{"intvolume":"         3","status":"public","year":"2023","author":[{"last_name":"Möller","id":"72391","full_name":"Möller, Marius Claus","first_name":"Marius Claus"},{"first_name":"Stefan","orcid":"0000-0002-3594-260X","id":"28836","last_name":"Krauter","full_name":"Krauter, Stefan"}],"publisher":"MDPI AG","department":[{"_id":"53"}],"publication_identifier":{"issn":["2673-9941"]},"title":"Dimensioning and Lifetime Prediction Model for a Hybrid, Hydrogen-Based Household PV Energy System Using Matlab/Simulink","_id":"35428","volume":3,"citation":{"ieee":"M. C. Möller and S. Krauter, “Dimensioning and Lifetime Prediction Model for a Hybrid, Hydrogen-Based Household PV Energy System Using Matlab/Simulink,” <i>Solar</i>, vol. 3, no. 1, pp. 25–48, 2023, doi: <a href=\"https://doi.org/10.3390/solar3010003\">10.3390/solar3010003</a>.","bibtex":"@article{Möller_Krauter_2023, title={Dimensioning and Lifetime Prediction Model for a Hybrid, Hydrogen-Based Household PV Energy System Using Matlab/Simulink}, volume={3}, DOI={<a href=\"https://doi.org/10.3390/solar3010003\">10.3390/solar3010003</a>}, number={1}, journal={Solar}, publisher={MDPI AG}, author={Möller, Marius Claus and Krauter, Stefan}, year={2023}, pages={25–48} }","ama":"Möller MC, Krauter S. Dimensioning and Lifetime Prediction Model for a Hybrid, Hydrogen-Based Household PV Energy System Using Matlab/Simulink. <i>Solar</i>. 2023;3(1):25-48. doi:<a href=\"https://doi.org/10.3390/solar3010003\">10.3390/solar3010003</a>","mla":"Möller, Marius Claus, and Stefan Krauter. “Dimensioning and Lifetime Prediction Model for a Hybrid, Hydrogen-Based Household PV Energy System Using Matlab/Simulink.” <i>Solar</i>, vol. 3, no. 1, MDPI AG, 2023, pp. 25–48, doi:<a href=\"https://doi.org/10.3390/solar3010003\">10.3390/solar3010003</a>.","chicago":"Möller, Marius Claus, and Stefan Krauter. “Dimensioning and Lifetime Prediction Model for a Hybrid, Hydrogen-Based Household PV Energy System Using Matlab/Simulink.” <i>Solar</i> 3, no. 1 (2023): 25–48. <a href=\"https://doi.org/10.3390/solar3010003\">https://doi.org/10.3390/solar3010003</a>.","apa":"Möller, M. C., &#38; Krauter, S. (2023). Dimensioning and Lifetime Prediction Model for a Hybrid, Hydrogen-Based Household PV Energy System Using Matlab/Simulink. <i>Solar</i>, <i>3</i>(1), 25–48. <a href=\"https://doi.org/10.3390/solar3010003\">https://doi.org/10.3390/solar3010003</a>","short":"M.C. Möller, S. Krauter, Solar 3 (2023) 25–48."},"user_id":"16148","language":[{"iso":"eng"}],"publication":"Solar","date_updated":"2023-01-09T06:36:10Z","type":"journal_article","quality_controlled":"1","abstract":[{"lang":"eng","text":"This paper presents a model of an energy system for a private household extended by a lifetime prognosis. The energy system was designed for fully covering the year-round energy demand of a private household on the basis of electricity generated by a photovoltaic (PV) system, using a hybrid energy storage system consisting of a hydrogen unit and a lithium-ion battery. Hydrogen is produced with a Proton Exchange Membrane (PEM) electrolyser by PV surplus during the summer months and then stored in a hydrogen tank. Mainly during winter, in terms of lack of PV energy, the hydrogen is converted back into electricity and heat by a fuel cell. The model was created in Matlab/Simulink and is based on real input data. Heat demand was also taken into account and is covered by a heat pump. The simulation period is a full year to account for the seasonality of energy production and demand. Due to high initial costs, the longevity of such an energy system is of vital interest. Therefore, this model was extended by a lifetime prediction in order to optimize the dimensioning with the aim of lifetime extension of a hydrogen-based energy system. Lifetime influencing factors were identified on the basis of a literature review and were integrated in the model. An extensive parameter study was performed to evaluate different dimensionings regarding the energy balance and the lifetime of the three components, electrolyser, fuel cell and lithium-ion battery. The results demonstrate the benefits of a holistic modelling approach and enable a design optimization regarding the use of resources, lifetime and self-sufficiency of the system"}],"date_created":"2023-01-09T06:35:00Z","issue":"1","publication_status":"published","doi":"10.3390/solar3010003","page":"25-48"}