Array Technologies Adds Algorithms For Better Light Capture By Solar Trackers

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Array Technologies, a company we recently featured due to its work testing bifacial solar panels and solar trackers, has added a set of software algorithms dubbed SmarTrack to its latest generation of solar tracker, the DuraTrack HZ v3, enhancing the system ability to react to weather and site conditions.

SmarTrack is an optimization technology that intelligently adjusts solar module angles to optimize backtracking power production on as-built project conditions to capture the maximum power yields during diffuse light conditions, the company says.

A solar tracker farm may be built on ground with an uneven or sloped surface, which can contribute to shading of one tracker row by another. Similarly, cloud movement can shift sunlight from a direct ray to a diffuse source, which can be perceived by sensors and can be learned from weather-condition Internet feeds.

“The next generation of solar tracking has arrived. We have created a suite of software which consists of three separate machine-learning algorithms, all of which are fine-tuned to maximize power output in different scenarios,” said Jim Fusaro, chief executive officer of Array Technologies, based in Albuquerque.

The software suite utilizes self-learning algorithms that work independently of each other to optimize the energy output of the PV system. Once an operational strategy has been learned, the tracker system orientates PV modules to the optimal angle for power output, responding to specific module technology, weather, and site conditions.

One algorithm controls backtracking. Undulating or hillside sites can introduce shading of modules in the late or early morning hours. SmarTrack monitors power production of the as-built project and alleviates the effects of shading by backtracking to optimal production angles.

The second algorithm controls diffuse light. Diffuse light conditions caused by cloud cover can rob PV plants of output. SmarTrack utilizes site production data and weather information to adjust the angle of the solar modules, providing optimal yield until the cloud cover disperses.

And the third algorithm controls bifacial and split-cell response. Bifacial tracking promises significantly higher power yields — anywhere from 10 percent to 50 percent or higher — from backside gain. PV plants equipped with SmarTrack will utilize custom algorithms to maximize energy harvest for split-cell bi-facial and mono-facial module configurations.

“Array Technologies is always looking for smart strategies to increase power production,” said Ron Corio, founder and chief innovation officer at Array Technologies, “This new product will further enable our customers to unlock the full potential of their solar power investment.”

The new algorithms will help optimize bifacial panel use on the tracker, which Array is now testing with a U.S. research laboratory in Albuquerque. While manufacturers rate the potential energy gain from the backside of bifacial modules as high as 95 percent, the actual field performance of these modules has not been tested enough to guarantee a given gain. The Array tests will help determine this by using 6 or 8 different bifacial panel brands.

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Once the top two or three bifacial panel performers are known, a generally accepted yield boost for a given panel manufacturer can be used across the industry. The field-tested values also can be utilized in various software analysis models, like widely-used PVSyst, which predict overall system performance.

There are competing software modeling programs like the U.S. National Renewable Energy Laboratory’s SAM, and several other private sector programs that have been updated to include bifacial functionality. However none of these will be considered good, much less the best, until field testing confirms the accuracy of the program predictions.

The expected system performance, based on the field testing results, can then be used in bankability studies by independent engineers to support the economic viability of a project that includes solar trackers and bifacial panels.

Bifacial panels work best on solar trackers, since the source of sunlight moves during the day, it is best captured by the moving tracker mechanism.

The composite sources of sunlight captured by a bifacial tracker system include direct sunlight on the front of the panel, diffuse sunlight caused by cloud and physical object reflection onto the back side, and albedo, the reflected light from the ground.

Array and other tracker makers are experimenting with different types of ground cover material to attempt to maximize albedo gain on their trackers. While green grass and gray gravel or dirt do not provide good albedo conditions, white surfaces from white gravel, white paint, or white membranes (like those used in commercial roof coverings) offer high albedo values. Perhaps surprisingly, snow provides up to an 85 percent albedo.

Standards for predicting bifacial panel performance also are being fine-tuned for a January 2019 public release. NREL, based in Golden, CO, and ISC Konstanz, based in Konstanz, Germany, have shepherded this standard-setting process, which will result in a new regulation under the International Electrotechnical Commission’s IEC 60904-1-2.

The buzz surrounding bifacial tracker systems is predicted to get louder soon. Indeed, Mike Woodhouse, an economic analyst at NREL, estimates that the market share for bifacial tracker systems will expand from a near-zero base today to a projected 10 percent market share in 2019, and a 30 percent market share by 2025, compared with monofacial panels. “That would represent a $20 billion to $110 billion market for bifacial technology,” he reckons.


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Charles W. Thurston

Charles specializes in renewable energy, from finance to technological processes. Among key areas of focus are bifacial panels and solar tracking. He has been active in the industry for over 25 years, living and working in locations ranging from Brazil to Papua New Guinea.

Charles W. Thurston has 78 posts and counting. See all posts by Charles W. Thurston