Progress and challenges on blade load research of large-scale wind turbines

Juchuan Dai, Mimi Li, Huanguo Chen, Tao He and Fan Zhang

Renewable Energy, 2022, vol. 196, issue C, 482-496

Abstract: Load identification is the premise of wind turbine blade design and control. In wind farms, due to the lack of a thorough understanding of the blade loads, catastrophic accidents occur occasionally, and the causes of some accidents cannot be reasonably explained. To further promote the depth of blade load research and application, the development of the blade industry, load theory, load measurement, and load control of large-scale Horizontal Axis Wind Turbines (HAWTs) are comprehensively reviewed in this paper. The key issues and the corresponding progress involved in the blade research and application are discussed in detail, covering aerodynamic load calculation and analysis, load measurement in both laboratory and field environments, and load control of wind turbine blades. Additionally, the main matters needing attention in the blade research and application in the future are outlined, including more accurate and faster load calculation, strain perception and load mapping in the field, reconstruction of historical service load, and time-history optimization of the load control algorithm. Some effective countermeasures, e.g., reconstructing the historical service loads on wind turbine blades with the help of both blade load sensors and the Supervisory Control and Data Acquisition (SCADA) system, are also proposed.

Keywords: Blade load; Wind turbines; SCADA data; Wind farm (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:196:y:2022:i:c:p:482-496

DOI: 10.1016/j.renene.2022.07.017

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