发电技术2025，Vol.46Issue(3)：482-495,14.DOI:10.12096/j.2096-4528.pgt.24167
基于人工智能的可再生能源电解水制氢关键技术及发展前景分析
Analysis of Key Technologies and Development Prospects for Renewable Energy-Powered Water Electrolysis for Hydrogen Production Based on Artificial Intelligence
摘要
Abstract
[Objectives]As an essential sustainable energy technology,renewable energy-powered water electrolysis for hydrogen production has attracted widespread attention due to its advantages in environmental protection and low carbon emissions.However,conventional water electrolysis technologies for hydrogen production face challenges in terms of efficiency and cost,the rapid development of artificial intelligence(AI)provides an effective way to solve the difficult problems of hydrogen production technology through electrolysis of water.To address this,this study aims to explore the key applications and development prospects of AI for optimizing the efficiency and economic performance of water electrolysis systems for hydrogen production.[Methods]Common AI tools such as MATLAB,Python,and SimuNPS are employed for algorithm development,deep learning model training,and multi-physics simulation in water electrolysis systems for hydrogen production.By integrating AI technologies,applications such as output prediction,system capacity optimization and scheduling,and fault diagnosis are implemented to improve system performance and stability.A comparative analysis of performance of different AI models in various real-world scenarios is conducted to explore their specific roles and implementation methods in enhancing system performance and controllability.[Conclusions]AI technology offers new avenues for enhancing the efficiency and intelligent scheduling of renewable energy-powered water electrolysis hydrogen production systems.Future research should focus on the application of AI in output forecasting,scheduling optimization,and fault diagnosis,promoting deep integration between AI and system operation.Moreover,innovative applications of AI in intelligent monitoring,automatic control,and multi-source coordination should be explored to provide strong support for the development of efficient,stable,and low-carbon hydrogen energy systems.关键词
可再生能源/电解水制氢/人工智能(AI)/深度学习/碱性电解槽/质子交换膜电解槽/故障诊断Key words
renewable energy/water electrolysis for hydrogen production/artificial intelligence(AI)/deep learning/alkaline electrolyzer/proton exchange membrane electrolyzer/fault diagnosis分类
能源与动力引用本文复制引用
杨博,张子健..基于人工智能的可再生能源电解水制氢关键技术及发展前景分析[J].发电技术,2025,46(3):482-495,14.基金项目
国家自然科学基金项目(62263014) （62263014）
云南省应用基础研究计划项目(202401AT070344,202301AT070443).Project Supported by National Natural Science Foundation of China(62263014) （202401AT070344,202301AT070443）
Yunnan Provincial Basic Research Project(202401AT070344,202301AT070443). （202401AT070344,202301AT070443）
