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Impact of PV penetration level on the capacity value of South Australian wind farms

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  • Mosadeghy, Mehdi
  • Yan, Ruifeng
  • Saha, Tapan Kumar

Abstract

Renewable generations are growing fast and they are becoming the major generation technology in power systems. Amongst all renewables, wind and solar resources have the highest growth rate. However, fluctuation and uncertainty of these sources are the main barriers in their utilization and can affect reliability of power system. Therefore, these generators must be treated differently in adequacy studies and their reliability contribution should be evaluated. South Australia (SA) accounts for more than half of Australia's wind share and its solar capacity is rapidly increasing as well. Thus, not only the reliability benefit of wind is required to be investigated in this power system, but also the contribution of solar energy and its impacts should be analysed as well. The reliability benefit of wind and PV has been studied in the literature, but there is a need to evaluate their combined contribution in reality and investigate the influence of their correlations. Therefore, this paper evaluates the reliability contribution of wind and solar power in South Australia and the impact of solar energy on wind load carrying capability. State sampling Monte Carlo technique is utilized for reliability assessment and Fuzzy C-means clustering method is employed to create a multistep load model.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:renene:v:85:y:2016:i:c:p:1135-1142
    DOI: 10.1016/j.renene.2015.07.072
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    References listed on IDEAS

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    Cited by:

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    2. Kongrit Mansiri & Sukruedee Sukchai & Chatchai Sirisamphanwong, 2018. "Fuzzy Control for Smart PV-Battery System Management to Stabilize Grid Voltage of 22 kV Distribution System in Thailand," Energies, MDPI, vol. 11(7), pages 1-19, July.
    3. Wenxia Liu & Dapeng Guo & Yahui Xu & Rui Cheng & Zhiqiang Wang & Yueqiao Li, 2018. "Reliability Assessment of Power Systems with Photovoltaic Power Stations Based on Intelligent State Space Reduction and Pseudo-Sequential Monte Carlo Simulation," Energies, MDPI, vol. 11(6), pages 1-14, June.
    4. Mastropietro, Paolo & Rodilla, Pablo & Batlle, Carlos, 2019. "De-rating of wind and solar resources in capacity mechanisms: A review of international experiences," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 253-262.

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