Asset health management as a tool for improving the levelized cost of wind

Introduction

Improving the levelized cost of wind energy is currently a critical challenge for the industry. One of the main issues is the optimization of a wind farm’s capacity factor by maximizing the uptime of its individual wind turbines, ensure they operate consistently and reliably for as long as possible. The reliability of individual components throughout the wind generation chain, together with the availability of spare parts is a crucial requirement. However, the digital era has now ushered in new developments in asset health management that are taking the operation, maintenance and servicing of wind turbines to the next level.

Approach

This paper presents the concept of the asset health center that collates a wide range of data collected remotely from wind turbines, as the core element for the maintenance and operation decision making process for wind farm operators.

Main body of abstract

The fact that wind turbines are both numerous and distributed across large geographical areas distant from population centers has driven the development of remote monitoring and operation solutions. Data from turbines is collated in centralized remote control centers and used by the operators to optimize production across their fleet. Over a number of years, these remote systems have established a large repository of historical information. This data is invaluable in helping to further improve the operation, maintenance and servicing of wind turbines. The availability of this data, combined with the technological trends towards digitalization and the internet of things (IoT) is making the wind industry a particularly interesting area for the development of innovative approaches to maximizing the uptime of wind turbines.

This paper presents the concept of an asset health center as the core element of the decision making process and optimization of maintenance of wind farms. It describes the principles of mapping assets on a health score map, according to their condition (measured or estimated) and their importance. This mapping process also considers the cost and time to service/repair the assets identified as the availability of service crews and tools (ships, transportation, spare parts, etc.). Therefore, the score on the asset health center map is the key enabler for optimizing maintenance of wind power plants. An example from a large utility using this concept and system for thousands of assets is then presented, highlighting its benefit sand the lessons learned.


Conclusion

Development of an asset health center that maps critical assets on a health score map offers a key enabler for the optimization of the operation and maintenance of wind farms.


Learning objectives
To show how assets are mapped onto a health score map and how this information is used to inform the planning of wind farm operation and maintenance programs. This concept is illustrated with a practical example from a large utility.