Advertisement

Reliability Assessment and Economic Evaluation of Offshore Wind Farm Using Stochastic Probability

  • Ahmed M. AtallahEmail author
  • Almoataz Y. Abdelaziz
  • Mohamed Ali
  • R. K. Saket
  • O. P. Bharti
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 394)

Abstract

This paper shortly introduced the electric power transmission system for offshore wind farms (OWF). The transmission system components are demonstrated. Each component cost and reliability are studied and tabulated. An evaluation of the transmission system reliability of OWF is performed to increase the dependence on the OWF as a power source in the future. Reliability assessment is performed on a proposed site in Zafarana, Egypt and results are tabulated and simulated for different distances from the shore. The cost of the transmission system is studied using the stochastic probability method; optimization is performed on the investment cost, unavailability cost, and ohmic cost losses. Optimization results on the proposed site are done using different electrical power transmission system schemes. Losses due to the wind unavailability and ohmic losses are studied and simulated.

Keywords

Reliability assessment Economic evaluation Offshore wind farm Stochastic probability 

References

  1. 1.
    Shahinpour A, Moghani JS, Gharehpetian GB, Abdi B. High gain high-voltage z-source converter for offshore wind energy systems. In: IEEE conference, power electronics, 5th drive systems and technologies conference (PEDSTC). Tehran, Iran; 2014.Google Scholar
  2. 2.
    Sannino A, Breder H, Nielsen EK. Reliability of collection grids for large offshore wind parks. In: Proceedings of the 9th international conference on probabilistic methods applied to power systems; 2006. p. 1–6.Google Scholar
  3. 3.
    Underbrink A, Hanson J, Osterholt A, Zimmermann W. Probabilistic reliability calculations for the grid connections of an offshore wind farm. In: Proceedings of the 9th international conference on probabilistic methods applied to power systems; 2006. p. 1–5.Google Scholar
  4. 4.
    Zhao M, Chen Z, Blaabjerg F. Generation ratio availability assessment of electrical systems for offshore wind farms. IEEE Trans Energy Convers. 2007;22(3):755–63.CrossRefGoogle Scholar
  5. 5.
    Shin J-S, Kim J-O, Cha ST, Wu Q. Reliability evaluation considering structures of a large scale wind farm. Power electronics and applications (EPE), 15th IEEE European conference on Lille, France; 2013.Google Scholar
  6. 6.
    Negra NB, Holmstrøm O, Bak-Jensen B, Sorensen P. Aspects of relevance in offshore wind farm reliability assessment. IEEE Trans Energy Convers. 2007;22(1):159–66.CrossRefGoogle Scholar
  7. 7.
    Tastu J, Pinson P, Trombe P-J, Madsen H. Probabilistic forecasts of wind power generation accounting for geographically dispersed information. IEEE Trans Smart Grid. 2014.Google Scholar
  8. 8.
    Ackermann T. Transmission systems for offshore wind farms. In: Ackermann T, editor. Wind power in power systems. West Sussex, England: Wiley; 2005. p. 479–503.Google Scholar
  9. 9.
    Lumbreras S, Ramos A. Optimal design of the electrical layout of an offshore wind farm applying decomposition strategies. Power Syst IEEE Trans IEEE Power Energy Soc. 2013.Google Scholar
  10. 10.
    Wright SD, Rogers AL, Manwell JF, Ellis A. Transmission options for offshore wind farms in the united states. In: Proceedings of the AWEA annual conference; 2002. p. 1–12.Google Scholar
  11. 11.
    McShane P. Vegetable-oil-based dielectric coolants. IEEE Ind Appl Mag. 2002;8(3):34–41.Google Scholar
  12. 12.
    Nielson P. Offshore wind energy projects feasibility study guidelines. [Online document], 2003 June (Ver 3.0), [cited 2006 Aug 07]. http://www.emd.dk/Projects/Projekter/Seawind/OTHER%20RELEVANT%20DOCOPPERMENTS/Feasibility%20Study%20Guidelines.pdf. (2003)
  13. 13.
    Gerdes G, et al. Case study: european offshore wind farms – a survey for the analysis of the experiences and lessons learnt by developers of offshore wind farms—final report. Published by the EU project “POWER—Pushing Offshore Windfarm Regions”.Google Scholar
  14. 14.
    Ionescu A, Brkic S. Report on the implementation of CBT mechanism in SEE region. Power point presentation prepared for ETSO, 4th Athens Forum. http://www.seerecon.org/infrastructure/sectors/energy/documents/3ew/cbt_mechanism_implementation.ppt(2004).
  15. 15.
    Caramanis T, Associates. Cost and risk analysis for a Norway-Netherlands HVDC interconnector. Power point presentation, tabors caramanis and associates. http://www.dte.nl/nl/Images/12_24732.pdf (2004).
  16. 16.
    Lumbreras S, Ramos A, Cerisola S. A progressive contingency incorporation approach for stochastic optimization problems. IEEE Trans Power Syst. 2013.Google Scholar
  17. 17.
    Brown T. Transmission network loading in Europe with high shares of renewables. IET Renew Power Gener. 2015.Google Scholar
  18. 18.
    Banzo M, Ramos A. Stochastic optimization model for electric power system planning of offshore wind farms. IEEE Trans Power Syst. 2013;26(3).Google Scholar

Copyright information

© Springer India 2016

Authors and Affiliations

  • Ahmed M. Atallah
    • 1
    Email author
  • Almoataz Y. Abdelaziz
    • 1
  • Mohamed Ali
    • 1
  • R. K. Saket
    • 2
  • O. P. Bharti
    • 2
  1. 1.Electrical Power & Machines DepartmentFaculty of Engineering Ain Shams UniversityCairoEgypt
  2. 2.Electrical Engineering DepartmentIndian Institute of Technology (BHU)Varanasi (UP)India

Personalised recommendations