Article: An artificial intelligence wind power equipment operation and maintenance system and method using big data Journal: International Journal of Global Energy Issues (IJGEI) 2026 Vol.48 No.1/2 pp.138 - 154 Abstract: With the continuous exploitation of fossil fuels, the reserves of this non-renewable energy source are increasingly being consumed. To alleviate the energy crisis and the environmental problems caused by fossil energy, wind power is now forming a boom in the world. However, the distribution of wind turbine units is relatively scattered, with each unit being far apart. Moreover, the cabins of wind turbines are mostly located at a height of several tens of metres, making traditional manual maintenance very difficult. The Artificial Intelligence (AI) wind power equipment Operation and Maintenance (O&M) system can display various technical indicators of the operation of each generator unit in real-time through Big Data (BD) technology, which plays an essential and positive role in reducing the O&M risks of O&M personnel and improving O&M efficiency. This article studied the O&M system and methods of wind power equipment using BD AI technology. The final experimental results showed that the wind power equipment O&M system using BD AI technology had an average maintenance difficulty score of 95.817 points, average maintenance duration of 4.208 hours and an average maintenance cost of 146,300 US dollars, which had significant advantages compared to traditional manual maintenance. Inderscience Publishers - linking academia, business and industry through research

Title: An artificial intelligence wind power equipment operation and maintenance system and method using big data

Authors: Tao Feng; Chaodong Wang; Zhishuai Zheng

Addresses: China Green Development Investment Group, Beijing, China ' Xuchang XJ Wind Power Technology Co., Ltd., Xuchang, Zhengzhou, China ' Xuchang XJ Wind Power Technology Co., Ltd., Xuchang, Zhengzhou, China

Abstract: With the continuous exploitation of fossil fuels, the reserves of this non-renewable energy source are increasingly being consumed. To alleviate the energy crisis and the environmental problems caused by fossil energy, wind power is now forming a boom in the world. However, the distribution of wind turbine units is relatively scattered, with each unit being far apart. Moreover, the cabins of wind turbines are mostly located at a height of several tens of metres, making traditional manual maintenance very difficult. The Artificial Intelligence (AI) wind power equipment Operation and Maintenance (O&M) system can display various technical indicators of the operation of each generator unit in real-time through Big Data (BD) technology, which plays an essential and positive role in reducing the O&M risks of O&M personnel and improving O&M efficiency. This article studied the O&M system and methods of wind power equipment using BD AI technology. The final experimental results showed that the wind power equipment O&M system using BD AI technology had an average maintenance difficulty score of 95.817 points, average maintenance duration of 4.208 hours and an average maintenance cost of 146,300 US dollars, which had significant advantages compared to traditional manual maintenance.

Keywords: big data; artificial intelligence; wind power generation; operation and maintenance systems.

DOI: 10.1504/IJGEI.2026.150723

International Journal of Global Energy Issues, 2026 Vol.48 No.1/2, pp.138 - 154

Received: 16 May 2024
Accepted: 26 Nov 2024
Published online: 22 Dec 2025 *

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Title: An artificial intelligence wind power equipment operation and maintenance system and method using big data

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