State-of-the-art in integrated prognostics and health management control for utility-scale wind turbines

Abstract

Wind energy takes an important role in the transformation of the global energy system towards clean and sustainable sources. The main development of wind energy technology in recent decades is the growth of wind turbine size motivated by economic factors. The larger turbine size helps increase power output and energy efficiency, however, it leads to challenges in wind turbine operation and maintenance. To further reduce the cost of wind energy, advanced control approaches are developed focusing on power maximization, structural load mitigation, lifetime extension, and reliability improvement. This multi-objective problem is difficult to solve due to design conflicts. The optimal trade-off between goals is varying and depends on actual operating situations such as on-site wind characteristics, system aging, and grid requirements.Modern utility-scale wind turbines are equipped with numerous sensors providing useful information about turbine components’ operation status. With the development of computation capability and big data analytics techniques, the turbine performance and state-of-health (SoH) information could be obtained and evaluated through historical logged data using Prognostics and Health Management (PHM) systems. This information aids the optimal operation and maintenance of wind energy systems.The health state of a system has significant effects on its performance, reliability, and remaining useful life. So it is crucial to consider SoH when designing controllers for optimal operations. In recent years, the integration of SoH information into the closed-loop control system has begun to attract the attention of the wind energy researcher community. Controllers have been adapted based on current and future aging behaviors optimizing the trade-off between service life expansion and power production maximization. This paper provides a review of integrated prognostics and health management control (IPHMC) systems for the optimal operation and maintenance of wind turbines and wind farms reducing the cost of wind energy. The review focuses on the combination of real-time PHM and advanced control for wind turbines. The most recent developments, generalization, classification, and comparison of IPHMC approaches for wind energy systems are given. Integrated PHM control concept has the potential to improve the reliability of wind turbines, however, further research on real-time RUL prognostic and reliability evaluation techniques is required for the effective implementation of the concept.