{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T22:13:40Z","timestamp":1767910420315,"version":"3.49.0"},"reference-count":52,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T00:00:00Z","timestamp":1760659200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>The global transition to a low-carbon energy system requires innovative solutions that integrate renewable energy production with storage and utilization technologies. The growth in energy demand, combined with the intermittency of these sources, highlights the need for advanced management models capable of ensuring system stability and efficiency. This paper presents the development of an optimized energy management system integrating renewable sources, with a focus on green hydrogen production via electrolysis, storage, and use through a fuel cell. The system aims to promote energy autonomy and support the transition to a low-carbon economy by reducing dependence on the conventional electricity grid. The proposed model enables flexible hourly energy flow optimization, considering solar availability, local consumption, hydrogen storage capacity, and grid interactions. Formulated as a Mixed-Integer Linear Programming (MILP) model, it supports strategic decision-making regarding hydrogen production, storage, and utilization, as well as energy trading with the grid. Simulations using production and consumption profiles assessed the effects of hydrogen storage capacity and electricity price variations. Results confirm the effectiveness of the model in optimizing system performance under different operational scenarios.<\/jats:p>","DOI":"10.3390\/a18100656","type":"journal-article","created":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T10:28:36Z","timestamp":1760696916000},"page":"656","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Optimizing Renewable Microgrid Performance Through Hydrogen Storage Integration"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-5745-7776","authenticated-orcid":false,"given":"Bruno","family":"Ribeiro","sequence":"first","affiliation":[{"name":"Department of Engineering, University of Tr\u00e1s-os-Montes and Alto Douro, 5000-801 Vila Real, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0297-4709","authenticated-orcid":false,"given":"Jos\u00e9","family":"Baptista","sequence":"additional","affiliation":[{"name":"Department of Engineering, University of Tr\u00e1s-os-Montes and Alto Douro, 5000-801 Vila Real, Portugal"},{"name":"INEC-TEC UTAD Pole, University of Tr\u00e1s-os-Montes and Alto Douro, 5000-801 Vila Real, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7494-6566","authenticated-orcid":false,"given":"Adelaide","family":"Cerveira","sequence":"additional","affiliation":[{"name":"INEC-TEC UTAD Pole, University of Tr\u00e1s-os-Montes and Alto Douro, 5000-801 Vila Real, Portugal"},{"name":"Department of Mathematics, University of Tr\u00e1s-os-Montes and Alto Douro, 5000-801 Vila Real, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2025,10,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"392","DOI":"10.1016\/j.est.2019.03.001","article-title":"Advances in alkaline water electrolyzers: A review","volume":"23","author":"David","year":"2019","journal-title":"J. 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