How the Triton Quality Factor Helps You Grade Your Data

Built into the firmware of Second Wind’s Triton is a powerful tool that helps you understand your wind data more quickly; allows you to view it more flexibly; and improves the credibility of the data with analysts and independent engineers. Called the Quality Factor, this powerful set of algorithms tags each wind measurement so it can be interpreted and understood both within the SkyServe wind data portal environment and by later analysts. What makes the Quality Factor so powerful, and how can you use it to save time and money?

To understand what makes the Quality Factor powerful, it helps to understand how other wind measurement systems deal with sources of uncertainty. Even though anemometry is still the gold standard by which remote sensing systems are judged, anemometer and vane data do have sources of error, ranging from mechanical failure of the sensors to deadband interpretation, icing, tower shadow, and more. Two anemometers mounted at the same location will not always agree with each other. Remote sensing systems also have known sources of uncertainty, mostly involving the interference of environmental factors and ambient conditions.

To lessen the impact of these discrepancies on a wind resource report, analysts use various methods of filtering or scrubbing the data. With the exception of Triton, no wind measurement system on the market has an algorithmic method of measuring data quality as it relates to the known sources of uncertainty. Anemometry data is analyzed by well-established consultants, using programs and methods that vary depending upon who is doing the analysis. Many sodars and lidars in the market have published quality standards that relate to data recovery, but. these standards only serve as marketing claims. Data recovery statistics are also cited in individual wind measurement reports. But these only answer the question "How much is in the bucket?" They do not qualify the data or provide any method for judging its validity.

Triton's Quality Factor was developed to give everyone from wind developers through investors a way to measure the wind data against the known sources of bias. Data recovery statistics tell you how much data you've gathered. The Quality Factor tells you something about the confidence you should assign to the data. In other words, "What is in the bucket?" 

Looking Under The Hood

Triton's Quality Factor operates at the firmware level. For each chirp the Triton sends out, it hears an echo. Each echo is analyzed for quality, primarily signal-to-noise ratio (SNR, which compares the environmental noise to the strength of the echo). Based upon the average SNR of all the chirps sent out during a ten-minute interval, Triton tags each ten-minute average with a Quality Factor number.

Triton sends its ten-minute averages to SkyServe so that you can see your wind data in near-real-time. Each ten-minute average is tagged with the Quality Factor number, and you use SkyServe to filter out data that you don't want to see. It's important to note that neither Triton nor SkyServe use the Quality Factor to change or discard any data. You simply choose what to display or hide based upon your preference. For example, if you set the Quality Factor to 90% in SkyServe, you will see only the data tagged with a Quality Factor number above 90%. It's like only allowing the "A" students to participate in a classroom survey.

How You Can Use Quality Factor To Get Better Returns

Looking at wind data can be confusing. SkyServe's graphical reporting tools already make it easier by displaying Triton data in a similar format to anemometry data. Choosing a Quality Factor threshold allows you to understand how much data you have that is good for a certain purpose. This allows you to make quick judgements about whether a measurement campaign needs to be extended or can be terminated early.

Research has shown that a Quality Factor of 90% is the best-practice standard for wind resource assessment. [For more on this research, and on the business case for the Quality Factor, click to download our free white paper.] By viewing the data with Quality Factor set to 90%, you can quickly see if you have enough data for the wind resource assessment study.

The Triton and SkyServe do not discard any of your wind data. Some analysts ask for all of the raw data so that they can do their own processing and filtering. In these cases, simply set the Quality Factor threshold to zero before exporting.

The same data set, filtered with a high Quality Factor setting of 90% (top, considered acceptable for a wind resource assessment report) and an ultra-high Quality Factor setting of 95% (bottom).

Improved Confidence Reduces Uncertainty

The Quality Factor improves confidence in the Triton data while saving you time and effort. A growing body of wind resource experts -- including independent engineers, consulting meteorologists, wind data analysts, and wind resource assessment service firms -- are experienced in the application of Triton's Quality Factor.

One of the key attributes of sodar and lidar systems is their ability to reduce project uncertainty by measuring the wind across a turbine's rotor sweep. Triton's Quality Factor further reduces uncertainty by qualifying each measurement, providing not only the raw data but also a standard metric for data quality. The Quality Factor is flexible -- providing the analyst with the freedom to choose which data are being viewed -- but the building blocks of the Quality Factor are fixed. Neither the SNR nor the Quality Factor calculations are customer-configurable. This is why all the leading independent engineering firms involved in wind project financing understand and use the Quality Factor as part of their energy projection calculations.

