Skip to main content
SpringerLink
Log in

Privacy Preserving Consensus-Based Economic Dispatch in Smart Grid Systems

  • Conference paper
  • First Online:
Future Network Systems and Security (FNSS 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 670))

Included in the following conference series:

Abstract

Economic dispatch is a well-known optimization problem in smart grid systems which aims at minimizing the total cost of power generation among generation units while maintaining some system constraints. Recently, some distributed consensus-based approaches have been proposed to replace traditional centralized calculation. However, existing approaches fail to protect privacy of individual units like cost function parameters, generator constraints, output power levels, etc. In this paper, we show an attack against an existing consensus-based economic dispatch algorithm from [16] assuming semi-honest non-colluding adversaries. Then we propose a simple solution by combining a secure sum protocol and the consensus-based economic dispatch algorithm that guarantees data privacy under the same attacker model. Our Privacy Preserving Economic Dispatch (PPED) protocol is information-theoretically secure.

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 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

Institutional subscriptions

References

  1. Bakirtzis, A., Petridis, V., Kazarlis, S.: Genetic algorithm solution to the economic dispatch problem. IEE Proc.-Gener. Transm. Distrib. 141(4), 377–382 (1994)

    Article  Google Scholar 

  2. Benaloh, J.C.: Secret sharing homomorphisms: keeping shares of a secret secret. In: Odlyzko, A.M. (ed.) Advances in Cryptology, Crypto 86. LNCS, vol. 263, pp. 251–260. Springer, Heidelberg (1986)

    Chapter  Google Scholar 

  3. Bickson, D., Dolev, D., Bezman, G., Pinkas, B.: Peer-to-peer secure multi-party numerical computation. In: 2008 Eighth International Conference on Peer-to-Peer Computing, pp. 257–266. IEEE (2008)

    Google Scholar 

  4. Chor, B., Kushilevitz, E.: A communication-privacy tradeoff for modular addition. Inf. Proces. Lett. 45(4), 205–210 (1993)

    Article  MathSciNet  MATH  Google Scholar 

  5. Chowdhury, B.H., Rahman, S.: A review of recent advances in economic dispatch. IEEE Trans. Power Syst. 5(4), 1248–1259 (1990)

    Article  Google Scholar 

  6. Dominguez-Garcia, A.D., Cady, S.T., Hadjicostis, C.N.: Decentralized optimal dispatch of distributed energy resources. In: 2012 IEEE 51st Annual Conference on Decision and Control (CDC), pp. 3688–3693. IEEE (2012)

    Google Scholar 

  7. Erkin, Z., Troncoso-Pastoriza, J.R., Lagendijk, R.L., Perez-Gonzalez, F.: Privacy-preserving data aggregation in smart metering systems: an overview. IEEE Signal Process. Mag. 30(2), 75–86 (2013)

    Article  Google Scholar 

  8. Gaing, Z.-L.: Particle swarm optimization to solving the economic dispatch considering the generator constraints. IEEE Trans. Power Syst. 18(3), 1187–1195 (2003)

    Article  Google Scholar 

  9. Huang, Z., Mitra, S., Vaidya, N.: Differentially private distributed optimization. In: Proceedings of the 2015 International Conference on Distributed Computing and Networking, p. 4. ACM (2015)

    Google Scholar 

  10. Kreitz, G., Dam, M., Wikström, D.: Practical private information aggregation in large networks. In: Aura, T., Järvinen, K., Nyberg, K. (eds.) NordSec 2010. LNCS, vol. 7127, pp. 89–103. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  11. Kursawe, K., Danezis, G., Kohlweiss, M.: Privacy-friendly aggregation for the smart-grid. In: Fischer-Hübner, S., Hopper, N. (eds.) PETS 2011. LNCS, vol. 6794, pp. 175–191. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

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

    Google Scholar 

  13. Lindell, Y., Pinkas, B.: Secure multiparty computation for privacy-preserving data mining. J. Priv. Confidentiality 1(1), 5 (2009)

    Google Scholar 

  14. Naranjo, J.A.M., Casado, L.G., Jelasity, M.: Asynchronous privacy-preserving iterative computation on peer-to-peer networks. Computing 94(8–10), 763–782 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  15. Wood, A.J., Wollenberg, B.F.: Power Generation Operation and Control. A Wiley-Interscience publication. Wiley, Hoboken (1996)

    Google Scholar 

  16. Yang, S., Tan, S., Jian-Xin, X.: Consensus based approach for economic dispatch problem in a smart grid. IEEE Trans. Power Syst. 28(4), 4416–4426 (2013)

    Article  Google Scholar 

  17. Zhang, Z., Chow, M.-Y.: Convergence analysis of the incremental cost consensus algorithm under different communication network topologies in a smart grid. IEEE Trans. Power Syst. 27(4), 1761–1768 (2012)

    Article  Google Scholar 

Download references

Acknowledgments

The author would like to thank Erik Zenner and Frederik Armknecht for the helpful discussions on security analysis.

Author information

Authors and Affiliations

  1. Offenburg University of Applied Sciences, Offenburg, Germany

    Avikarsha Mandal

Authors
  1. Avikarsha Mandal
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Avikarsha Mandal .

Editor information

Editors and Affiliations

  1. School of Information Technology, Deakin University , Burwood, Victoria, Australia

    Robin Doss

  2. Department of Information Systems and Operations Management, University of Florida, Warrington College of Business Administration, Gainesville, Florida, USA

    Selwyn Piramuthu

  3. Information & Operations Management Department , ESCP Europe, Paris, France

    Wei Zhou

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing AG

About this paper

Cite this paper

Mandal, A. (2016). Privacy Preserving Consensus-Based Economic Dispatch in Smart Grid Systems. In: Doss, R., Piramuthu, S., Zhou, W. (eds) Future Network Systems and Security. FNSS 2016. Communications in Computer and Information Science, vol 670. Springer, Cham. https://doi.org/10.1007/978-3-319-48021-3_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-48021-3_7

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48020-6

  • Online ISBN: 978-3-319-48021-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation