Looking for the Swiss Wind Energy R&D Network? We’ve moved to www.windenergynetwork.ch
Looking for the Swiss Wind Energy R&D Network? We’ve moved to www.windenergynetwork.ch
Looking for the Swiss Wind Energy R&D Network? We’ve moved to www.windenergynetwork.ch
Looking for the Swiss Wind Energy R&D Network? We’ve moved to www.windenergynetwork.ch
October 26th, 2023

Introducing our new Static Yaw Misalignment Analysis Challenge

As part of our Open Data Exploration (ODE) space, we are pleased to introduce our new challenge, the Static Yaw Misalignment Analysis Challenge, in collaboration with the OpenOA team, Eric Simley, Rob Hammond and Jordan Perr-Sauer, at the National Renewable Energy Laboratory in the US.

Increasing Wind Turbine Efficiency with Data-Driven Insights

This challenge aims to harness the power of data science to optimise wind turbine performance by analysing static yaw misalignment. Contributed by Cubico Sustainable Investments, the datasets of two wind farms, Kelmarsh and Penmanshiel, offer an ideal base for innovative approaches to yaw analysis.
The academic community will benefit from this challenge by gaining an opportunity to work with SCADA data, delve into the OpenOA wind plant operational assessment framework, and contribute to state-of-art analysis that can be utilised by industry. Meanwhile, ongoing research can capitalise on model variations to track parameters and visualise their effects. For the industry, the reward is an increase in energy conversion efficiency through the extraction of actionable insights into the most profitable static yaw error correction for individual turbines.

Static yaw misalignment and its impact on wind turbine performance

The goal of this challenge is to analyse static yaw misalignment and its impact on wind turbine performance using SCADA data from two different wind farms, Kelmarsh and Penmanshiel, contributed by Cubico Sustainable Investments. Participants have the freedom to choose their analytical methods but must produce specific interim results, focusing on wake-free zones within the wind farms. The challenge aims to deepen the understanding of static yaw misalignment and encourage a rich discourse on the topic among various stakeholders.
The challenge is split into the following parts, for which results for each turbine in a wake free zone should be submitted:
  • Part 1: Calculate the static yaw misalignment angle (the average yaw misalignment relative to the true wind direction) per wind speed bin, complete with a 95% confidence interval.
  • Part 2: Calculate the average static yaw misalignment over all wind speed bins weighted by the wind speed frequencies.
  • Part 3: Calculate the energy capture loss (by comparing the energy conversion with static yaw misalignment and the estimated energy that would have been produced with zero static yaw misalignment).
  • Part 4: Provide a comprehensive explanation of the method or model chosen for the analysis, including a detailed account of the data filtering process employed (i.e. power curve filtering, pitch threshold filtering, wake free zone analysis or other methods used).
The analysis will rely on data from two wind farms:
1. Kelmarsh: This wind farm has 6 wind turbines and serves as a rich source of data patterns for static yaw misalignment.
2. Penmanshiel: This wind farm SCADA consists of 14 wind turbines and provides an alternative set of data.
While the use of OpenOA's extensive documentation is encouraged as a starting point for gathering and processing SCADA data of both wind farms, it is not a requirement for participation in the challenge. OpenOA also offers a yaw_misalignment tool, which could be advantageous for testing various parameters.
Example of an analysis with OpenOA's yaw misalignment tool

More about OpenOA

NREL's Open Operational Assessment (OpenOA) software helps the wind energy community assess the performance of operating wind plants. To share resources and increase consistency across the industry, the OpenOA software, which launched in 2019, was developed to act as an open-source library for assessing operational wind plant performance by providing reference implementations of important operational data structures and analytics methods. A first-of-its-kind resource, OpenOA is intended to provide a central hub for knowledge sharing and collaboration among wind energy industry researchers, wind plant owners and operators, and wind energy data analysts, helping to standardize operational analyses of wind power plants. OpenOA consists of modules for organizing different types of data, low-level data analysis (e.g., filtering, power curve fitting) toolkits, and high-level operational assessment methods.
Read more here.

More about the ODE space

The Open Data Exploration space is a safe discussion space for open data exploration in connection with wind farm planning and operation run by Charlie Plumley. It was originally focused on just the wind farm SCADA data at the Penmanshiel and Kelmarsh sites published by Cubico Sustainable Investments, but now we are expanding to other open data sets.
You can read more about the ODE space below:

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