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Volume 55 Issue 1
Jan.  2020
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Article Contents
Journal of Southwest Jiaotong University  > 2020  >  55(1): 1-8.
ZHU Qing, ZENG Haowei, XIE Xiao, ZHANG Yeting, JIANG Jie. Key Technologies in Visualized Intelligent Management Platform for Life Cycle of Wind Power Systems[J]. Journal of Southwest Jiaotong University, 2020, 55(1): 1-8. doi: 10.3969/j.issn.0258-2724.20180721
Citation: ZHU Qing, ZENG Haowei, XIE Xiao, ZHANG Yeting, JIANG Jie. Key Technologies in Visualized Intelligent Management Platform for Life Cycle of Wind Power Systems[J]. Journal of Southwest Jiaotong University, 2020, 55(1): 1-8. doi: 10.3969/j.issn.0258-2724.20180721
shu

Key Technologies in Visualized Intelligent Management Platform for Life Cycle of Wind Power Systems

doi: 10.3969/j.issn.0258-2724.20180721
  • Received Date: 27 Aug 2018
  • Rev Recd Date: 19 Oct 2018
    • Available Online: 24 Oct 2018
  • Publish Date: 01 Feb 2020
    Abstract
  • For years, each sector in the wind farm life cycle has used separate management systems, which results poor data sharing and low levels of intelligent automation. It is difficult to achieve comprehensive and efficient management of whole space and full information in wind power systems. To deal with this problem, we analyzed the relationship and characteristics of geographic environments data, facilities, and all sector operations in wind power systems, study the key technologies of different types of spatio-temporal data sharing, multi-sector and multi-service collaboration, and visualized intelligent management in the life cycle of wind power systems. A visualized intelligent management platform based on the 3D GIS (geographic information system) technology was designed and developed. This platform includes functional modules such as real-world data management, planning and design management, dynamic construction supervision, and intelligent operation and maintenance management. It integrates various professional applications and runs through the life cycle in wind power system, and provides efficient decision support for the collaborative planning, construction, operation and maintenance of wind power systems. The platform is tested and verified by a typical wind farm.

     

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