Data-Driven Stochastic-Robust Planning for Resilient Hydrogen-Electricity System With Progressive Hedging Decoupling

作     者：Wen, Ziyi Zhang, Xian Wang, Guibin Li, Yiqun Qiu, Jing Wen, Fushuan 

作者机构： School of Mechanical Engineering and Automation Shenzhen518055 China Shenzhen University College of Mechatronics and Control Engineering Shenzhen518060 China Southeast University School of Transportation Nanjing211189 China The University of Sydney School of Electrical and Information Engineering SydneyNSW2006 Australia Zhejiang University College of Electrical Engineering Hangzhou310027 China 

出 版 物：《IEEE Transactions on Sustainable Energy》 (IEEE Trans. Sustainable Energy)

年 卷 期：2025年第16卷第3期

页      面：1545-1561页

核心收录：

学科分类：0808[工学-电气工程] 080802[工学-电力系统及其自动化] 08[工学] 0202[经济学-应用经济学] 1202[管理学-工商管理] 1004[医学-公共卫生与预防医学(可授医学、理学学位)] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 1002[医学-临床医学] 1001[医学-基础医学(可授医学、理学学位)] 0807[工学-动力工程及工程热物理] 0837[工学-安全科学与工程] 0714[理学-统计学（可授理学、经济学学位）] 0701[理学-数学] 

基　　金：This work was supported in part by the National Natural Science Foundation of China under Grant 72171155 and Grant 72001058  in part by the Guangdong Basic and Applied Basic Research Foundation under Grant 2023A1515010724  Grant 2022A1515240051  and Grant 2024A1515012656  in part by the General Program of Foundation of Shenzhen Science and Technology Committee under Grant GXWD20231130154831002  in part by the Major Science and Technology Special Projects in Xinjiang Autonomous Region under Grant 2022A01007  in part by the Xinjiang Autonomous Region Key Research and Development Task Special Project under Grant 2022B01016  and in part by the China Hydrogen Alliance Policy Research Project under Grant CHA2022RP001 

主　　题：Stochastic systems 

摘      要：Given the severe damage that typhoons can inflict on power systems, it is of utmost urgency to develop proactive pre-disaster planning to enhance power system resilience. To this end, considering the high efficiency and long-term storage capabilities of hydrogen energy, a resilience-oriented planning model of the hydrogen-electricity integrated energy system (H-EIES) is constructed in this work. In this resilience-oriented planning model, hardening power lines and constructing hydrogen-to-power stations (H2Ps) are jointly planned to reduce load shedding during typhoons. A tri-layer stochastic-robust optimization (SRO) approach is proposed to find the optimal construction strategy under uncertainties, where the first layer determines the planning strategy, the second layer identifies the worst outage contingency, and the third layer ensures the optimal operation. However, the uncertainty of typhoons presents significant challenges to the feasibility of the proposed SRO approach. Therefore, this work leverages the Wasserstein generative adversarial network with gradient penalty (WGAN-GP) and spectral clustering method to quantify the typhoon uncertainty. Additionally, a novel nested column-and-constraint generation with progressive hedging algorithm (C&CG-PHA) is elaborately designed to solve the complex tri-layer and multi-scenario coupled optimization problem. Validating by the real-life typhoon data, numerical experiments are carried out and indicate the economic efficiency and robustness of the proposed SRO approach, where the system s load shedding losses are reduced by 95.7%. Also, it has been proved that the C&CG-PHA can notably accelerate the solution process and exhibit excellent scalability. © 2010-2012 IEEE.