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Electric Power Systems

  • Antonello MontiEmail author
  • Ferdinanda Ponci
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 565)

Abstract

The electric power system is one of the largest and most complex infrastructures and it is critical to the operation of society and other infrastructures. The power system is undergoing deep changes which result in new monitoring and control challenges in its own operation, and in unprecedented coupling with other infrastructures, in particular communications and the other energy grids. This Chapter provides an overview of this transformation, starting from the primary causes through the technical challenges, and some perspective solutions.

Keywords

Power systems Smart grid Renewable energy sources Monitoring Control Distributed resources 

References

  1. 1.
    Amin, M.: Automation, control, and complexity: An integrated approach. In: Samad & Weyrauch (eds.) Wiley, pp. 263–286 (2000)Google Scholar
  2. 2.
    Monti, A., Ponci, F.: The Complexity of Smart Grid. IEEE Smart Grid e-Newsletter, May 2012Google Scholar
  3. 3.
    Future Internet for Smart Energy (Finseny): Future Internet PPP, FP7. http://www.fi-ppp-finseny.eu/
  4. 4.
    Future Internet Smart Utility Services (Finesce): Future Internet PPP, FP7. http://www.finesce.eu/
  5. 5.
    Ericsen, T.: The second electronic revolution (It´s all about control). IEEE Trans. Ind. Appl. 46(5), 1778–1786 (2010)CrossRefGoogle Scholar
  6. 6.
    Molitor, C., Benigni, A., Helmedag, A., Chen, K., Cali, D., Jahangiri, P., Muller, D., Monti, A.: Multi-physics test bed for renewable energy systems in smart homes. IEEE Trans. Ind. Electron. 60(3), 1235–1248 (2013)CrossRefGoogle Scholar
  7. 7.
    Karlsson, D., Hemmingsson, M., Lindahl, S.: Wide area system monitoring and control—terminology, phenomena, and solution implementation strategies. IEEE Power Energy Mag. 2(5), 68–76 (2004)CrossRefGoogle Scholar
  8. 8.
    Atanackovic, D., Clapauch, J.H., Dwernychuk, G., Gurney, J., Lee, H.: First steps to wide area control. IEEE Power Energy Mag. 6(1), 61–68 (2008)CrossRefGoogle Scholar
  9. 9.
    Chakrabarti, S., Kyriakides, E., Bi, T., Cai, D., Terzija, V.: Measurements get together. IEEE Power Energy Mag. 7(1), 41–49 (2009)CrossRefGoogle Scholar
  10. 10.
    Data provided by ENTSO-E. http://www.entsoe.eu
  11. 11.
    Fraunhofer Institute for solar energy systems ISE – Electricity production from solar and wind in Germany. http://www.ise.fraunhofer.de/de/downloads/pdf-files/aktuelles/stromproduktion-aus-solar-und-windenergie-2012.pdf (2013)
  12. 12.
  13. 13.
  14. 14.
  15. 15.
    NIST Special Publication 1108 NIST Framework and Roadmap for Smart Grid Interoperability Standards, Release 1.0. http://www.nist.gov/public_affairs/releases/upload/smartgrid_interoperability_final.pdf. Accessed Jan 2010
  16. 16.
  17. 17.
    ftp://ftp.cencenelec.eu/CENELEC/Smartgrid/SmartGridFinalReport.pdfGoogle Scholar
  18. 18.
    Della Giustina, D., Pau, M., Pegoraro, P.A., Ponci, F., Sulis, S.: Distribution system state estimation: Measurement issues and challenges. IEEE Instrum. Meas. Mag. (2014)Google Scholar
  19. 19.
    Machowski, J., Bialek, J.W., Bumby J.R.: Power System Dynamics: Stability and Control. Wiley, New York (2008)Google Scholar
  20. 20.
    Continental Europe Operation Handbook, © ENTSO-E (2014)Google Scholar
  21. 21.
    Abur, A., Exposito, A.G.: Power System State Estimation, Theory and Implementation. Marcel Dekker, Inc., New York (2004)Google Scholar
  22. 22.
    IEEE Standard for Synchrophasor Measurements for Power Systems (IEEE Std. 37.118.1-2011) and IEEE Standard for Synchrophasor Data Transfer for Power Systems (IEEE Std. 37.118.2-2011)Google Scholar
  23. 23.
