@inproceedings{ceefa7f88dbe4e599ad04d69e63a6ccd,
title = "Cooperative operation optimization of offshore wind power and hybrid electric-hydrogen energy storage",
abstract = "Under the {"}dual carbon{"} target, offshore wind power (OWP) is continuously developing, which brings about the challenges of wind power consumption and dealing with the uncertainty of power output. To address this issue, a hydrogen storage system containing hydrogen storage caverns and an electro-hydrogen hybrid energy storage system with retired power batteries are constructed. A collaborative optimization operation model of OWP and electro-hydrogen hybrid energy storage is studied by establishing a distributionally robust optimization model of wind power output fuzzy sets based on data-driven Wasserstein distance. Finally, the impact of different prediction errors on system operation and operating costs is studied through case studies, verifying the effectiveness of electro-hydrogen hybrid energy storage in wind power consumption and reducing real-time power deviation.",
keywords = "collaborative optimization, Hybrid Electric-hydrogen Energy Storagey, OWP PV",
author = "Nan Yang and Hao Chen and Shanke Mou and Aixia Bao and Xiangwen Wu",
note = "Publisher Copyright: {\textcopyright} 2025 SPIE.; 9th International Conference on Energy System, Electricity, and Power, ESEP 2024 ; Conference date: 29-11-2024 Through 01-12-2024",
year = "2025",
doi = "10.1117/12.3061435",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Yunfei Mu and Kolhe, \{Mohan Lal\} and Ze Cheng and Qian Xiao",
booktitle = "Ninth International Conference on Energy System, Electricity, and Power, ESEP 2024",
address = "United States",
}