Remote sensing systems are the new secret weapon of the greenfield prospecting stage, saving wind developers time and money before the wind resource assessment campaign even begins. Keeping the costs of the development process as low as possible can make the difference between profit and loss in wind energy development.

Wind energy development is a complex business where any one factor (lack of proper wind resource, community opposition, one unwilling landowner, the inability to secure permits, or failure to pass an environmental review) can derail a project. The development process takes anywhere from 2-5 years, and the cost of failure increases exponentially during that development process.

Wind prospecting is the phase of wind development that occurs before the formal studies begin. Its object is to find sites that will be profitable -- and disqualify sites that will not be profitable. Ruling out non-viable sites as quickly as possible is essential to staying in business -- and this is where remote sensing systems can help.

Prospecting involves an initial look at likely sites to see if they meet criteria for profitable development -- the most important of which is viable wind resource. Mesoscale wind maps and site-specific historical wind data, such as data from met stations at nearby airports, are typically the first thing the developer consults. In some areas of the world, such as parts of Brazil, these sources are unavailable. Even in the areas with more mesoscale and historical data, these sources have limitations. Conducting even a short wind measurement campaign is mandatory in wind prospecting.

Starting Your Project Quickly

Before the commercialization of remote sensing systems such as sodar and lidar, wind measurement meant putting up a tilt-up tower. Permitting, procuring, and installing met towers can add months to a prospecting cycle. When you consider the cumulative costs per site -- which can run hundreds of thousands of dollars per year -- it's easy to see the advantages of a remote sensing system that needs no permitting and can be deployed and transmitting data in one day.

Understanding the data quickly is also a concern. Both Triton and Second Wind's tower-based wind data logger, Nomad, work with SkyServe Wind Data Service. SkyServe archives your wind data on a secure website as it is being gathered so you can monitor your campaign and gain rapid insight into the wind resource on the site.

A Mobile Asset

Flexibility to move measurement equipment quickly can make or break the wind prospecting process. Met towers cost almost as much to move as they cost to purchase and set up in the first place. Because of this, met towers are often left standing on non-viable wind sites and new towers purchased for new sites. A remote sensing system can continue its life as an asset from one wind site to the next, saving months every time it is moved.

Confidentiality

Compared to a met tower with its high visibility and public permitting process, remote sensing systems attract very little attention and can usually be deployed without compromising the confidentiality of your wind project. Keeping the details of the proposed project private until the right time can save the developer time, money, and energy.

Project Finance

Tower data may be required as part of the wind resource assessment report for a project financing proposal. When remote sensing data are included, some analysts prefer that the remote sensing system be "validated" by measuring concurrently with a tower for a certain period of time.

Our customers typically deploy Tritons for a few months and use the Triton data to disqualify sites that are not suitable. If the site qualifies for further study, a met tower may be erected after several months next to the already running Triton. In what we call "reverse validation," a good correlation between the met tower and Triton can be used to validate the Triton data that was gathered before the met tower was put up. If the wind resource at the site does not pan out, the developer has saved the cost of putting up a met tower and can inexpensively move the Triton to the next site.

Back In The Black

To date, remote sensing systems have been primarily used in wind resource assessment applications. However, the flexibility, low profile, and re-usability of remote sensing systems helps wind developers save many months and thousands of dollars before the wind resource assessment even begins. Using remote sensing systems in greenfield prospecting can help keep your project out of the red. 

Mechanical Engineer Finds Beauty in the Wind

Q: What is your job at Second Wind?
I’m a mechanical engineer.

Q. What is your background?
I studied mechanical engineering at Tufts University.

Q. What do you like about Second Wind?
I like the smaller company feel about Second Wind which allows my work to be diversified, keeping my job fresh and exciting. I also really like the people that I work with. They’re all super smart, quirky and overall truly awesome people.

Q. What activities do you enjoy outside of work?
I enjoy hanging out with friends, cooking (…and eating), shopping, and exploring Boston.

Q: What interests you about the wind industry?
I strongly believe that we need to be taking bigger steps towards a green tomorrow and the wind industry is just one of the many ways we can get there. Being a mechanical engineer, wind turbines are almost like a piece of art to me as well as a way to improve the world we live in. I’m glad to be working in a company whose products help make our world a better place to live.

Q: If you had one super power what would it be?
If I had a super power I would be able to control the weather like Storm from X-Men. I’d only use it when I wanted to make it a beach day in middle of the winter.