{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T03:11:02Z","timestamp":1769569862673,"version":"3.49.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686448","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T00:00:00Z","timestamp":1769472000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,1,27]]},"abstract":"<jats:p>This study examines the integrated production of green hydrogen, electricity, and hot water utilizing geothermal energy within an Organic Rankine Cycle (ORC) system, coupled with a Proton Exchange Membrane (PEM) electrolyzer. Motivated by the need for sustainable energy solutions and decarbonization, the research addresses the technical and thermodynamic interactions involved in maximizing resource utilization from geothermal sources. Geothermal energy provides a stable, renewable input, while the system\u2019s design enables simultaneous outputs and efficient utilization of waste heat. The thermodynamic performance is modeled using mass and energy balances, with a focus on the influence of working fluid selection and system operating conditions. Results demonstrate that hydrogen yield and overall system efficiency are highly sensitive to the type of ORC working fluid and the mass flow rate of the geothermal fluid. Notably, R600 and R123 working fluids yielded superior energy and exergy efficiencies, with optimal performance observed at specific turbine inlet temperatures. The study presents a comprehensive approach to integrated energy systems, offering insights for future advancements in renewable hydrogen production and multi-output geothermal utilization.<\/jats:p>","DOI":"10.3233\/faia251711","type":"book-chapter","created":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T13:20:34Z","timestamp":1769520034000},"source":"Crossref","is-referenced-by-count":0,"title":["Thermodynamic Analysis and Performance Optimization of a Geothermal Power Plant for Sustainable Green Hydrogen Production"],"prefix":"10.3233","author":[{"given":"Ziyang","family":"Shao","sequence":"first","affiliation":[{"name":"School of Marine Technology and Environment, Dalian Ocean University, Dalian, China"}]},{"given":"Lina","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Marine Technology and Environment, Dalian Ocean University, Dalian, China"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Fuzzy Systems and Data Mining XI"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA251711","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T13:20:35Z","timestamp":1769520035000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA251711"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,27]]},"ISBN":["9781643686448"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia251711","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,27]]}}}