Wind Turbine Monitoring

Introduction

With increasing demand for renewable energy sources and falling construction costs, US wind power has more than tripled over the past decade. According to the American Wind Energy Association, there are over 100 GW of wind energy with over 57,700 wind turbines operating in the US as of 2019. This also means, however, that the existing inventory of wind farms is beginning to show signs of age. The average wind turbine age in the US is 7 years, and 18 years in Europe. With an average operational life of 25 years, studies show that the wear and tear on the structures begins to increase substantially after 5 years, and quickly leads to an overall reduction in production and increase in O&M cost.

The rate of total failures of wind turbines has been increasing over the years. At least 5 turbines collapsed in the US in 2019. Structural issues appear related to rotational strain of the rotors being translated via tower structures to the foundation. This can lead to the foundation cracking or loosening in its socket over time. Total collapse can be prevented by monitoring the foundation for increasing movements and initiating remediation efforts early enough before critical damage is done. The benefit can be a substantial prolongation of the safe operational life of a turbine while minimizing risk to man and material, and also avoiding higher costs at later stages of failure.

Solutions

Canary Systems® has designed an inexpensive, easy to install, cloud-based wind turbine foundation monitoring platform. This system consists of a self-contained datalogger system (MLDAQ) with a highly sensitive biaxial tiltmeter sensor, high-speed data acquisition, cellular telemetry and power system, all integrated into a cloud-based software platform. The system simply mounts to the center of the concrete foundation block with concrete anchors and is plugged into available power. It allows for automatically comparing the rotation patterns over time and alerting staff to changes in the patterns. These could include increasing amplitude or changes in resonant frequency, and/or exceedance of defined thresholds, which can indicate possible progression in foundation instability.

Data from the tiltmeter is exported seamlessly to the cloud-based data platform MLWeb® using a cellular connection. Charts, graphs, and reports can be configured in MLWeb to show rotational stiffness in near real-time. Maps provide for an overview of multiple locations or even entire wind farms with color coded status indicators at a glance.

The platform is available as a service at a fixed monthly fee, no purchase of hardware or electronics is necessary. Installation can be included in the monthly fee or charged on a one-time basis. Additional options for power, telemetry, and adding supplemental sensors (such as strain gages) are available.