    IEEE Guide for Synchronization, Calibration, Testing, and Installation of Phasor Measurement Units (PMUs) for Power System Protection and Control (IEEE Std. C37.242-2013)Google Scholar
  24. 24.
    Lira, R., Mycock, C., Wilson D., Kang, H.: PMU performance requirements and validation for closed loop applications. In 2nd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies (ISGT Europe), pp. 1–7, Manchester, UK (2011)Google Scholar
  25. 25.
    Junqi, L., Benigni, A., Obradovic, D., Hirche, S., Monti, A.: State estimation and branch current learning using independent local Kalman filter with virtual disturbance model. IEEE Trans. Instrum. Meas. 60(9), 3026–3034 (2011)CrossRefGoogle Scholar
  26. 26.
    Baran, M.E., El-Markabi, I.M.: A multi-agent based dispatching scheme for distributed generators for voltage support of distribution feeders. IEEE Trans. Power Syst. 22(1), 52–59 (2007)CrossRefGoogle Scholar
  27. 27.
    Monti, A., Ponci, F., Benigni, A., Liu, J.: Distributed intelligence for smart grid control. In: 2010 International School on Nonsinusoidal Currents and Compensation (ISNCC), pp. 46–58. Lagow, Poland (2010)Google Scholar
  28. 28.
    Marwali, M.N., Keyhani, A.: Control of distributed generation systems—part I: Voltages and currents control. IEEE Trans. Ind. Electron. 19(6), 1541–1550 (2004)Google Scholar
  29. 29.
    Blaabjerg, F., Teodorescu, R., Liserre, M., Timbus, A.V.: Overview of control and grid synchronization for distributed power generation systems. IEEE Trans. Ind. Electron. 53(5), 1398–1409 (2006)CrossRefGoogle Scholar
  30. 30.
    Macken, K.J.P., Vanthournout, K., Van den Keybus, J., Deconinck, G., Belmans, R.J.M.: Distributed control of renewable generation units with integrated active filter. IEEE Trans. Power Electron. 19(5), 1353–1360 (2004)CrossRefGoogle Scholar
  31. 31.
    Tuladhar, A., Hua, J., Unger, T., Mauch, K.: Control of parallel inverters in distributed AC power systems with consideration of line impedance effect. IEEE Trans. Ind. Appl. 36(1), 131–138 (2000)CrossRefGoogle Scholar
  32. 32.
    Karlsson, P., Svensson, J.: DC bus voltage control for a distributed power system. IEEE Trans. Power Electron. 18(6), 1405–1412 (2003)CrossRefGoogle Scholar
  33. 33.
    Xie, S., Xie, L., Wang, Y., Guo, G.: Decentralized control of multimachine power systems with guaranteed performance. IEE Proc. Control Theory Appl. 147(3), 355–365 (2000)CrossRefGoogle Scholar
  34. 34.
    Venkat, A.N., Hiskens, I.A., Rawlings, J.B., Wright, S.J.: Distributed MPC strategies with application to power system automatic generation control. IEEE Trans. Control Syst. Technol. 16(6), 1192–1206 (2008)CrossRefGoogle Scholar
  35. 35.
    Negenborn, R.R.: Multi-agent model predictive control with applications to Power networks. Doctoral Dissertation, TU Delft (2007)Google Scholar
  36. 36.
    De Brabandere, K., Bolsens, B., Van den Keybus, J., Woyte, A., Driesen, J., Belmans, R.: A voltage and frequency droop control method for parallel inverters. IEEE Trans. Power Electron. 22(4), 1107–1115 (2007)CrossRefGoogle Scholar
  37. 37.
    Liu, J., Obadovic, D., Monti, A.: Decentralized LQG control with online set-point adaptation for parallel power converter systems. In: IEEE Energy Conversion Congress and Exposition (ECCE 2010), pp. 3174–3179. Atlanta, GA, USA (2010)Google Scholar
  38. 38.
    Liu, J.: Cooperative control of distributed power grids using a multi-agent systems approach. Master thesis, Technische Universität München (2009)Google Scholar
  39. 39.
    Gusrialdi, A., Hirche, S.: Performance-oriented communication topology design for large-scale interconnected systems. In: 49th IEEE Conference on Decision and Control (CDC), Atlanta, GA, USA, pp. 5707–5713 (2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.E.ON ERCInstitute for Automation of Complex Power Systems, RWTH Aachen UniversityAachenGermany

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