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Application of the Power Law Process in the Reliability Analysis of a Wind Farm: A Case Study Approach
Jui-Hung Liu a, Nelson T. Corbita Jr. b, Glenn B. Paclijan c and Jave Rahayne A. Bantuas d
aAssociate Professor, Intelligent Automation Engineering Department, National Chin Yi University of Technology, Taichung, Taiwan 411030
bFaculty, Mechanical Engineering Department, University of Science and Technology of Southern Philippines, Cagayan de Oro City, Philippines 9000
cFaculty, Industrial Engineering Department, Xavier University – Ateneo de Cagayan, Cagayan de Oro City, Philippines 9000
dAlumnus, Mechanical Engineering Department, University of Science and Technology of Southern Philippines, Cagayan de Oro City, Philippines 9000
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Abstract:
Wind energy is becoming increasingly popular as a clean and environmentally friendly form of renewable energy. As a result, wind turbines are being used more as a primary power source. With this, failure analysis on wind turbines is becoming necessary for large-scale wind turbines. In this study, the reliability of wind turbines is analyzed using SCADA data. To diagnose any faults in the wind turbines, the alarm data of each turbine was assessed. This allowed for a reliability analysis to determine which wind turbine is the most and least reliable, and the state of reliability of the wind farm. The results showed that the overall reliability of the wind turbines was deteriorating, with a high probability of failure observed in a relatively short time. These highlight the importance of regular maintenance and monitoring of wind turbines to ensure their continued operation and to minimize the risk of failures. This study demonstrates the value of using SCADA data and reliability analysis techniques to assess and predict the performance of wind turbines. With the increasing use of renewable energy sources such as wind power, it is important to continue researching and developing methods to improve the reliability and efficiency of these systems.
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Keywords: SCADA Data Analysis, Reliability Analysis, Wind Turbines, Power Law Process, Fault Diagnosis, Reliability Engineering
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©
2026
CSME , ISSN 0257-9731
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