INEGI wants to make wind turbine life management more «intelligent»

A new project, led by INEGI, is underway to develop tools for intelligent management of the useful life of structural components of wind turbines.

With the aim of improving efficiency and prolonging the useful life of equipment, INEGI's team is exploring the application of monitoring, modeling and machine learning technologies to estimate the fatigue life consumed by wind farms, with minimal instrumentation, quantify the impact of key factors on fatigue loads, and enable «smart» management of its service life.

The project is seen as an important initiative to support the energy transition and meet the goals established at national level, which aim to reach 47% of energy from renewable sources in gross final energy consumption by 2030.

As Silvina Guimarães explains, "when we talk about increasing the installed capacity of wind energy, the installation of new wind turbines must be combined with careful management of the existing infrastructure. Given that the time for decommissioning the main components is determined by fatigue, managing operational life of wind turbines becomes an important factor to increase its useful life”.

The M4WIND project – Monitoring, Modeling and Machine Learning for managing the operating time of wind farms is co-financed by FCT - Fundação para a Ciência e Tecnologia. The consortium also comprises the University of Porto, IDMEC – Institute of Mechanical Engineering, and Ventient Energy Serviços.