{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,5]],"date-time":"2026-11-05T22:31:22Z","timestamp":1793917882308,"version":"4.8.0"},"reference-count":49,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,2,23]],"date-time":"2026-02-23T00:00:00Z","timestamp":1771804800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,2,23]],"date-time":"2026-02-23T00:00:00Z","timestamp":1771804800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100002352","name":"Ain Shams University","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100002352","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    Hybrid microgrids combining photovoltaic (PV), wind turbine (WT), diesel generator (DG), and battery energy storage systems (BESS) provide a practical pathway for delivering reliable and low-carbon energy to isolated regions. However, their optimal sizing and dispatch planning constitute a challenging multi-objective problem due to renewable intermittency, battery degradation, and competing economic\u2013environmental trade-offs. This paper proposes a novel Arctic Puffin Optimization (APO)-based framework for the techno-economic planning of standalone hybrid microgrids. The model simultaneously minimizes the Annual System Cost (ASC), carbon dioxide (CO\n                    <jats:sub>2<\/jats:sub>\n                    ) emissions, and Loss of Power Supply Probability (LPSP) through integrated component sizing, dispatch optimization, and adaptive constraint handling. Two real-world case studies from Ras Ghareb, Egypt, using hourly solar, wind, and load profiles validate the proposed approach. Comparative results demonstrate that APO consistently outperforms Grey Wolf Optimizer (GWO), Ant Lion Optimizer (ALO), and Starfish Optimization Algorithm (SFOA), achieving up to 8% lower ASC, 17% higher renewable penetration, and zero LPSP while maintaining stable convergence behavior. Sensitivity analyses across varying load demands, wind speeds, irradiance levels, and generator constraints confirm the robustness of the optimized configurations. By directly incorporating emission costs and battery degradation into the objective function, the framework ensures realistic, economically viable, and environmentally responsible system design suitable for off-grid hybrid energy applications.\n                  <\/jats:p>","DOI":"10.1038\/s41598-026-37727-0","type":"journal-article","created":{"date-parts":[[2026,2,23]],"date-time":"2026-02-23T03:36:24Z","timestamp":1771817784000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Sustainable sizing, dispatch, and resilience planning of hybrid microgrids using Arctic Puffin Optimization"],"prefix":"10.1038","volume":"16","author":[{"given":"Ahmed H.","family":"Yakout","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amr S.","family":"Mashaal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adel M.","family":"Alfons","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abdelrahman M.","family":"Metwaly","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hany M.","family":"Hasanien","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Waheed","family":"Sabry","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marwa","family":"Ahmed","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,2,23]]},"reference":[{"key":"37727_CR1","unstructured":"Wang, et al. 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BOOST: A decision-support tool for PV-BESS systems. J. Power Sources 401, 540\u2013555 (2021)."},{"key":"37727_CR8","unstructured":"Alqurashi et al. Hybrid renewable system sizing using IMOEAD. IEEE Access 10, 45610\u201345623 (2022)."},{"key":"37727_CR9","unstructured":"Traor\u00e9 et al. Sizing of PV-WT microgrids using enhanced genetic algorithms. Renew. Sustain. Energy Rev. 135 (2021)."},{"key":"37727_CR10","unstructured":"Yu et al. Performance benchmarking of HHO for hybrid microgrids. Electric Power Syst. Res. 210 (2023)."},{"key":"37727_CR11","unstructured":"Bade et al. Multi-criteria sizing with biomass and fuel cells. Energy Convers. Manag. 202 (2022)."},{"key":"37727_CR12","doi-asserted-by":"crossref","unstructured":"Matsumoto et al. Aguni Island off-grid microgrid planning. IEEE Trans. Smart Grid 14, 2 (2023).","DOI":"10.1109\/TSG.2023.3265786"},{"key":"37727_CR13","unstructured":"Ahn et al. Microgrid planning for Ethiopia\u2019s remote areas. 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Grid-connected HRES sizing for reliability. Wiley Int. J. Energy Res. 46 (2022)."},{"key":"37727_CR29","unstructured":"Smith et al. Metaheuristic optimization in microgrid design: A review. ScienceDirect Energy Rep. 11 (2024)."},{"key":"37727_CR30","unstructured":"Ali et al. Limits of LPSP in Heuristic MG Models, E3S Web Conf. 315 (2024)."},{"key":"37727_CR31","unstructured":"Hassan & Youssry. Metaheuristic weaknesses in emission-reliability trade-offs. ResearchGate Preprint, 2023."},{"key":"37727_CR32","unstructured":"Ameen et al. Lack of Integrated EMS and Sizing Under Uncertainty. ResearchGate (2024)."},{"key":"37727_CR33","unstructured":"Azmy et al. POST-OPT Battery Degradation Modeling, IEEE Trans. Sustain. Energy 14(1) (2024)."},{"key":"37727_CR34","unstructured":"Fadel et al. SMOSO-based microgrid with emission degradation terms. Appl. Energy 327 (2024)."},{"key":"37727_CR35","unstructured":"Patel et al. Resilient dispatch with fixed sizing. 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