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A Data-Driven Uncertainty Quantification Method for Stochastic Economic Dispatch
[article]
2021
arXiv
pre-print
This letter proposes a data-driven sparse polynomial chaos expansion-based surrogate model for the stochastic economic dispatch problem considering uncertainty from wind power. The proposed method can provide accurate estimations for the statistical information (e.g., mean, variance, probability density function, and cumulative distribution function) for the stochastic economic dispatch solution efficiently without requiring the probability distributions of random inputs. Simulation studies on
arXiv:2109.08195v1
fatcat:3jmbq5ao3nhwzfyv4dg5mi7lmq