Zhen Xie , Zhongwei Lin , Qinlin Cai , Zhenyu Chen
{"title":"Aerodynamic reconstruction of wind turbines using terrestrial laser scanning: Methodology, validation, and error analysis","authors":"Zhen Xie , Zhongwei Lin , Qinlin Cai , Zhenyu Chen","doi":"10.1016/j.enconman.2025.119792","DOIUrl":null,"url":null,"abstract":"<div><div>Aerodynamic performance analysis is essential for improving wind turbine efficiency and reliability, yet it is often constrained by the lack of aerodynamic models, either due to commercial confidentiality or the legacy turbine types. This study proposes a novel method for aerodynamic reconstruction of wind turbines using Terrestrial Laser Scanning (TLS). The method allows for efficiently capturing turbine geometry and aerodynamic properties without requiring blade disassembly. The specific procedures, including TLS-based data acquisition, data preprocessing, and blade parameterization, are outlined systematically to demonstrate the complete framework. A field implementation on a 2 MW commercial wind turbine proved its effectiveness, with validation against historical data and manufacturer-supplied performance curves showing strong consistency. Challenges such as blade twist variations and wind speed measurement inaccuracies are analyzed as potential error sources, and strategies for enhancing precision and reliability are provided. The proposed method offers a competitive, engineering-oriented solution for wind turbine aerodynamic reconstruction, laying a foundation for enhanced turbine design, operational efficiency, and long-term performance optimization.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"334 ","pages":"Article 119792"},"PeriodicalIF":9.9000,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Conversion and Management","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0196890425003152","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
Aerodynamic performance analysis is essential for improving wind turbine efficiency and reliability, yet it is often constrained by the lack of aerodynamic models, either due to commercial confidentiality or the legacy turbine types. This study proposes a novel method for aerodynamic reconstruction of wind turbines using Terrestrial Laser Scanning (TLS). The method allows for efficiently capturing turbine geometry and aerodynamic properties without requiring blade disassembly. The specific procedures, including TLS-based data acquisition, data preprocessing, and blade parameterization, are outlined systematically to demonstrate the complete framework. A field implementation on a 2 MW commercial wind turbine proved its effectiveness, with validation against historical data and manufacturer-supplied performance curves showing strong consistency. Challenges such as blade twist variations and wind speed measurement inaccuracies are analyzed as potential error sources, and strategies for enhancing precision and reliability are provided. The proposed method offers a competitive, engineering-oriented solution for wind turbine aerodynamic reconstruction, laying a foundation for enhanced turbine design, operational efficiency, and long-term performance optimization.
期刊介绍:
The journal Energy Conversion and Management provides a forum for publishing original contributions and comprehensive technical review articles of interdisciplinary and original research on all important energy topics.
The topics considered include energy generation, utilization, conversion, storage, transmission, conservation, management and sustainability. These topics typically involve various types of energy such as mechanical, thermal, nuclear, chemical, electromagnetic, magnetic and electric. These energy types cover all known energy resources, including renewable resources (e.g., solar, bio, hydro, wind, geothermal and ocean energy), fossil fuels and nuclear resources.