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A review on reliability assessment for wind power

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  • Wen, Jiang
  • Zheng, Yan
  • Donghan, Feng

Abstract

The application of wind energy in electric power systems is growing rapidly due to enhanced public concerns to adverse environmental impacts and escalation in energy costs associated with the use of conventional energy sources. Electric power from wind energy is quite different from that of conventional resources. The fundamental difference is that the wind power is intermittent and uncertain. Therefore, it affects the reliability of power system in a different manner from that of the conventional generators. This paper, from available literatures, presents the model of wind farms and the methods of wind speed parameters assessment. Two main categories of methods for evaluating the wind power reliability contribution, i.e., the analytical method and the Monte Carlo simulation method have been reviewed. This paper also summarizes factors affecting the reliability of wind power system, such as wake effect, correlation of output power for different windturbines, effect of windturbine parameters, penetration and environment. An example has been used to illustrate how these factors affect the reliability of wind power system. Finally, mainstream reliability indices for evaluating reliability are introduced. Among these reliability indices, some are recently developed, such as wind generation interrupted energy benefit (WGIEB), wind generation interruption cost benefit (WGICB), Equivalent Capacity Rate (ECR), load carrying capacity benefit ratio (LCCBR).

Suggested Citation

  • Wen, Jiang & Zheng, Yan & Donghan, Feng, 2009. "A review on reliability assessment for wind power," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(9), pages 2485-2494, December.
    • Handle: RePEc:eee:rensus:v:13:y:2009:i:9:p:2485-2494
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    Citations

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    Cited by:

    1. Roy, Sanjoy, 2014. "Performance prediction of active pitch-regulated wind turbine with short duration variations in source wind," Applied Energy, Elsevier, vol. 114(C), pages 700-708.
    2. Ashrafi, Maryam & Davoudpour, Hamid & Khodakarami, Vahid, 2015. "Risk assessment of wind turbines: Transition from pure mechanistic paradigm to modern complexity paradigm," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 347-355.
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    9. Mosadeghy, Mehdi & Yan, Ruifeng & Saha, Tapan Kumar, 2016. "Impact of PV penetration level on the capacity value of South Australian wind farms," Renewable Energy, Elsevier, vol. 85(C), pages 1135-1142.
    10. Malik, Abdul Q., 2021. "Renewables for Fiji – Path for green power generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    11. Mahbudi, Shahrbanoo & Jamalizadeh, Ahad & Farnoosh, Rahman, 2020. "Use of finite mixture models with skew-t-normal Birnbaum-Saunders components in the analysis of wind speed: Case studies in Ontario, Canada," Renewable Energy, Elsevier, vol. 162(C), pages 196-211.
    12. Li, Shenghu, 2013. "Reliability models for DFIGs considering topology change under different control strategies and components data change under adverse operation environments," Renewable Energy, Elsevier, vol. 57(C), pages 144-150.
    13. Hachicha, Fatma & Krichen, Lotfi, 2012. "Rotor power control in doubly fed induction generator wind turbine under grid faults," Energy, Elsevier, vol. 44(1), pages 853-861.
    14. Makhloufi, Saida & Mekhaldi, Abdelouahab & Teguar, Madjid, 2016. "Three powerful nature-inspired algorithms to optimize power flow in Algeria's Adrar power system," Energy, Elsevier, vol. 116(P1), pages 1117-1130.
    15. Cuervo, Felipe Isaza & Botero, Sergio Botero, 2016. "Wind power reliability valuation in a Hydro-Dominated power market: The Colombian case," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1359-1372.
    16. Chaiamarit, Kunjana & Nuchprayoon, Somboon, 2013. "Modeling of renewable energy resources for generation reliability evaluation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 26(C), pages 34-41.
    17. Feijóo, Andrés & Villanueva, Daniel & Pazos, José Luis & Sobolewski, Robert, 2011. "Simulation of correlated wind speeds: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(6), pages 2826-2832, August.
    18. Wang, L. & Kolios, A. & Liu, X. & Venetsanos, D. & Rui, C., 2022. "Reliability of offshore wind turbine support structures: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    19. Masmoudi, Abdelkarim & Abdelkafi, Achraf & Krichen, Lotfi, 2011. "Electric power generation based on variable speed wind turbine under load disturbance," Energy, Elsevier, vol. 36(8), pages 5016-5026.
    20. LM López-Manrique & EV Macias-Melo & KM Aguilar-Castro & I Hernández-Pérez & HP Díaz-Hernández, 2021. "Review on methodological and normative advances in assessment and estimation of wind energy," Energy & Environment, , vol. 32(1), pages 25-61, February.
    21. Eryilmaz, Serkan & Navarro, Jorge, 2022. "A decision theoretic framework for reliability-based optimal wind turbine selection," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    22. Chaudhry, Nikhil & Hughes, Larry, 2012. "Forecasting the reliability of wind-energy systems: A new approach using the RL technique," Applied Energy, Elsevier, vol. 96(C), pages 422-430.
    23. Scholz, Teresa & Lopes, Vitor V. & Estanqueiro, Ana, 2014. "A cyclic time-dependent Markov process to model daily patterns in wind turbine power production," Energy, Elsevier, vol. 67(C), pages 557-568.
    24. Denis Anatolievich Ustinov & Ershat Rashitovich Shafhatov, 2022. "Assessment of Reliability Indicators of Combined Systems of Offshore Wind Turbines and Wave Energy Converters," Energies, MDPI, vol. 15(24), pages 1-20, December.
    25. Malik, A.Q., 2011. "Assessment of the potential of renewables for Brunei Darussalam," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 427-437, January.

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