Special Session X: Intelligent Monitoring and Control of Wind Turbines 风电装备智能监测与控制
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Session Chair: Prof., Zhaohua Liu, Hunan University of Science and Technology, China |
Co-Chair: Prof., Shuaishuai Wang, Ocean University of China, China |
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Technology, China |
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Summary:
With the continuously growing global demand for clean energy, wind power generation, as a sustainable energy solution, is playing an increasingly important role in the energy mix. Intelligent monitoring and control of wind power serves as a vital approach and inevitable choice for the transformation, upgrading, cost reduction and efficiency improvement of the wind power industry, and also lays the foundation for realizing the informatization and intelligence of the energy internet. Alongside the rapid advancement of wind power technologies and continuous expansion of wind farm scales, how to effectively apply big data and artificial intelligence technologies to conduct system modeling, condition monitoring, fault diagnosis and optimal control of wind turbines has become critical to boosting wind power efficiency and cutting operation and maintenance costs. This forum thoroughly discusses specific research and applications of electrical, electronic and information engineering technologies in wind turbine monitoring and diagnosis, power prediction, intelligent operation and maintenance and other fields. It gathers research expertise from the wind power sector and facilitates industry-university-research collaboration, aiming to provide theoretical and technical support as well as achievement transformation for advancing the intelligent development of the wind power industry.
随着全球对清洁能源需求的不断增长，风力发电作为一种可持续的能源解决方案，在能源结构中的地位愈发重要。风电智能监测与控制是当前风电行业转型升级和降本增效的重要路径和必然选择，更是实现能源互联网化与智能化的基础。随着风力发电技术的快速发展和风电场规模的不断扩大，如何有效利用大数据和人工智能技术对风电机组进行系统建模、状态监测、故障诊断和优化控制，成为提高风电效率和降低运维成本的关键。本分论坛深入探讨电气、电子与信息工程技术在风电机组监测与诊断、功率预测、智能运维等方面的具体研究应用，汇聚风电界科研智慧，促进产学研协同，旨在为推动风电行业的智能化发展提供理论技术支撑和成果转化。
Topics of interest include, but are not limited to:
(1) Wind power system modeling and operation characteristics analysis （风电系统仿真建模与运行特性分析）
(2) Visual inspection of wind turbine blades （风电叶片视觉检测）
(3) Multimodal data processing for wind power （风电多模态数据处理）
(4) Multi-objective coordinated control of offshore wind turbines （海上风电机组多目标协调控制）
(5) Intelligent operation and maintenance of offshore wind turbines （海上风电机组智能运维）
(6) Condition monitoring and fault diagnosis of wind turbines （风电机组状态监测与故障诊断）
Keywords:
Wind Power Generation （风力发电）
Intelligent Monitoring （智能监测）
Fault Diagnosis （故障诊断）
Intelligent Control （智能控制）
Information Processing （信息处理）
System Modeling （系统建模）
Submission Deadline: September 10, 2026
Participant: Lecture, Bisheng Wen,