- Details
- Category: Articles
Minimising Environmental Impact and Preventing Energy Loss
During wind turbine operation, the gearbox, generator and rotor blades generate noise that is emitted to the environment. The noise from the rotor blades is mainly caused by air turbulence at their trailing edge and blade tip. These operating noises can be perceived as disturbing by residents. Reducing them to a minimum therefore plays an important role in the acceptance of wind energy in the population. This article describes ways of reducing noise at wind turbines using the example of a multimegawatt wind farm in Germany. The focus is on the blade angle adjustment, which ultimately led to compliance with the limit values.
By Martin Peters, Head of Measurement Department, Green Wind Engineering, Germany
- Details
- Category: Articles
Enhancing Efficiency and Sustainability Through Digital Innovation
With advancements in digitalisation and computational power, data-driven design unlocks new possibilities for optimising wind turbine foundations. Traditional design methods rely on predefined specifications and limited iterations, often leading to conservative and suboptimal solutions. These methods take time for adjustments and can lead to increased material use and costs.
By Chris van der Ploeg, Digital Innovation Lead, Windbase, the Netherlands
- Details
- Category: Articles
Resurgent Technology Can Maintain Grid Stability in the Renewable Era
Renewables are taking over, but they are shaking up grid stability. As fossil fuel plants shut down, we are also losing the vital inertia they provide. The result? A hidden engineering challenge that undermines the reliability of clean power.
By Kristina Carlquist, Head of Synchronous Condenser Product Line, ABB Large Motors and Generators, Sweden
- Details
- Category: Articles
The Role of Continuous Thermal Imaging in Detecting Faults and Reducing Risks
Wind turbines are a critical pillar of renewable energy production, yet they routinely encounter significant operational risks, including overheating, electrical fires, and arc-flash incidents within their nacelle environments. These issues not only threaten the reliability of energy output, they also endanger maintenance personnel, increase operational costs, and contribute to lengthy downtime. Traditional methods of diagnosing these hazards, while long relied upon, are often dangerous, inefficient and prone to data inaccuracies. In response to these persistent challenges, Puget Sound Energy transitioned from conventional diagnostic methods to an advanced, fixed, bispectral infrared camera solution, fundamentally transforming its approach to wind turbine maintenance. This article explores how the adoption of this technology resulted in substantial improvements in technician safety, operational efficiency, real-time diagnostics, and proactive failure prevention, ultimately reshaping best practices for wind energy infrastructure maintenance.
By Troy Goss, Project Manager, Sytis, USA
- Details
- Category: Articles
Load Reduction and Anchor Sharing for Floating Wind Farms
Honeymooring is a grid solution for sustainable planning of floating wind farms. It is cost-effective, environmentally friendly, and enables coexistence with other ocean users. This article describes the technical principles and components of the system and reflects on the developments needed to industrialise it.
By Kasper Sandal, Engineering Specialist, Semar, Norway
- Details
- Category: Articles
Turning Blurry Wind Data into Crystal-Clear Insights
Deep learning has been a game changer in many industries, from autonomous vehicles to natural language processing. Now, this powerful technology is making waves in the renewable energy sector, specifically in the creation of high-resolution wind resource maps using super-resolution models. These maps are vital for wind farm developers to optimise turbine placement and accurately estimate energy production.
By Mike Optis, Veer Renewables, and Jacob Schnell, University of Waterloo, Canada
- Details
- Category: Articles
Utilising Bi-Wave Ultrasonics and Machine Learning
Maintaining bolt preload is critical to ensure the structural integrity of a wind turbine. Current non-destructive testing approaches for estimating bolt tension, such as ultrasonic elongation measurements, are impractical on a large scale for new and in situ bolts. However, the limitations of elongation measurement techniques (untensioned baseline measurements, compounding errors from material and environmental variation, and complex calibrations) can be overcome by combining bi-wave ultrasonics technology and machine learning.
By Joshua Scott, Director of Research and Innovation, Predictant, USA
