Sparse Variational Gaussian Process Based Day-Ahead Probabilistic Wind Power Forecasting

IEEE Transactions on Sustainable Energy(2022)

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摘要
In this paper, we present a probabilistic wind power forecasting (PWPF) model via quantification of epistemic uncertainty and aleatory uncertainty. Concretely, the epistemic uncertainty is described by the statistical characteristics of function space constituted by all wind power forecasting (WPF) mappings through Gaussian process (GP) frameworks. In particular, we adopt the sparse variational Ga...
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关键词
Uncertainty,Wind power generation,Forecasting,Predictive models,Data models,Kernel,Estimation
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