整流器(神经网络)
堆栈(抽象数据类型)
晶闸管
能源消耗
电气工程
碱性水电解
可再生能源
工程类
电压
电解
计算机科学
化学
人工神经网络
电解质
随机神经网络
机器学习
循环神经网络
物理化学
程序设计语言
电极
作者
Joonas Koponen,Vesa Ruuskanen,Antti Kosonen,Markku Niemelä,Jero Ahola
标识
DOI:10.1109/tpel.2018.2876636
摘要
Water electrolysis will be used to produce renewable hydrogen for energy storage and Power-to-X applications in the future renewable-energy-based energy systems. Therefore, the energy efficiency of hydrogen production will probably become a major issue. In this study, the effect of practical supply power converters on the specific energy consumption ofMW-scale alkaline electrolyzers is studied and compared with an ideal DC power supply. The current quality and the stack specific energy consumption are studied in the case of traditional thyristor rectifiers and a transistor-based converter. The stack specific energy consumption is analyzed based on the simulated current waveforms and the electrical equivalent circuit of the electrolyzer stack. It is found that the transistor-based converter offers up to 14% lower electrolyzer stack specific energy consumption than the 6-pulse thyristor rectifier and up to 9.2% lower electrolyzer stack specific energy consumption than the 12-pulse thyristor rectifier as the current varies between 5000A and 1000A. The simulated change in the stack specific energy consumption of the MW-scale alkaline water electrolyzer outweighs the losses occurring in the rectifiers. Further, selection of the AC voltage level may have a more adverse effect on the stack specific energy consumption with the thyristor rectifier topologies compared with the transistor-based topologies.
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