Skip to main content
SpringerLink
Log in

Towards Discovering the Limits of Smart Grid Communication Infrastructure

  • Conference paper
  • First Online:
Book cover Governing Business Systems

Part of the book series: Springer Proceedings in Business and Economics ((SPBE))

Abstract

The concept of Smart Grid enforces standard power grid with intelligent devices and communication network to add new functionality to the power distribution system. The concept builds upon enormous volumes of metering and monitoring data, and thus also a robust communication infrastructure. Apart from pilot projects, modeling and simulation plays an important role in smart grids design, since it provides an opportunity to effectively benchmark and compare particular technologies, especially for its communication infrastructure.

In this paper, we summarize the specifics of communication in smart grids. Then, we provide an extensive review on particular approaches to smart grids simulation, which are analyzed and compared. Finally, we present GridMind, a new Smart grid simulation software that enhances the quality and usability of executed simulations, describe its features and the simulation process, and discuss its application in real projects.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover 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

Institutional subscriptions

References

  • Albagli, A. N., Falcão, D. M., & de Rezende, J. F. (2016). Smart grid framework co-simulation using HLA architecture. Electric Power Systems Research, 130, 22–33.

    Article  Google Scholar 

  • Alliance LoRa. (2015). Lora technology. Accessed 2015-21-12.

    Google Scholar 

  • Andreadou, N., & Pavlidou, F.-N. (2010). Modeling the noise on the OFDM power-line communications system. IEEE Transactions on Power Delivery, 25, 150–157.

    Article  Google Scholar 

  • Armendariz, M., Chenine, M., Nordstrom, L., & Al-Hammouri, A. (2014). A co-simulation platform for medium/low voltage monitoring and control applications. In 2014 IEEE PES, Innovative Smart Grid Technologies Conference (ISGT) (pp. 1–5). New York: IEEE.

    Google Scholar 

  • Association, D. U. (2003). COSEM glossary of terms.

    Google Scholar 

  • Association, D. U. (2014). COSEM interface classes and OBIS identification system.

    Google Scholar 

  • Association, D. U. (2014). DLMS/COSEM architecture and protocols.

    Google Scholar 

  • Association, D. U. (2015). DLMS/COSEM conformance testing process.

    Google Scholar 

  • Atayero, A. A., Alatishe, A., & Ivanov, Y. A. (2012). Power line communication technologies: Modeling and simulation of prime physical layer. World Congress on Engineering and Computer Science, 2, 931–936.

    Google Scholar 

  • Bauer, M., Plappert, W., Wang, C., & Dostert, K. (2009). Packet-oriented communication protocols for smart grid services over low-speed PLC. In IEEE International Symposium on Power Line Communications and Its Applications, 2009. ISPLC 2009, March (pp. 89–94).

    Google Scholar 

  • Bergmann, J., Glomb, C., Gotz, J., Heuer, J., Kuntschke, R., & Winter, M. (2010). Scalability of smart grid protocols: Protocols and their simulative evaluation for massively distributed DERs. In 2010 First IEEE International Conference on Smart Grid Communications (SmartGridComm), Oct (pp. 131–136).

    Google Scholar 

  • Bhor, D., Angappan, K., & Sivalingam, K. M. (2016). Network and power-grid co-simulation framework for smart grid wide-area monitoring networks. Journal of Network and Computer Applications, 59, 274–284.

    Article  Google Scholar 

  • Canete, F. J., Cortés, J., Díez, L., Entrambasaguas, J. T., & et al. (2011). A channel model proposal for indoor power line communications. IEEE Communications Magazine, 49, 166–174.

    Google Scholar 

  • De Craemer, K., & Deconinck, G. (2010). Analysis of state-of-the-art smart metering communication standards. In Proceedings of the 5th Young Researchers Symposium.

    Google Scholar 

  • Feuerhahn, S., Zillgith, M., Wittwer, C., & Wietfeld, C. (2011). Comparison of the communication protocols DLMS/COSEM, SML and IEC 61850 for smart metering applications. In 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm), Oct (pp. 410–415).

    Google Scholar 

  • Georg, H., Wietfeld, C., Muller, S., & Rehtanz, C. (2012). A HLA based simulator architecture for co-simulating ict based power system control and protection systems. In 2012 IEEE Third International Conference on Smart Grid Communications (SmartGridComm), Nov (pp. 264–269).

