5 Companies Harnessing AI To Boost Solar Power

Artificial intelligence is letting these companies make solar power more accessible, powerful, and efficient.

on March 29, 2023 at 12:30 PM

Image by the American Public Power Association via Unsplash

Artificial intelligence and machine learning are cutting edge technologies that have pushed the energy industry to seek new solutions to old challenges. 

Solar energy, sometimes seen as expensive or difficult to use, has gotten a boost from companies who have discovered how AI can make this green energy source a more powerful, cost-efficient option for reducing human reliance on fossil fuels. 

Read on to learn more about five companies that use AI-assisted technologies to improve the production and use of solar energy.


SunPower is a solar panel company that uses AI and high-resolution satellite imagery to help residential consumers design custom solar power systems for their homes.

“Homeowners typically spend a significant amount of time online researching solar panels and running calculations to understand their potential savings and  the number of panels they need for their home,” SunPower product manager Nour Daouk writes in a blog post for Google.

AI and machine learning play a key role in creating digitally generated solar power installation plans for each unique roof, the company says. 

“When a user enters an address, artificial intelligence recognizes the roof, obstructions, and trees. We then place panels according to local design rules,” Sunpower writes on its website.


Heliogen is a solar energy startup that uses an AI-powered program to concentrate sunlight and generate heat. 

By using AI to align a field of specialized mirrors to direct a lot of sunlight — and a lot of heat — at a central tower, Heliogen can produce enough energy to power industrial processes like making cement or glass.

Directing and monitoring solar panels isn’t the company’s only method of utilizing AI, however.

Heliogen’s Installation & Cleaning Autonomous Robot & Utility Solution (ICARUS), first demonstrated at the company’s Lancaster, California, facility in 2021, uses GPS, ultrasonic rangefinders and light detection and ranging (LIDAR) sensors to direct AI-assisted robots to install and maintain its systems.

By combining multiple AI-enhanced technologies, the company aims to “cost-effectively deliver near-24/7 carbon-free energy in the form of heat, power, or green hydrogen fuel at scale,” according to the Heliogen website.


Danish energy industry software company Enfor utilizes AI in its SolarFor solar power forecasting solution.

“SolarFor is a self-learning and self-calibrating software system based on a combination of physical models and advanced machine learning,” the company states on its website.

“The self-learning and self-calibrating algorithms will continuously learn about the solar farm characteristics and will adapt to changing conditions, seasonal variations, and as the photovoltaic module ages, such that forecasts stay accurate over time without the need for manual configuration.” 

When installed, SolarFor is given historical weather and energy production data, the company says. The AI function then learns from that historical data and from real-time inputs to produce its forecasts.

By constantly monitoring and updating its forecasts, the software allows the companies that use SolarFor to adjust expectations for how much energy might be generated on a given day.

Green Power Monitor

“GreenPowerMonitor makes use of [Machine Learning] to extract information from the myriad of data points residing in our databases to provide value to our customers,” the solar plant data collection and management software company states on its website.

“ML models allow for a statistical description of site components given certain conditions and as a result our solutions can predict the component’s behaviour in such conditions.”

GreenPowerMonitor utilizes AI in its GPM Plus and GPM Horizon asset management services. 

The company sees three main benefits to using AI in its products. First, it allows the software to create models for expected performance. Second, AI can help predict future performance. Lastly, AI can help trace issues to their root cause through analysis.

Glint Solar

Glint Solar was founded in 2020 in response to “an urgent need to speed up [solar power plant] site origination and ensuring better insight from a project’s inception.”

Where does AI come into play? Glint Solar combines satellite imagery, relevant datasets, and machine learning to help solar power generation companies quickly spot the best locations for generating solar power.

Glint Solar’s software “is able to analyze factors such as available solar radiation and proximity to key infrastructure, such as capacity in the grid for connecting to projects,” TechCrunch reports.

“It also considers social and environmental regulations, as well as looking at other physical factors — like shading on a site; extreme weather; or the elevation or slope of the land, among others — to feed its modeling.”

Jasper AI assisted a Breaking Energy writer in creating this article.