Urban environments can be a challenge to solar development. When evaluating a building’s solar power potential, solar installers and consultants often turn to Google Earth or Bing Maps to get an early impression of the building; it’s the analog of real estate ‘drive-by’. Even knowing the pitfalls, it’s hard to resist a quick look at a satellite-based image.
The recent case study below is a good lesson in the limitations of that approach.
Initial images of this 80,000+/- SF mixed use commercial building were not promising. The building appeared to be in the shadow of a 42 story skyscraper – one block due South. But something didn’t look quite right. Part of the shadow is missing – there is bright sunlight on the street between buildings. Huh?
Shadows cast by adjacent buildings are the major limiting technical factor to solar development in urban environments.
So we took a look at Microsoft’s new Bing Maps. No shadow. We went back to the Google image and began to notice discrepancies in the patterns of shadow between buildings and also a few small shadows that appeared to be pointed in the wrong direction. We came to conclude, for a variety of reasons, that the length of the shadow must be computer generated.
Returning to Bing Maps, we navigated to a view from the rooftop itself. Though very slow to respond to incremental commands, Bing ultimately provided a ‘rooftop view’ of the skyline. Looking due South (solar south, not magnetic south) the image gave us a more encouraging skyline, but one dominated by a skyscraper that extended beyond the computer generated image.
Though both Google and Bing technologies are powerful and, at times, very useful if not truly amazing, they didn’t yield much more useable information about the solar potential of the building than we had when we began.
Since we did not yet have access to the building, we measured the distances at street level, went to City records, and searched published real estate information on both buildings. With some street level surveying and high school trigonometry, we were able to calculate that the smaller building was free of shadow about 7 +/- months each year – late spring through early fall – when the weather and sun angles were best for solar power generation. A few additional calculations indicated that during the remaining months, the skyscraper’s shadow passed quickly, in about 1 ¼ hours on average.
With this analysis in hand, we approached the building owners and suggested a full case study. Granted access to the roof, we mapped shadows created by roof-mounted equipment and then captured digital data of the skyline in relatively open areas of the roof. Solmetric’s ‘SunEye’ provided a completely new perspective on the available sunlight.
The SunEye image overlays the sun’s path and a calendar on a fisheye image of the city skyline from the surface of the roof. In other words, this is how a solar panel (module) will ‘see’ the sun’s path from this location.
In this view, the skyscraper – that looks so huge from roof level – is a relatively small part of the sky during daylight hours. More importantly, the building turns out to be a good candidate for solar power with strong ROI.
Two takeaways from this case: though Google and Bing technologies can be very useful, visual impressions and satellite-based images may be misleading in terms of solar potential of a specific building or location. Second, only careful data capture from the rooftop can provide an accurate assessment of the amount of solar power a building can generate.
More about this case study in future blogs including details of the ‘business case’ for urban solar.