Data Driven Robust Energy and Reserve Dispatch Based on a Nonparametric Dirichlet Process Gaussian Mixture Model

Data Driven Robust Energy and Reserve Dispatch Based on a Nonparametric Dirichlet Process Gaussian Mixture Model

Traditional robust optimization methods use box uncertainty sets or gamma uncertainty sets to describe wind power uncertainty. However, these uncertainty sets fail to utilize wind forecast error probability information and assume that the wind forecast error is symmetrical and independent. This assu...

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Bibliographic Details
Main Authors: Li Dai, Dahai You, Xianggen Yin
Format: Article
Language:English
Published: MDPI AG 2020-09-01
Series:Energies
Subjects:
energy and reserve dispatch
data driven robust optimization
polyhedral uncertainty set
nonparametric Dirichlet process Gaussian mixture model
Online Access:https://www.mdpi.com/1996-1073/13/18/4642

Internet

https://www.mdpi.com/1996-1073/13/18/4642

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