Presentation Description: Yaw error and its impact on turbine performance has been an investigation topic for many years. Progress has been relatively slow due to lack of robust theoretical foundation and accurate field measurements.
In 2014, one of the co-authors, Francis Pelletier, patented a means of accurately aligning nacelle wind vanes with a high degree of accuracy and repeatability (US 61/720,145). This was considered the first step towards investigating the optimal yaw angle for maximizing energy output.
Yaw error has now become a mainstream industry concern and various means of measuring and correcting it are being proposed, notably by using nacelle-mounted lidars. More recently, there have been claims about data-driven methodologies that could address the issue with SCADA data alone.
Leveraging a database of 15+ GW of operational wind power plants in North America, data-driven approaches were investigated using various methodologies and time scales ranging from 1-minute to the industry-standard 10-minute averages.
Both accurate yaw error measurement and optimal yaw offset determination were thoroughly investigated. The study showed the requirements and limits of data-driven approaches. In addition, analyses were pushed to include detailed on-site action plans to test the findings.
The presentation provides an accurate and state-of-the-art framework rooted in robust field data for owners and operators planning to tackle yaw optimization at their wind power plant.
Upon completion, participants will be able to compare state-of-the-art approaches for yaw optimization and their applicability in specific cases based on field experience.
Upon completion, participants will be able to distinguish between various approaches offered in the market to implement a yaw optimization plan. The presentation will notably provide critical decision-making criteria such as precision and accuracy, SCADA data availability and operational constraints.
Upon completion, participants will be able to establish a business case for implementing a yaw optimization plan. The plan should include diagnostics, gap analysis, and feasibility as detailed in the presentation.