It feels like we’ve been talking about Artificial Intelligence (AI) and all its various forms for a while now. From those creepy early robots that could deliver food on a tray, to Watson winning Jeopardy, AI has a surprisingly long history — even if it’s felt a little abstract to most of us.
The groundbreaking advent of ChatGPT, however, made AI real to many people, and seemed to dramatically accelerate the timeline. What was once a distant future concept has become a transformative force today, reshaping industries across the globe, including the solar sector.
The era of true AI isn’t on the horizon — in many ways it’s already here.
We had a great discussion about AI at Empower 2023, which highlighted the critical role of AI in optimizing energy usage, enhancing PV system design, and addressing key challenges in the solar sector. This article explores some of the key topics covered during the discussion, and touches on many of the most promising AI-powered applications that could help make solar technology truly mainstream in the years ahead.
The convergence of AI and solar energy for sustainable innovation
Solar’s unprecedented growth is encouraging for us all, but it also presents some challenges, including hiring and training people quickly enough to meet this demand. This is just one area where AI will help lighten the load.
This is clearly evident in areas like 3D modeling, configurations, and light detection and ranging (LIDAR) analysis. Salespeople in the field can use these tools to render different PV system models in real-time as they help customers decide on the optimal design for their own budget and energy goals.
However, progress has been incremental — hindered by slow adoption rates, limited data access, and a historical reliance on face-to-face consultations that necessitate deploying large off-site technician teams.
These limitations are quickly eroding as stakeholders throughout the industry continue to leverage the mind-boggling power of generative AI models and large data sets.
How AI is being used in solar
There are many possible uses for AI in the solar industry, here are some that are helping right now.
Data and AI systems
Data is the lifeblood of AI, driving its growth and effectiveness. In the solar industry, companies like SolarEdge Technologies are leveraging vast amounts of sensor data to train AI models. This data-driven approach is essential for developing and improving AI systems, enabling more accurate predictions, and delivering personalized solutions. As more distributed energy resources ship with sensors and receivers, data collection will become easier and even more accurate — leading to better, cheaper, and more powerful designs and energy management solutions.
According to Chris Thompson, Vice President of Product and Technical Marketing at SolarEdge Technologies, “In the history of the industry, we have never seen such strong price signaling, you know, in terms of market formation. So when I look at our own solutions and how AI has led those new products that we are launching… it’s using this data.“
3D modeling and design
AI’s application in 3D modeling and design is transforming solar system planning. Aurora AI is trained on nearly half a million roofs originally modeled in Aurora. It’s this training data in combination with quality geospatial data that creates the 3D model. This automation not only speeds up the design process but also enhances precision, allowing for tailored solar system configurations that meet individual needs. It also leads to more accurate production estimates therefore leading to installations that produce what was promised and happier home owners.
Energy optimization
AI is playing a pivotal role in optimizing energy usage and economics within the solar industry. Complex algorithms predict solar generation and energy demand, enabling the most cost-effective dispatch of energy. This optimization extends to real-time adjustments, making solar energy more efficient and economically viable. This leads to optimal savings for residential and commercial users. However, predictive modeling can also make energy arbitrage more lucrative for those trading on the open markets.
Where AI has potential in solar
With emerging AI tools, there are now a range of potential applications that can help increase solar adoption — while simultaneously speeding up installation times and making the technology even more affordable than it already is.
When deployed correctly and at scale, AI models can act as:
- Digital Consultants and Customer Support: AI-powered models for personalized guidance in selecting solar solutions and continuous support. You’ll still need boots on the roof to perform the actual installation. But this level of digital support can make the process both cheaper and more successful — without needing to deploy teams into the field.
- Automated Permitting and Regulatory Compliance: Streamlining processes, reducing administrative burdens, and accelerating project timelines. A sufficiently trained AI model would have access to all the latest bylaws, regulations, HOA contracts, and even utility rates.
- 3D Modeling and Predictive Maintenance: Utilizing AI algorithms for potential system failures, recommending preemptive actions, and minimizing downtime. In addition to real-time access to manufacturer documentation, future AI models will also be able to monitor all components connected to the grid to generate accurate forecasts about failure rates, maintenance schedules, and general upkeep. This accuracy will only improve as sensors and receivers become more standard in our shift to truly virtual power plants.
- Intelligent Energy Management: Integrating AI with IoT for dynamically adjusting energy consumption and production to achieve optimal efficiency. For many, this represents the holy grail — i.e. a controller that optimizes energy generation, storage, and dispatch at scale so that the grid remains as green, affordable, and reliable as possible — all in real time.
These applications mirror current AI trends, showcasing a roadmap for a future where AI is an essential part of the solar industry.
Conclusion
AI is a powerful tool for the solar industry, and its influence is only growing. It’s easy to envision a vibrant future where AI is not just an accessory but a core driver of innovation and environmental responsibility. In a world striving for cleaner energy solutions, the solar industry’s embrace of AI marks a significant stride towards a more intelligent, adaptable, and sustainable energy landscape.
To learn more about AI and solar, watch the entire Empower session on demand.
More questions? Check out the FAQs below, then book a personalized demo to get all your AI questions answered.
AI in renewable energy frequently asked questions
How can AI help renewable energy succeed?
AI has the opportunity to change the renewable energy sector as we know it, specifically solar energy, by enhancing efficiency, reliability, and integration. AI can eventually touch every part of the process from optimization of energy production, including forecasting and performance monitoring, to accessibility and adoption.
What are the benefits of AI in renewable energy?
AI has many benefits in the renewable energy space. Here’s a few:
- Efficiency and automation: AI can help streamline repetitive tasks and optimize your day-to-day operations, leading to enhanced productivity
- Data analytics: AI can process large datasets quickly, providing valuable insights and reducing the cost of prediction
- Cost reduction: AI allows you to automate previously manual processes to reduce operational and labor costs
- Customer experience: AI allows you to better support your customers through personalization as well as chatbots and gathering consumer insights
Are there any challenges to using AI in renewable energy?
AI does have its own set of challenges. These include issues related to data privacy, security concerns, and the need for substantial initial investment, among others. Also, human workers have fears about their jobs being completely replaced by AI. Fortunately for solar, there is more work to be done than there are people to do it and AI can be used to augment the existing workforce.