    Google Scholar 

  • Godfrey, T., Mullen, S., Dugan, R. C., Rodine, C., Griffith, D. W., & Golmie, N. (2010). Modeling smart grid applications with co-simulation. In 2010 First IEEE International Conference on Smart Grid Communications (SmartGridComm) (pp. 291–296). New York: IEEE.

    Chapter  Google Scholar 

  • Gungor, V., Sahin, D., Kocak, T., Ergut, S., Buccella, C., Cecati, C., & Hancke, G. (2011). Smart grid technologies: Communication technologies and standards. IEEE Transactions on Industrial Informatics, 7, 529–539.

    Article  Google Scholar 

  • Gungor, V. C., Sahin, D., Kocak, T., Ergut, S., Buccella, C., Cecati, C., & Hancke, G. P. (2013) A survey on smart grid potential applications and communication requirements. IEEE Transactions on Industrial Informatics, 9, 28–42.

    Article  Google Scholar 

  • GURUX. (2016). Gurux open source community. Accessed 2016-01-11.

    Google Scholar 

  • Hoch, M. (2011). Comparison of PLC G3 and PRIME. In IEEE International Symposium on Power Line Communications and Its Applications (ISPLC 2011) (pp. 165–169).

    Google Scholar 

  • Hopkinson, K., Wang, X., Giovanini, R., Thorp, J., Birman, K., & Coury, D. (2006). Epochs: A platform for agent-based electric power and communication simulation built from commercial off-the-shelf components. IEEE Transactions on Power Systems, 21, 548–558.

    Article  Google Scholar 

  • IEEE. (2011). IEEE guide for smart grid interoperability of energy technology and information technology operation with the electric power system (EPS), end-use applications, and loads. IEEE Std 2030-2011 (pp. 1–126).

    Google Scholar 

  • Islam, M., Uddin, M. M., Al Mamun, M. A., & Kader, M. (2014). Performance analysis of AMI distributed area network using wimax technology. In 2014 9th International Forum on Strategic Technology (IFOST) (pp. 152–155). New York: IEEE.

    Chapter  Google Scholar 

  • Kim, M.-S., Son, D.-M., Ko, Y.-B., & Kim, Y.-H. (2008). A simulation study of the PLC-MAC performance using network simulator-2. In IEEE International Symposium on Power Line Communications and Its Applications, 2008. ISPLC 2008, April (pp. 99–104).

    Google Scholar 

  • Kmethy, G. (2014). IEC 62056 DLMS/COSEM seminar – communication profiles. Accessed 2016-01-05.

    Google Scholar 

  • Kosek, A., Lunsdorf, O., Scherfke, S., Gehrke, O., & Rohjans, S. (2014). Evaluation of smart grid control strategies in co-simulation 2014; integration of IPSYS and mosaik. Power Systems Computation Conference (PSCC), 2014, Aug (pp. 1–7).

    Google Scholar 

  • Kouhdaragh, V., Tarchi, D., Vanelli-Coralli, A., & Corazza, G. E. (2015). Smart meters density effects on the number of collectors in a smart grid. 2015 European Conference on Networks and Communications (EuCNC) (pp. 476–481). New York: IEEE.

    Google Scholar 

  • Krejčí, L. (2014). Programové vybavení datového koncentrátoru AMM sítě [online]. Masters thesis, Czech Technical University. Available at http://is.muni.cz/th/325292/fi_m/.

  • Lévesque, M., Béchet, C., Suignard, E., Maier, M., Picault, A., & Joós, G. (2014). From co-toward multi-simulation of smart grids based on HLA and FMI standards. arXiv preprint arXiv:1412.5571.

    Google Scholar 

  • Li, W., & Zhang, X. (2014). Simulation of the smart grid communications: Challenges, techniques, and future trends. Computers & Electrical Engineering, 40, 270–288.

    Article  Google Scholar 

  • Lin, H., Sambamoorthy, S., Shukla, S., Thorp, J., & Mili, L. (2011). Power system and communication network co-simulation for smart grid applications. In 2011 IEEE PES Innovative Smart Grid Technologies (ISGT) (pp. 1–6). New York: IEEE.

    Google Scholar 

  • Lin, H., Veda, S. S., Shukla, S. S., Mili, L., & Thorp, J. (2012). Geco: Global event-driven co-simulation framework for interconnected power system and communication network. IEEE Transactions on Smart Grid, 3, 1444–1456.

