Data Science

Machine Learning is Helping Change the Solar Industry

Sep 22, 2016
By Brad Nemire
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AI-Generated Summary
  • PowerScout uses GPUs on Amazon cloud and cuDNN to train deep learning models that predict which homes are likely to buy solar panels.
  • The models analyze commercial database data and LIDAR from satellite images to detect existing solar panels and tree cover that could shade rooftops.
  • Solar radiation maps factor in building height, vegetation, and other objects to estimate rooftop energy harvest potential without in-person measurements.
  • Predictive analytics reduce customer acquisition costs by targeting direct mail and online marketing to the most promising homeowners.
  • The U.S. Department of Energy awarded $2.5 million in grants through its SunShot Initiative to support the company.

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A startup from California is using GPUs and big data to predict what homes are likely to buy solar panels.
PowerScout is using GPUs on the Amazon cloud and cuDNN to train their deep learning models on a mix of data from commercial databases and LIDAR to detect solar panels from satellite images, and to also detect the presence of trees near homes that could cast shade onto roofs.
The tools the startup developed can also help estimate how much energy could be harvested from a home’s rooftop without needing to take measurements in person with a decent degree of accuracy. From the information, they can target direct mail and online marketing to the most promising customers and quickly give them online estimates. Then, those who are interested in rooftop solar can choose a financing plan and get connected to a local installation partner to have it installed.

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The map shows how much solar radiation that neighborhood is receiving. It takes into account the height of the buildings, vegetation, and other objects that could cast shade on an area. The red pixels receive the most sunlight and the blue pixels receive the least.

The company says “predictive analytics can shave a huge portion off the price tag of solar because it eliminates the cost of finding homeowners who want clean energy.”
PowerScout’s recent round of funding was provided by a mix of private and public sources including the U.S. Department of Energy, which awarded a total of $2.5 million in grants via its well-known SunShot Initiative.
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Data Science | Cloud Services | CUDA | cuDNN | News | Big Data & Data Mining | Image / Video Detection & Recognition | Machine Learning & Artificial Intelligence

About the Authors

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About Brad Nemire
Brad Nemire leads the Developer Communications team at NVIDIA. Prior to NVIDIA, he worked at Arm on the Developer Relations team. Brad graduated from San Diego State University and currently resides in Silicon Valley.

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