인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Abstract This paper presents a new and multidisciplinary systematic analysis of floating photovoltaic (FPV) systems that integrates recent advances in computational modelling and intelligent optimization to address persistent issues with performance, hydrodynamics, and adaptability. The review is organized according to five main goals: (i) to publish experimental and empirical results in FPV literature; (ii) to develop a unified computational approach that combines CFD and ML; (iii) to assess system improvements through multi-scale hydrodynamic modelling and AI-driven adjustments; (iv) to introduce the Bidirectional Conceptual Feedback Loop (BCFL) as a dynamic optimization model; and (v) to develop a scalable, climate-resilient FPV model for the global energy transition. Scopus, Web of Science, Google Scholar, ScienceDirect, SpringerLink, and Taylor & Francis were the sources of 404 research publications in all. 189 high-impact publications were found through a careful curation of online databases, with a focus on computational innovations, machine learning (ML)-based optimization, and hydrodynamic analysis. Following a strict inclusion and exclusion process and using Mendeley reference management software to remove duplicate records during the screening stage, authors evaluated a collection of high-impact literature, technology developments, and verified empirical data related to mooring systems, wave-wind interactions, structural stability, predictive analytics, and digital twin environments. According to the synthesis, real-time adaptation, predictive defect detection, and optimized energy yield are made possible by the clever fusion of CFD and ML, especially in dynamic aquatic environments. In order to meet the demands of both climate resilience and the scaling of renewable energy, FPV platforms must become cyber-physical, self-optimizing systems. This paper introduces a paradigm shift by using a methodical and theoretical approach to review and incorporate empirical research, advanced simulation, and AI-driven system intelligence. Future FPV development can be revolutionized by the proposed BCFL paradigm, which makes it easier to move from isolated innovation to integrative, flexible, and globally replicable FPV system design.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
최근 본 자료 전체보기
