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Forecasting methods for wind power scenarios of multiple wind farms based on spatio-temporal dependency structure

Yanting Li, Xinghao Peng and Yu Zhang

Renewable Energy, 2022, vol. 201, issue P1, 950-960

Abstract: In this paper, we first proposed a new wind power generation scheme for multiple wind farms that considers both spatial and temporal dependence of wind power time series based on copula theory in a computationally efficient way. Different vine copulas were studied and compared. Then a novel two-stage spatio-temporal sampling method is used to generate wind power scenario samples. Finally, we propose a conditional quantile sampling method that converts the samples into specific wind power generation scenarios. A case study was conducted on Wind Integration National Dataset (WIND) of National Renewable Energy Laboratory (NREL) to benchmark the performance of the new method with existing methods. The results show that the proposed method can generate scenarios with more accuracy and efficiency, which is conducive to subsequent operations.

Keywords: Wind power; Scenario generation; Spatio-temporal dependence; Vine copula (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:201:y:2022:i:p1:p:950-960

DOI: 10.1016/j.renene.2022.11.002

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