Advertisement

Composite Reliability Assessment of Power Systems with Large Penetration of Renewable Sources

  • Armando M. Leite da Silva
  • Luiz Antônio F. Manso
  • Silvan A. Flávio
  • Mauro A. da Rosa
  • Leonidas C. Resende
Chapter
Part of the Reliable and Sustainable Electric Power and Energy Systems Management book series (RSEPESM)

Abstract

The constant increase in oil prices and the concern over the reduction of gas emissions causing the greenhouse effect favor the creation of policies to encourage the production of energy through renewable sources. The recent restructuring of the electricity sector has introduced new concepts such as power market, transmission open access, cogeneration, independent production, etc., which enabled the decentralized energy generation, strengthening such policies. Thus, non-conventional energy sources, namely wind power, mini-hydro, solar, and cogeneration (e.g., biomass), start having a significant contribution in the energy production matrix. However, if the volatility of the available capacity from such sources is not properly considered, the decisions taken in power systems expansion and/or operation planning can severely endanger the reliability of the power supply. Thus, systems planners and operators will require new computational tools capable of coping with these characteristics, in addition to the recent power system market implementation in a deregulated environment.

Keywords

Monte Carlo Simulation Reliability Index Renewable Source Composite Reliability Optimal Power Flow 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This work was partially supported by the following Brazilian research institutions: CNPq, CAPES, FAPEMIG, and INERGE. The authors would like to thank Prof. Warlley Salles (Federal University of São João del-Rei, MG, Brazil), Prof. Manuel Matos and Mr. Ricardo Ferreira (INESC Tec, Porto, Portugal), and also Dr. Reinaldo González-Fernández (Itaipu Binational, Paraguay) for important discussions.

