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\begin{document}
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\title{Distributionally Robust Dispatch of Thermal Units with Multiple Energy
Storage Considering Oxygen-enriched Deep Peaking Technology}



\author[1]{Xiong Wu}%
\author[1]{Yonglong Fan}%
\author[2]{Junji Zhou}%
\author[3]{Dong Liu}%
\affil[1]{Xi'an Jiaotong University}%
\affil[2]{Xian Jiaotong University}%
\affil[3]{State Grid Economic and Technological Research Institute Co., Ltd.}%


\vspace{-1em}



  
  \date{April 25, 2026}


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\begin{abstract}
The growing penetration of renewable energy needs a large amount of
flexible resource to regulate in power systems. Current research mainly
focuses on individual flexibility of resources, the synergistic flexible
potential of thermal units with multi-energy storage systems remains
underexplored. Therefore, this paper proposes a distributionally robust
optimal dispatch method for multiple flexible resources including
thermal units and multiple energy storage. Firstly, a refined operation
model of units and energy storage is constructed. Specifically,
oxygen-enriched deep peaking of units and coordinated operation of
battery and hydrogen energy storage are considered. Secondly, a
data-driven distributionally robust optimization (DRO) model is
established to cope with the uncertainties of renewable energy. An
inexact columns and constraint generation (i-C\&CG) method is then
developed to solve the model efficiently. Finally, a case study of a
provincial power system is conducted, and the results verify the
validity of the proposed method.%
\end{abstract}%



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\verb`\begin{CJK}{UTF8}{gbsn}初稿\end{CJK}\selectlanguage{english}_0602.docx`  available at \url{https://authorea.com/users/933482/articles/1304177-distributionally-robust-dispatch-of-thermal-units-with-multiple-energy-storage-considering-oxygen-enriched-deep-peaking-technology}

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