重庆理工大学学报2025，Vol.39Issue(5)：57-65,9.DOI:10.3969/j.issn.1674-8425(z).2025.03.008
碱性电解水制氢双目标能效模型全局遗传算法求解与应用
Solution and application of a dual-objective energy efficiency model for alkaline water electrolysis using global genetic search algorithm
摘要
Abstract
To address the high energy consumption and low hydrogen production efficiency in industrial water electrolysis for hydrogen generation,we propose a dual-objective energy efficiency optimization model to promote sustainable development.First,by building an electrolyzer voltage model,we analyze the impacts of reaction temperature,operating pressure,and current density on the voltage characteristics of the electrolyzer.Then,an efficiency optimization model for alkaline water electrolysis is formulated,utilizing a global genetic search algorithm that integrates the extensive search capability of genetic algorithms with the fine-tuning advantages of global search algorithms to achieve efficient and high-precision optimization.Simulation and practical applications demonstrate that under optimal parameters(current density of 1 492.00 A/m2,pressure of 10.00 bar,and temperature of 95.00℃),hydrogen production efficiency reaches 93.75%.Our proposed algorithm exhibits both efficiency and rationality while model stability is verified through sensitivity analysis.In real applications,the model's simulation values closely align with measured values,confirming its practicality and feasibility,thereby providing valuable reference for further optimizing hydrogen production systems.关键词
新能源/清洁能源/碱性电解水制氢/能耗/智能算法/制氢效率/优化模型Key words
new energy/clean energy/hydrogen production by alkaline electrolysis of water/energy consumption/intelligent algorithms/hydrogen production efficiency/optimization model分类
计算机与自动化引用本文复制引用
张宝平,赵雄,陈明轩,王文雍,郁章涛,季孟波,李晶,周灿,齐志新..碱性电解水制氢双目标能效模型全局遗传算法求解与应用[J].重庆理工大学学报,2025,39(5):57-65,9.基金项目
国家自然科学基金项目(52367022) （52367022）
多场景规模化电解水制氢关键技术研究及应用示范项目(CTGTC/2023-LQ-07) （CTGTC/2023-LQ-07）
