A proposal for condition monitoring and diagnosing the operating condition of wind turbines for micro and mini distributed generation

• Grant number: 22/14479-5
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: February 01, 2023
• End date: January 31, 2024
• Field of knowledge: Engineering - Electrical Engineering - Industrial Electronics, Electronic Systems and Controls
• Principal Investigator: Andre Luis Dias
• Grantee: Willian Kenji Ishioka
• Host Institution: Instituto Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP). Campus Sertãozinho. Sertãozinho , SP, Brazil

Abstract

Intelligent fault diagnosis systems in the context of predictive maintenance represent an opportunity for small wind power generation units to improve their efficiency by ensuring they are operating under healthy conditions. The wind energy sector in Brazil has been growing steadily, with an evolution of 26.7% in 2021 compared to the previous year according to the 2022 National Energy Balance, produced by Empresa de Pesquisa Energética. It becomes increasingly interesting to develop new technologies for monitoring wind turbines, seeking to mitigate the high cost of wind farms maintenance due to unexpected turbine failures. In this context, intelligent fault diagnosis systems for predictive maintenance can increase the reliability of energy generation, avoiding production losses, unscheduled stops, increasing equipment efficiency, and reducing maintenance costs. Thus, this work proposes to investigate, implement and validate a method to diagnose operating conditions in low power wind turbines, through the analysis of the generated electric current.