Paris, 2015

    Google Scholar 

  24. REN21 renewable energy policy network, Renewables 2005 global status report. Worldwatch Institute, Washington, DC (2005)

    Google Scholar 

  25. A. Ridi, C. Gisler, J. Hennebert, ACS-F2- a new database of appliance consumption signatures, in 2014 6th International Conference of Soft Computing and Pattern Recognition (SoCPaR), August 2014, pp. 145–150

    Google Scholar 

  26. S. Rohjans, S. Lehnhoff, S. Schutte, S. Scherfke, S. Hussain, mosaik-A modular platform for the evaluation of agent-based smart grid control, in Innovative Smart Grid Technologies Europe (ISGT EUROPE), 2013 4th IEEE/PES (IEEE, New York, 2013), pp. 1–5

    Google Scholar 

  27. S. Rohjans, S. Lehnhoff, S. Schu tte, F. Andrén, T. Strasser, Requirements for smart grid simulation tools, in 2014 IEEE 23rd International Symposium on Industrial Electronics (ISIE) (IEEE, New York, 2014), pp. 1730–1736

    Google Scholar 

  28. SGsim, Home page (2016). https://sourceforge.net/projects/sgsim

  29. M. Stifter, J.H. Kazmi, F. Andrén, T. Strasser, Co-simulation of power systems, communication and controls, in 2014 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES) (IEEE, New York, 2014), pp. 1–6

    Google Scholar 

  30. O. Tan, D. Gunduz, H. Poor, Increasing smart meter privacy through energy harvesting and storage devices. IEEE J. Sel. Areas Commun. 31(7), 1331–1341 (2013)

    Article  Google Scholar 

  31. A. Varga, The OMNeT++ discrete event simulation system, in European Simulation Multiconference (ESM 2001), Prague, June 2001

    Google Scholar 

  32. Z. Zhang, J.H. Son, Y. Li, M. Trayer, Z. Pi, D.Y. Hwang, J.K. Moon, Training-free non-intrusive load monitoring of electric vehicle charging with low sampling rate, in The 40th Annual Conference of the IEEE Industrial Electronics Society (IECON 2014), Dallas, TX, October 2014, pp. 1–6

    Google Scholar 

  33. R.D. Zimmerman, C.E. Murillo-Sánchez, R.J. Thomas, Matpower: steady-state operations, planning, and analysis tools for power systems research and education. IEEE Trans. Power Syst. 26(1), 12–19 (2011)

    Article  Google Scholar 

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Acknowledgements

Peter Bazan is also a member of “Energie Campus Nürnberg,” Fürther Str. 250, 90429 Nürnberg. His research was performed as part of the “Energie Campus Nürnberg” and supported by funding through the “Aufbruch Bayern (Bavaria on the move)” initiative of the state of Bavaria.

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Correspondence to Abdalkarim Awad .

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Awad, A., Bazan, P., German, R. (2019). A House Appliances-Level Co-simulation Framework for Smart Grid Applications. In: Puliafito, A., Trivedi, K. (eds) Systems Modeling: Methodologies and Tools. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-319-92378-9_19

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  • DOI: https://doi.org/10.1007/978-3-319-92378-9_19

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