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A probabilistic security assessment approach to power systems with integrated wind resources

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  • Le, D.D.
  • Berizzi, A.
  • Bovo, C.

Abstract

Renewable energy sources, such as wind and photovoltaic solar, have added additional uncertainty to power systems. These sources, further to the conventional sources of uncertainty due to stochastic nature of both the load and the availability of generation resources and transmission assets, make clear the limitations of the conventional deterministic power flow in power system analysis and security assessment applications. In order to manage uncertainties, probabilistic approaches can provide a valuable contribution.

Suggested Citation

  • Le, D.D. & Berizzi, A. & Bovo, C., 2016. "A probabilistic security assessment approach to power systems with integrated wind resources," Renewable Energy, Elsevier, vol. 85(C), pages 114-123.
    • Handle: RePEc:eee:renene:v:85:y:2016:i:c:p:114-123
    DOI: 10.1016/j.renene.2015.06.035
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    References listed on IDEAS

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    1. Carpinelli, Guido & Caramia, Pierluigi & Varilone, Pietro, 2015. "Multi-linear Monte Carlo simulation method for probabilistic load flow of distribution systems with wind and photovoltaic generation systems," Renewable Energy, Elsevier, vol. 76(C), pages 283-295.
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    Cited by:

    1. Motalleb, Mahdi & Thornton, Matsu & Reihani, Ehsan & Ghorbani, Reza, 2016. "A nascent market for contingency reserve services using demand response," Applied Energy, Elsevier, vol. 179(C), pages 985-995.
    2. Yu, L. & Li, Y.P. & Huang, G.H., 2016. "A fuzzy-stochastic simulation-optimization model for planning electric power systems with considering peak-electricity demand: A case study of Qingdao, China," Energy, Elsevier, vol. 98(C), pages 190-203.
    3. Wang, Jinhe & Zhang, Xiaohong & Zeng, Jianchao & Zhang, Yunzheng, 2020. "Joint external and internal opportunistic optimisation for wind turbine considering wind velocity," Renewable Energy, Elsevier, vol. 159(C), pages 380-398.

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