电力系统保护与控制2025，Vol.53Issue(3)：68-80,13.DOI:10.19783/j.cnki.pspc.240512
可再生能源ALK-PEM联合制氢系统多时间尺度优化运行策略
Multi-time scale optimization strategy of a renewable energy ALK-PEM combined hydrogen production system
摘要
Abstract
With the gradual increase in the demand for hydrogen,research on the optimal operation of a renewable energy hydrogen production system has become a hot topic.However,the uncertainty of wind and solar renewable energy output makes the optimal operation of these systems complex.To address the impact of wind and solar output uncertainty on system optimization,a multi-time scale optimization strategy for a renewable energy alkaline-proton exchange membrane combined hydrogen production system is proposed,aiming to minimize the system's daily operating cost.The strategy implements a multi-time scale operational control based on the differences in dynamic response capabilities of different equipment in the system and their specific functions.In the day-ahead stage,a day-ahead distributed robust optimization model of the renewable energy alkaline-proton exchange membrane combined hydrogen production system is constructed.In the intra-day stage,a rolling optimization strategy is adopted.In the real-time stage,supercapacitors are used to smooth out the severe fluctuations in wind and solar power,and then the real-time optimal operation strategy is proposed to minimize the output adjustment variation of each device.The case study results show that the operational economy of the system can be improved by the multi-time scale optimization operation strategy from day-ahead to intra-day and to real-time.关键词
碱性-质子交换膜联合制氢/多时间尺度/分布鲁棒/滚动优化Key words
alkaline-proton exchange membrane combined hydrogen production/multiple-time-scale/distributed robust/rolling optimization引用本文复制引用
杨胜,樊艳芳,侯俊杰,白雪岩,谢紫云..可再生能源ALK-PEM联合制氢系统多时间尺度优化运行策略[J].电力系统保护与控制,2025,53(3):68-80,13.基金项目
This work is supported by the Natural Science Foundation of Xinjiang Uygur Autonomous Region(No.2022D01C365). 新疆维吾尔自治区自然科学基金项目资助(2022D01C365) （No.2022D01C365）
天山英才培养计划项目资助(2022TSYCLJ0019) （2022TSYCLJ0019）
