WIND POWER
Wind of Change
The digital transformation of wind energy by Heinrich Dyck
The share of U.S. electricity generation from wind energy has grown from less than 1 percent in 1990, to about 10.2 percent in 2022. To achieve this accomplishment over the past two decades, the wind industry had to increase the rated capacity of wind turbines by 350 percent by installing turbines in 2022 with an average capacity of 3.2 megawatts.
Figure 1: As turbines become larger, they can generate more power, but the larger size also adds complexity.
At the same time, the industry saw a 173 percent increase in the average rotor diameter to an impressive average of 131.6 meters in 2022. Yet, turbine size continues to grow. Specifically, the latest generation of offshore turbines is reaching a rated capacity between 12 and 15 megawatts, and a rotor diameter between 260 – 236 meters to optimize project cost and performance (Figure 1). These : important measurements keep the wind industry competitive with other energy sources.
The evolution of the digital twin
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Bigger wind turbines usually face higher loads and are subject to harsh environmental impacts. They require multiple sensors to ensure a safe and reliable operation within the specification during normal and extreme weather conditions. A “digital twin” is a digital map of the sensors in the field, making it possible for decisionmakers to access important data to make informed decisions (Figure 2). The density and technology of these sensors has changed dramatically over the last two decades. Turbine manufacturers
changed from low-frequency, simple digital sensors to analog sensors that measure the exact pressure, temperature, acceleration, or position. The latest generations of smart sensors even come with an integrated communication interface, such as MODBUS, PROFINET, or IO-Link, to simplify the integration and communication of complex applications. Digital tools like weather forecast and simulations provide additional external information for power predictions, maintenance planning, and safety enhancement. All these trends support the framework of the digital twin at scale. But how does this help?
Leveraging data for maximum impact
A good example of the impact was the deployment of drivetrain condition monitoring systems (CMS) in the last
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Figure 2: A digital twin gives key decision-makers access to important sensor data.