    Article  Google Scholar 

  • López, G., Moreno, J., Amarís, H., & Salazar, F. (2015). Paving the road toward smart grids through large-scale advanced metering infrastructures. Electric Power Systems Research, 120, 194–205.

    Article  Google Scholar 

  • López, G., Moura, P. S., Custodio, V., & Moreno, J. I. (2012). Modeling the neighborhood area networks of the smart grid. In 2012 IEEE International Conference on Communications (ICC) (pp. 3357–3361). New York: IEEE.

    Chapter  Google Scholar 

  • Lu, X., Kim, I. H., & Vedantham, R. (2013). Implementing prime for robust and reliable power line communication (PLC). Texas Instruments White Paper.

    Google Scholar 

  • Madueno, G. C., Stefanovic, C., & Popovski, P. (2013). How many smart meters can be deployed in a gsm cell? In 2013 IEEE International Conference on Communications Workshops (ICC) (pp. 1263–1268). New York: IEEE.

    Chapter  Google Scholar 

  • Matanza, J., Alexandres, S., & Rodriguez-Morcillo, C. (2013). Automatic meter-reading simulation through power line communication. In 2013 IEEE 21st International Symposium on Modeling, Analysis Simulation of Computer and Telecommunication Systems (MASCOTS), Aug (pp. 283–287).

    Google Scholar 

  • Meters and Alliance, M. (2015). Technology — meters and more. Accessed 2015-12-11.

    Google Scholar 

  • Mets, K., Ojea, J. A., & Develder, C. (2014). Combining power and communication network simulation for cost-effective smart grid analysis. IEEE Communications Surveys Tutorials, 16, 1771–1796.

    Article  Google Scholar 

  • Mets, K., Verschueren, T., Develder, C., Vandoorn, T., & Vandevelde, L. (2011). Integrated simulation of power and communication networks for smart grid applications. 2011 IEEE 16th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), June (pp. 61–65).

    Google Scholar 

  • Niyato, D., Xiao, L., & Wang, P. (2011). Machine-to-machine communications for home energy management system in smart grid. IEEE Communications Magazine, 49, 53–59.

    Article  Google Scholar 

  • Open meter. (2015). Report on final test results and recommendations. Accessed 2015-11-06.

    Google Scholar 

  • Pang, C., Vyatkin, V., & Mayer, H. (2014). Towards cyber-physical approach for prototyping indoor lighting automation systems. In 2014 IEEE International Conference on Systems, Man and Cybernetics (SMC) (pp. 3643–3648). New York: IEEE.

    Chapter  Google Scholar 

  • Pham, G. T. (2013). Integration of IEC 61850 MMS and LTE to support smart metering communications.

    Google Scholar 

  • Prasanna, S. G., Lakshmi, A., Sumanth, S., Simha, V., Bapat, J., & Koomullil, G. (2009). Data communication over the smart grid. In IEEE International Symposium on Power Line Communications and Its Applications, 2009. ISPLC 2009 (pp. 273–279). New York: IEEE.

    Google Scholar 

  • Razazian, K., Umari, M., Kamalizad, A., Loginov, V., & Navid, M. (2010). G3-PLC specification for powerline communication: Overview, system simulation and field trial results. In 2010 IEEE International Symposium on Power Line Communications and Its Applications (ISPLC) (pp. 313–318). New York: IEEE.

    Google Scholar 

  • Rengaraju, P., Lung, C.-H., & Srinivasan, A. (2012). Communication requirements and analysis of distribution networks using wimax technology for smart grids. In 2012 8th International Wireless Communications and Mobile Computing Conference (IWCMC) (pp. 666–670). New York: IEEE.

    Chapter  Google Scholar 

  • Rosecky, J., Prochazka, F., & Buhnova, B. (2015). Grid mind: Prolog-based simulation environment for future energy grids.

    Google Scholar 

  • Rinaldi, S. M. (2004). Modeling and simulating critical infrastructures and their interdependencies. In Proceedings of the 37th Annual Hawaii International Conference on System Sciences, 2004 (pp. 873–880). New York: IEEE.

    Google Scholar 

  • Schütte, S., Scherfke, S., & Sonnenschein, M. (2012). Mosaik-smart grid simulation API. In Proceedings of SMARTGREENS (pp. 14–24).

    Google Scholar 

  • Sendin, A., Berganza, I., Arzuaga, A., Pulkkinen, A., & Kim, I. H. (2012). Performance results from 100,000+ prime smart meters deployment in Spain. In 2012 IEEE Third International Conference on Smart Grid Communications (SmartGridComm) (pp. 145–150). New York: IEEE.

