Benefits of Big Data and Machine Learning for the life cycle of wind turbines: New methods for plant monitoring offer many and various potentials across the entire value chain

摘要

To optimize their economic efficiency, the technical availability of wind turbines has to be kept at the highest possible level at low costs. Systems for the online monitoring of important operating parameters of wind turbines make consistent use of the progress of digitalization and thus of the strong points of AI methods, among other things on the basis of Big Data and Machine Learning. By intelligently analyzing data of operation management and condition monitoring, such systems not only allow to implement more cost-efficient maintenance strategies during wind farm operation but offer many and various benefits already during the development as well as in the course of the installation and commissioning of wind farms. Thus the inclusion of experiences available from monitoring installed plants from other wind farms provides valuable decision support in selecting an optimal plant type and, in addition, can significantly contribute to decreasing the levelized cost of energy. Moreover, the online monitoring of wind farms creates a valuable plant history in the form of a digital service life record that enables reliable support in assessing the residual lifetime with regard to the ongoing operation. The potentials of the solutions described in this paper thus range across the entire life cycle of wind turbines, from the development of the wind farm right up to the ongoing operation of the plants after the 20th year of operation.