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Potential capacity factor estimates of wind generating resources for transmission planning

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  • Hur, Jin

Abstract

Wind Generating Resources (WGRs) are variable, uncontrollable, and uncertain compared to traditional generating resources. As Wind Generating Resources (WGRs) have the intermittent nature of WGRs and uncertain characteristics according to the weather condition, the accurate prediction of WGRs' capacity factor is an essential factor associated with integrating a large amount of wind generating resources into the grid. As wind farm outputs depend on natural wind resources that vary over space and time, spatial correlation analysis is also needed to estimate power outputs of wind generation resources. In this paper, we propose the potential capacity factor estimates of new wind generating resources using the augmented spatial analysis and modelling of power outputs produced by wind farms that are geographically distributed in windy areas. To validate the proposed spatial prediction model, we use the empirical data from the Jeju Island's wind farms in South Korea.

Suggested Citation

  • Hur, Jin, 2021. "Potential capacity factor estimates of wind generating resources for transmission planning," Renewable Energy, Elsevier, vol. 179(C), pages 1742-1750.
    • Handle: RePEc:eee:renene:v:179:y:2021:i:c:p:1742-1750
    DOI: 10.1016/j.renene.2021.08.015
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    References listed on IDEAS

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    1. Girard, R. & Laquaine, K. & Kariniotakis, G., 2013. "Assessment of wind power predictability as a decision factor in the investment phase of wind farms," Applied Energy, Elsevier, vol. 101(C), pages 609-617.
    2. Lee, Yerim & Hur, Jin, 2019. "A simultaneous approach implementing wind-powered electric vehicle charging stations for charging demand dispersion," Renewable Energy, Elsevier, vol. 144(C), pages 172-179.
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    1. Bodong, Song & Wiseong, Jin & Chengmeng, Li & Khakichi, Aroos, 2023. "Economic management and planning based on a probabilistic model in a multi-energy market in the presence of renewable energy sources with a demand-side management program," Energy, Elsevier, vol. 269(C).

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