    Chapter  Google Scholar 

  • Skrášek, T. (2015). Úzkopásmová PLC komunikace se standardy G3-PLC, PRIME a IEEE-1901.2 [online]. Masters thesis, Brno University of Technology. Available at http://hdl.handle.net/11012/39956.

  • Taylor, D. & Kmethy, G. (2010). 61968-9 message profiles for DLMS/COSEM. Accessed 2015-19-11.

    Google Scholar 

  • Tonello, A. M., & Versolatto, F. (2010). Bottom-up statistical PLC channel modeling - Part II: Inferring the statistics. IEEE Transactions on Power Delivery, 25, 2356–2363.

    Article  Google Scholar 

  • Tonello, A. M. & Versolatto, F. (2011). Bottom-up statistical PLC channel modeling - Part I: Random topology model and efficient transfer function computation. IEEE Transactions on Power Delivery, 26, 891–898.

    Article  Google Scholar 

  • Tonello, A. M., & Zheng, T. (2009). Bottom-up transfer function generator for broadband PLC statistical channel modeling. In IEEE International Symposium on Power Line Communications and Its Applications, 2009. ISPLC 2009 (pp. 7–12). New York: IEEE.

    Google Scholar 

  • Trefke, J., Rohjans, S., Uslar, M., Lehnhoff, S., Nordstrom, L., & Saleem, A. (2013). Smart grid architecture model use case management in a large european smart grid project. In 4th IEEE/PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), 2013 (pp. 1–5). New York: IEEE.

    Google Scholar 

  • Usman, A. & Shami, S. H. (2013). Evolution of communication technologies for smart grid applications. Renewable and Sustainable Energy Reviews, 19, 191–199.

    Article  Google Scholar 

  • Vyas, D., & Pandya, H. (2012). Advance metering infrastructure and dlms/cosem standards for smart grid. International Journal of Engineering Research, 1. e-ISSN: 2278-0181.

    Google Scholar 

  • Wang, W., Xu, Y., & Khanna, M. (2011). A survey on the communication architectures in smart grid. Computer Networks, 55, 3604–3629.

    Article  Google Scholar 

  • Wolkerstorfer, M., Schweighofer, B., Wegleiter, H., Statovci, D., Schwaiger, H., & Lackner, W. (2016). Measurement and simulation framework for throughput evaluation of narrowband power line communication links in low-voltage grids. Journal of Network and Computer Applications, 59, 285–300.

    Article  Google Scholar 

  • Yadav, A. (2015). Cypress powerline communication (PLC) repeater implementation. Accessed 2015-11-13.

    Google Scholar 

  • Zaballos, A., Vallejo, A., Majoral, M., & Selga, J. (2009). Survey and performance comparison of AMR over PLC standards. IEEE Transactions on Power Delivery, 24, 604–613.

    Article  Google Scholar 

  • Zaballos, A., Vallejo, A., & Selga, J. M. (2011). Heterogeneous communication architecture for the smart grid. IEEE Network, 25, 30–37.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Informatics, Masaryk University, Brno, Czech Republic

    Miroslav Kadlec, Jan Rosecky, Barbora Buhnova & Tomas Pitner

  2. Mycroft Mind, a.s., Brno, Czech Republic

    Jan Rosecky & Filip Prochazka

Authors
  1. Miroslav Kadlec
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jan Rosecky
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Filip Prochazka
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Barbora Buhnova
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Tomas Pitner
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Miroslav Kadlec .

Editor information

Editors and Affiliations

  1. Professor of Management, University of Palermo and Business Systems Laboratory, Palermo and Avellino, Italy

    Gandolfo Dominici

  2. Professor of Management, University of Rome “Link Campus”, Naples, Italy

    Manlio Del Giudice

  3. Law and Economics of Productive Activities, Sapienza University of Rome, Rome, Italy

    Rosa Lombardi

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Cite this paper

Kadlec, M., Rosecky, J., Prochazka, F., Buhnova, B., Pitner, T. (2018). Towards Discovering the Limits of Smart Grid Communication Infrastructure. In: Dominici, G., Del Giudice, M., Lombardi, R. (eds) Governing Business Systems. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-319-66036-3_5

Download citation

Publish with us

Policies and ethics

Search

Navigation