Artificial Intelligence and Automatic Self-Organisation

Abstract

Maintenance and repair of offshore wind turbines out at sea is expensive and can make up 25% of the total costs of a wind farm. Artificial intelligence and automatic self-organisation can significantly reduce these costs, according to the RAVE research project Methods and Tools for Proactive Maintenance of Offshore Wind Turbines. Up to now the maintenance and repair was mostly reactive, periodic or condition-dependent. If a repair is first triggered by a malfunction, it can be too late or too expensive; due to a lack of ships, spare parts or months of poor weather. The project gathered operating data for a broad range of malfunctions and breakdowns, and developed a proactive maintenance concept with automated recommendations for action combined with expected repair times and the remaining service life of components. In future the machines will be able to trigger maintenance measures themselves depending on resource allocation and available logistics.