{"title":"Development of a dynamic mathematical model of PEM electrolyser for integration into large-scale power systems","authors":"Siavash Asiaban , Dimitar Bozalakov , Lieven Vandevelde","doi":"10.1016/j.ecmx.2024.100610","DOIUrl":null,"url":null,"abstract":"<div><p>Proton exchange membrane (PEM) electrolyser stands as a promising candidate for sustainable hydrogen production from renewable energy sources (RESs). Given the fluctuating nature of RESs, accurate modelling of the PEM electrolyser is crucial. Nonetheless, complex models of the PEM electrolyser demand substantial time and resource investments when integrating them into a large-scale power system. The majority of introduced models in the literature are either overly intricate or fail to effectively reproduce the dynamic behaviour of the PEM electrolyser. To this end, this article aims to develop a model that not only captures the dynamic response of the PEM electrolyser, crucial for conducting flexibility studies in the power system, but also avoids complexity for seamless integration into large-scale simulations without comprising accuracy. To verify the model, it is validated against static and dynamic experimental data. Compared to the investigated experimental cases, the model exhibited an average error of 0.66% and 3.93% in the static and dynamic operation modes, respectively.</p></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":null,"pages":null},"PeriodicalIF":7.1000,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2590174524000886/pdfft?md5=6c5a797f11fb8187188f470ade1be63d&pid=1-s2.0-S2590174524000886-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Conversion and Management-X","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2590174524000886","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
Proton exchange membrane (PEM) electrolyser stands as a promising candidate for sustainable hydrogen production from renewable energy sources (RESs). Given the fluctuating nature of RESs, accurate modelling of the PEM electrolyser is crucial. Nonetheless, complex models of the PEM electrolyser demand substantial time and resource investments when integrating them into a large-scale power system. The majority of introduced models in the literature are either overly intricate or fail to effectively reproduce the dynamic behaviour of the PEM electrolyser. To this end, this article aims to develop a model that not only captures the dynamic response of the PEM electrolyser, crucial for conducting flexibility studies in the power system, but also avoids complexity for seamless integration into large-scale simulations without comprising accuracy. To verify the model, it is validated against static and dynamic experimental data. Compared to the investigated experimental cases, the model exhibited an average error of 0.66% and 3.93% in the static and dynamic operation modes, respectively.
期刊介绍:
Energy Conversion and Management: X is the open access extension of the reputable journal Energy Conversion and Management, serving as a platform for interdisciplinary research on a wide array of critical energy subjects. The journal is dedicated to publishing original contributions and in-depth technical review articles that present groundbreaking research on topics spanning energy generation, utilization, conversion, storage, transmission, conservation, management, and sustainability.
The scope of Energy Conversion and Management: X encompasses various forms of energy, including mechanical, thermal, nuclear, chemical, electromagnetic, magnetic, and electric energy. It addresses all known energy resources, highlighting both conventional sources like fossil fuels and nuclear power, as well as renewable resources such as solar, biomass, hydro, wind, geothermal, and ocean energy.