References

  1. 1.
    Presidency Conclusions of the Brussels European Council (2007). Reference DOC/07/1. Accessible on http://www.eppgroup.eu/Press/pfocus/docs/March07.pdf
  2. 2.
    CAISO (2007) Integration of renewable resources. Available at http://www.caiso.com/1ca5/1ca5a7a026270.pdf
  3. 3.
    Billinton R, Chen H, Ghajar R (1996) A sequential simulation technique for adequacy evaluation of generating systems including wind energy. IEEE Trans Energy Convers 11(4):728–734CrossRefGoogle Scholar
  4. 4.
    Billinton R, Karki R (2001) Capacity expansion of small isolated power systems using PV and wind energy. IEEE Trans Power Syst 16(4):892–897Google Scholar
  5. 5.
    Billinton R, Wangdee W (2007) Reliability-based transmission reinforcement planning associated with large-scale wind farms. IEEE Trans Power Syst 22(1):34–41CrossRefGoogle Scholar
  6. 6.
    Wangdee W, Billinton R (2007) Reliability assessment of bulk electric systems containing large wind farms. Int J Elect Power Energy Syst 29(10):759–766, DecGoogle Scholar
  7. 7.
    Leite da Silva AM, Manso LAF, Sales WS, Resende LC, Aguiar MJQ, Matos MA, Peças Lopes JA, Miranda V (2007) Application of Monte Carlo simulation to generating system well-being analysis considering renewable sources. Eur Trans Electr Power 17:387–400, July/AugGoogle Scholar
  8. 8.
    Matos MA, Peças Lopes JA, Rosa MA, Ferreira R, Leite da Silva AM, Sales WS, Resende LC, Manso LAF (2008) Dealing with intermittent generation in the long-term evaluation of system adequacy and operational reserve requirements in the Iberian Peninsula. In: Proceedings of 2008 session CIGRÉ—international conference, Paris, France, paper C1-304, 24–29 Aug 2008Google Scholar
  9. 9.
    Lingfeng W, Singh C (2008) Population-based intelligent search in reliability evaluation of generation systems with wind power penetration. IEEE Trans Power Syst 23(3):1336–1345CrossRefGoogle Scholar
  10. 10.
    Matos MA, Peças Lopes JA, Rosa MA, Ferreira R, Leite da Silva AM, Sales WS, Resende LC, Manso LAF (2009) Probabilistic evaluation of reserve requirements of generating systems with renewable power sources: The Portuguese and Spanish cases. Int J Electr Power Energy Syst 31(9):562–569Google Scholar
  11. 11.
    Billinton R, Yi G, Karki R (2009) Composite system adequacy assessment incorporating large-scale wind energy conversion systems considering wind speed correlation. IEEE Trans Power Syst 24(3):1375–1382CrossRefGoogle Scholar
  12. 12.
    Liang W, Jeongje P, Jaeseok C, El-Keib AA, Shahidehpour M, Billinton R (2009) A probabilistic reliability evaluation of a power system including solar/photovoltaic cell generator. IEEE PES general meeting, Calgary, Alberta, Canada, 26−30 July 2009Google Scholar
  13. 13.
    INESC Porto and DIEE Italy—Univ of Cagliari (2009) Study on the impact of large renewable deployment on European electricity higher voltage systems—Final report (vols I—Steady state analysis and II—Reliability evaluation). Institute of the Joint Research Centre (JCR-IE), Oct 2009Google Scholar
  14. 14.
    Leite da Silva AM, Sales WS, Manso LAF, Billinton R (2010) Long-term probabilistic evaluation of operating reserve requirements with renewable sources. IEEE Trans Power Syst 25(1):106–116CrossRefGoogle Scholar
  15. 15.
    LF Rocha, Borges CLT (2010) Probabilistic generation and interruption costs and other economic aspects related to distributed generation integration. IEEE PES GM, Minneapolis, MN, USA 25–29 July 2010Google Scholar
  16. 16.
    Flávio SA, Manso LAF, Resende LC, Sales WS, Leite da Silva AM (2011) Reliability of generation and transmission systems with large penetration of renewable sources. In: Proceedings CIGRÉ international symposium on assessing and improving power system security, reliability and performance in light of changing energy sources, Recife, Brazil, 2011Google Scholar
  17. 17.
    Ding Y, Wang P, Goel L, Loh PC, Wu Q (2011) Long-term reserve expansion of power systems with high wind power penetration using universal generating function methods. IEEE Trans Power Syst 26(2):766–774CrossRefGoogle Scholar
  18. 18.
    Shu Z, Jirutitijaroen P (2011) Latin hypercube sampling techniques for power systems reliability analysis with renewable energy sources. IEEE Trans Power Syst 26(4):2066–2073CrossRefGoogle Scholar
  19. 19.
    Bordeerath B, Jirutitijaroen P (2012) Hybrid enumeration and conditional probability approach for reliability analysis of power systems with renewable energy sources. In: 12th PMAPS—international conference on probabilistic methods applied to power systems, Istanbul, Turkey, 10–14 June 2012Google Scholar
  20. 20.
    Leite da Silva AM, Manso LAF, Sales WS, Flávio SA, Anders GJ, Resende LC (2012) Chronological power flow for planning transmission systems considering intermittent sources. IEEE Trans Power Syst 27(4):2314–2322Google Scholar
  21. 21.
    Carvalho LM, Rosa MA, Leite da Silva AM, Miranda V (2012) Probabilistic analysis for maximizing the grid integration of wind power generation. IEEE Trans Power Syst 27(4):2323–2331Google Scholar
  22. 22.
    Subcommittee on the Application of Probability Methods IEEE (1979) IEEE reliability test system. IEEE Trans PAS, vol PAS-99, pp 2047–2054 Nov/Dec 1979Google Scholar
  23. 23.
    Subcommittee on the Application of Probability Methods IEEE (1999) The IEEE reliability test system—1996. IEEE Trans Power Syst 14:1010–1020 Aug 1999Google Scholar
  24. 24.
    Pereira MVF, Balu NJ (1992) Composite generation/transmission reliability evaluation. Proc IEEE 80(4):470–491 Apr 1992Google Scholar
  25. 25.
    Billinton R, Allan RN (1992) Reliability evaluation of engineering systems—concepts and techniques. Plenum Press, New YorkGoogle Scholar
  26. 26.
    Li W (2005) Risk assessment of power systems—models, methods, and applications. IEEE Press/Wiley, New YorkGoogle Scholar
  27. 27.
    Billinton R, Li W (1994) Reliability assessment of electric power systems using monte carlo methods. Plenum Press, New YorkGoogle Scholar
  28. 28.
    Salvaderi L (1990) Monte Carlo simulation techniques in reliability assessment of composite generation and transmission systems, IEEE tutorial course 90EH0311-1-PWR:36–43Google Scholar
  29. 29.
    Leite da Silva AM, Manso LAF, Mello JCO, Billinton R (2000) Pseudo-chronological simulation for composite reliability analysis with time varying loads. IEEE Trans Power Syst 15(1):73–80CrossRefGoogle Scholar
  30. 30.
    Leite da Silva AM, Resende LC, Manso LAF, Billinton R (2004) Well-being analysis for composite generation and transmission systems. IEEE Trans Power Syst 19(4):1763–1770CrossRefGoogle Scholar
  31. 31.
    Leite da Silva AM, González-Fernández RA, Sales WS, Manso LAF (2010) Reliability assessment of time-dependent systems via quasi-sequential Monte Carlo simulation. In: 11th PMAPS—probabilistic methods applied to power systems, Singapore, pp 14–17 June 2010Google Scholar
  32. 32.
    González-Fernández RA, Leite da Silva AM (2012) Comparison between different cross-entropy based methods applied to generating capacity reliability. In: 12th PMAPS—international conference on probabilistic methods applied to power systems, Istanbul, Turkey, pp 10–14 June 2012Google Scholar
  33. 33.
    Koninklijk Netherlands Meteorological Institute (KNMI) (2010) KNMI—climate and services. Accessible on: http://www.knmi.nl/klimatologie/onderzoeksgegevens/potentiele_wind/index.cg?language=eng
  34. 34.
    Leite da Silva AM, Gonzalez-Fernandez RA, Singh C (2010) Generating capacity reliability evaluation based on Monte Carlo simulation and cross-entropy methods. IEEE Trans Power Syst 25(1):129–137CrossRefGoogle Scholar
  35. 35.
    Gonzalez-Fernandez RA, Leite da Silva AM (2011) Reliability assessment of time-dependent systems via sequential cross-entropy Monte Carlo simulation. IEEE Trans Power Syst 26(4):2381–2389CrossRefGoogle Scholar

Copyright information

© Springer India 2013

Authors and Affiliations

  • Armando M. Leite da Silva
    • 1
  • Luiz Antônio F. Manso
    • 2
  • Silvan A. Flávio
    • 1
  • Mauro A. da Rosa
    • 3
  • Leonidas C. Resende
    • 2
  1. 1.Institute of Electrical Systems and EnergyFederal University of Itajubá, UNIFEIItajubáBrazil
  2. 2.Electrical Engineering DepartmentFederal University of São João del-Rei, UFSJSão João del-ReiBrazil
  3. 3.Power System UnitINESC TechPortoPortugal

Personalised recommendations