Innovation in wind energy modeling approaches need not come at the expense of the trust of project developers and investors, according to Vaisala, a global leader in environmental and industrial measurement and provider of energy assessment and due diligence services. In fact, ongoing refinements to methodology, which are critical in enhancing overall accuracy and reliability, can be implemented in such a way that maintains stability and confidence for the wind development community
"Wind project developers and investors rely on energy assessment consultants to predict the power output of proposed wind farms. They require both a high level of confidence in the numbers reported and for these estimates to be as accurate as possible," said Matthew Hendrickson, Head of Energy Operations, Vaisala.
"But these two requirements can be at odds with one another. Confidence demands a high level of comfort with a stable methodology, while accuracy demands innovation to drive continual improvement. The question is, how can these needs be reconciled to keep the industry moving in the right direction?"
Creating transparency through continuous validation
In a briefing, Vaisala demonstrates how its continuous validation process makes it possible for the company to achieve both stability and innovation simultaneously. The document discusses the advantages of Vaisala's rigorous validation philosophy and outlines updated results demonstrating the current accuracy of its wind assessment approach.
Vaisala's initial global wind assessment validation study, which was released in December 2015, proved the reliability of its unique numerical weather prediction (NWP) modeling technique. The study remains one of the industry's largest, including 30 operational wind farms and data spanning 127 wind farm years. It illustrated the low bias error of Vaisala's methodology, which applies the latest advances in weather science to wind energy modeling.
With the release of the 2015 validation paper, the company pledged to constantly evolve its approach by incorporating cutting-edge science while also remaining transparent about the skill of its wind assessment methodology and its ability to deliver stable results to clients. To show its commitment to this pledge, Vaisala has made a significant investment in developing and implementing its ground-breaking continuous validation process.
The process allows the company to evaluate proposed advancements to its methodology by testing new techniques against its entire validation database. This is accomplished through automation, requiring 600,000 core hours of computing power and generating 8TB of data output, which is analyzed and compared to previous validation results. The process fully leverages Vaisala's state-of-the-art computing infrastructure, the world's largest commercial data center dedicated to renewable energy.
Measuring the impact of methodology changes
This systematic approach allows Vaisala's analysts to measure the effects of new process changes on subsequent energy estimates. Through its rigorous validation process, Vaisala can easily differentiate between process changes that actually add value and produce more accurate results, from those that may seem beneficial, but ultimately introduce increased bias error and uncertainty or have other unintended consequences.
Pascal Storck, Head of Renewable Energy at Vaisala, further commented: "By analyzing the exact impact of any proposed advancement to our assessment methodology and what it might mean for our clients in practice - and by providing full transparency of the process - we're aiming to maintain the industry's trust in our approach to innovation, without affecting the stability of our results."
As a part of this ongoing validation process, today Vaisala released the most recent version of its validation histogram, which illustrates its low bias error of +0.7% and uncertainty levels of 8.8%. This latest validation is also an expansion from the previous version and includes 143 wind farm years.
Core components of Vaisala's industry-leading wind assessment methodology:
Approach driven by NWP models based on the most advanced weather science
Industry's highest spatial resolutions and longest simulation time periods
Advanced techniques for integrating measurements in the time domain
Sophisticated climate ensemble analysis, downscaling all major reanalysis datasets
Proprietary energy risk framework accounting for full propagation of uncertainty
Vaisala | http://www.vaisala.com/energy