Distributionally robust planning for power-to- gas integrated large wind farm systems incorporating hydrogen production switch control model

作     者：Son, Yeong Geon Kim, Sung Yul 

作者机构：Hanyang Univ Dept Elect Engn Seoul South Korea 

出 版 物：《ENERGY》 (Energy)

年 卷 期：2025年第314卷

核心收录：

学科分类：0820[工学-石油与天然气工程] 08[工学] 0807[工学-动力工程及工程热物理] 

基　　金：Korea Institute of Energy Technology Evaluation and Planning (KETEP) Ministry of Trade, Industry & Energy (MOTIE) of the Republic of Korea [RS-2023-00247086] 

主　　题：Wind farm Power to gas Distributionally robust optimization Ambiguity set Mixed-integer linear programming 

摘      要：To address the challenges associated with the variability of wind power and to optimize the use of renewable energy, this study investigates the integration of large wind farms with a power-to-gas system. This integration is designed to convert surplus wind energy into hydrogen, thereby enhancing grid stability and reducing energy curtailment. In this paper, an optimal planning and operation strategy is proposed for a large wind farm coupled with a power-to-gas system. The key contributions include: (1) a mixed integer linear programming-based switch control model that accurately captures the realistic operation of the electrolyzer within the power-to-gas system, and (2) a novel distributionally robust optimization method that considers variability in wind speed distributions. The electrolyzer requires a continuous and stable output to preserve its lifespan, and the switch control model ensures realistic operational conditions. The proposed distributionally robust optimization addresses regional variations in wind speeds, balancing robustness with flexibility. A case study demonstrates that the proposed approach outperforms conventional methods. Furthermore, incorporating mixed integer linear programming-based constraints for the electrolyzer switch control led to a 20 % improvement in economic performance over systems without power-to-gas integration and reduced curtailed energy from the wind farm by up to 94.5 %.