Aurora Solar, a developer of solar power estimating applications, announced that HelioScope, its commercial solar design software, will be using additional, better LiDAR data to provide more accurate estimates of solar power systems.
Unlike flat images from Google Earth, or aerial and satellite images, LiDAR data can accurately provide valuable information, such as the height of buildings and trees and the pitches of roofs—data that is quite important for determining the size and energy yeilds of commercial and utilty-scale installations.
Aurora’s LiDAR database is built from a variety of sources, including the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Geological Survey (USGS), agencies that take it upon themselves to map regions affected by severe weather, earthquakes, forest fires, and so on. Private companies may also contribute to libraries of LiDAR data, but as one might imagine, they are more likely to keep their LiDAR data (expensively obtained from flying drones or fixed-wing manned aircraft) close to the vest. The result is a limited patchwork quilt of LiDAR mapped areas that is varied by units used of diverse point densities and plot sizes, with gaps and overlaps.
Aurora stitches the LiDAR data together, irons out the wrinkles and seams, and makes the entire database available (for a price) to commercial solar installers that need to provide estimates to consumers and businesses of solar power systems using HelioScope.
But we have the LiDAR where it is important, says Paul Grana, general manager of HelioScope at Aurora Solar, focusing on urban areas. In 2018, Aurora had LiDAR data available where 95.8 percent of the U.S. population lived, according to the company. In 2022, Aurora’s coverage of the U.S. has not only expanded to 98.6 percent but has also increased the average point density from 9.2 points/m2 to 12.8 points/m2. This database update is no small task, says Grana. The LiDAR database grew from 120 terabytes to 280 terabytes.
As important as a seamstress function is to creating a uniform LiDAR database is a librarian function. Aging LiDAR data needs to be replaced with the most current database, a function that Aurora has volunteered for. For purposes of solar power estimating that must be concerned with shadows, it is important to have the latest information for buildings and structures, which may change over time, and for trees, which can both grow taller, be trimmed and fall down.
This may seem like a small-scale version of what Google did to aerial and satellite photos to create Google Earth, generating a seamless visual coverage of the entire planet—except, of course, Google graciously provides the results freely to the public.
A commercial solar system installation starts with an estimate and continues with a detailed design. A salesperson can get a reasonable estimate for a system on their iPad if they are local, or they can push it to a web page if they are a national solar provider, like Tesla with its Solar Roof. The estimate can be done with the aid of software like Aurora’s HelioScope. All that is needed is an address that brings up the image of the property, from which one can zoom in on the roof and place the panels to get the solar power attainable. Since the address determines the location on Earth, the angle of the sun throughout the day and over the seasons can be determined. The user may have to tell the application the area where solar panels will be placed (until AI can take over this task), but if it is a LiDAR image, the pitch of the roof can be easily calculated.
Find out more about Aurora Solar on their website.