Digital twins in renewable energy systems: A comprehensive review of concepts, applications, and future directions

Basit Öğe Kaydı
dc.authorid0000-0002-1024-8822
dc.authorid0000-0002-4353-1261
dc.authorid0000-0001-6944-4775
dc.authorid0000-0002-4049-0716
dc.contributor.authorMbasso, Wulfran Fendzi
dc.contributor.authorHarrison, Ambe
dc.contributor.authorDagal, Idriss
dc.contributor.authorJangir, Pradeep
dc.contributor.authorKhishe, Mohammad
dc.contributor.authorKotb, Hossam
dc.contributor.authorShaikh, Muhammad Suhail
dc.date.accessioned2026-01-31T15:08:17Z
dc.date.available2026-01-31T15:08:17Z
dc.date.issued2025
dc.departmentİstanbul Beykent Üniversitesi
dc.description.abstractDigital Twin (DT) technologies are rapidly transforming the design, operation, and lifecycle management of renewable energy systems. This systematic review investigates DT applications across four major renewable energy domains-solar, wind, hydro, and hybrid systems-encompassing all lifecycle phases from initial design and simulation to maintenance and end-of-life (EoL) optimization. Using a PRISMA-guided methodology and keyword-driven thematic classification, the study analyzes over 150 peer-reviewed and industry-sourced publications from 2014 to 2024. A novel taxonomy is introduced to categorize DT applications by energy type and lifecycle phase, offering a structured and comprehensive perspective on current practices and research directions. The review synthesizes enabling technologies within a layered DT architecture, highlighting the roles of Artificial Intelligence (AI), Internet of Things (IoT), cloud/edge computing, and big data in realizing scalable, intelligent, and autonomous systems. Real-world deployments-such as GE's Digital Wind Farm and Huawei's DT-enhanced solar inverters-demonstrate tangible benefits, including up to a 25 % reduction in downtime and 10-20 % improvements in energy yield. Key challenges are critically examined, including model fidelity, data heterogeneity, standardization, and cybersecurity. In response, the study outlines a forward-looking agenda aligned with global sustainability frameworks such as the UN Sustainable Development Goals (SDGs) and the EU Green Deal. By integrating fragmented literature into a coherent, application-driven framework, this work advances academic understanding, supports industrial innovation, and informs policy development for the next generation of intelligent renewable energy systems.
dc.identifier.doi10.1016/j.esr.2025.101814
dc.identifier.issn2211-467X
dc.identifier.issn2211-4688
dc.identifier.scopus2-s2.0-105012295205
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org./10.1016/j.esr.2025.101814
dc.identifier.urihttps://hdl.handle.net/20.500.12662/10647
dc.identifier.volume61
dc.identifier.wosWOS:001545747300001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier
dc.relation.ispartofEnergy Strategy Reviews
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WoS_20260128
dc.subjectCameroon
dc.subjectDigital Twin
dc.subjectRenewable energy systems
dc.subjectPredictive maintenance
dc.subjectReal-time monitoring
dc.subjectCyber-physical systems
dc.subjectArtificial intelligence
dc.titleDigital twins in renewable energy systems: A comprehensive review of concepts, applications, and future directions
dc.typeReview Article

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