Adaptive energy optimization strategy of island renewable power-to-hydrogen system with hybrid electrolyzers structure

被引:0
|
作者
Yu, Binbin [1 ]
Fan, Guangyao [1 ]
Sun, Kai [2 ]
Chen, Jing [1 ]
Sun, Bo [1 ]
Tian, Peigen [2 ]
机构
[1] Shandong Univ, Sch Control Sci & Engn, Jingshi Rd 17923, Jinan 250061, Peoples R China
[2] Tsinghua Univ, Dept Elect Engn, Beijing 100084, Peoples R China
基金
中国国家自然科学基金;
关键词
Island power-to-hydrogen system; Hydrogen economy; Equipment durability; Energy optimization; Hybrid electrolyzers; Collaborative hydrogen production; ALKALINE WATER ELECTROLYSIS; GAS; MANAGEMENT; BATTERY; STORAGE; DESIGN;
D O I
暂无
中图分类号
O414.1 [热力学];
学科分类号
摘要
Islands, rich in solar, wind, and wave energy, present an opportunity for sustainable electrolytic hydrogen production. The challenge lies in the variability of 100 % renewable energy, affecting hydrogen output and electrolyzers ' lifespan. To address this, a flexible hybrid electrolyzers structure is designed. It cleverly utilizes the low cost and high efficiency of alkaline electrolyzer to absorb the stable renewable energy component, and the rapid response capability of proton exchange membrane electrolyzer to absorb the fluctuating renewable energy component. Thus, it achieves efficient and long-lasting hydrogen production. Then, an operational optimization strategy is proposed to achieve the optimal hydrogen production scheme for this structure. This strategy includes an electrolyzer scheduling model that considers the dynamic process of state transitions and life degradation under the impact of fluctuating power sources. Furthermore, it encompasses an optimization algorithm balanced for scheduling accuracy, solving efficiency, and reduced risk of local optima through a bi-level fuzzy controller, simplifying the search space. Case studies demonstrated the hybrid structure ' s effectiveness in minimizing lifespan degradation and maximizing profits, validating the optimization method ' s capacity to quickly find the optimal scheduling plan. Results showed improvements of 6.6 % in annual return, 13.4 % in device lifespan, and 30.1 % in optimization time.
引用
收藏
页数:16
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