Artificial Intelligence Delivers Great Benefits for Solar Energy

While the impact of artificial intelligence (AI) on solar draws far less notice that what it does for tech or banking, it turns out that AI can provide massive benefits for everything from solar energy system design and maintenance to system optimization and the entire electricity grid.

Designing the Solar System

Once business or residential customers decide to install solar energy, AI can help with designing the right system. AI can tailor the design of solar systems based on the customer’s priorities, such as maximum net metering income or lowest cost installation.

AI could help to design the solar system and analyze the property, CNET noted, as well as to optimize a home battery and even predict maintenance costs after the panels are installed. AI promises to make solar installations faster and potentially cheaper while also improving the performance of a home energy system over time.

AI algorithms can be used to optimize the positioning of solar panels and reduce shading, according to Omdena, which improves solar energy production. AI algorithms can also analyze very localized weather patterns and solar radiation levels to predict future solar energy production, which improves planning.

 

Maintaining the Solar System

AI-based analytics are also being used for predictive maintenance, Omdena found, so users can identify potential issues with solar panels or inverters and reduce maintenance costs as well as downtime. At the same time, AI-based tools are being used to monitor and manage the performance of solar panels, inverters, and other components of solar systems, which improves system reliability.

AI will bring revolutionary improvements in the efficiency, reliability and predictability of solar power generation, PV Magazine writer Patrick Jowett observed. For power forecasting, for example, AI algorithms can detect deviations from normal operations that may indicate faults or anomalies that manual inspection may not find, thus reducing maintenance costs and improving efficiency.

Optimizing Solar

Beyond simply maintaining a solar energy system, AI can help optimize the system immediately and for the longer term. AI algorithms can encourage consumers to reduce their energy usage during times of high demand, for instance, which improves grid stability and reduces costs.

Data analytics plays a crucial role in identifying patterns and trends in solar systems, Green.org explained, which allows better decision-making and optimization strategies. AI-based real-time monitoring and analysis of system performance leads to improved efficiency, fewer human errors, higher reliability and adaptation to changing environmental conditions.

A solar farm in California, for instance, implemented AI algorithms to optimize energy generation. The algorithms analyzed weather data, historical performance, and real-time conditions to determine the most efficient operation parameters, which resulted in significantly higher energy output and lower maintenance costs.

And in Germany, a solar installation that utilized algorithms to detect faults in panels and identify potential issues in real-time reduced downtime and improved system performance.

At the heart of solar energy optimization, Tech-Stack opined, is sophisticated AI algorithms that process real-time data from environmental sensors to adjust the positioning of solar panels for maximum sunlight exposure. AI also monitors solar cells, identifying inefficiencies or malfunctions such as dust accumulation that may hinder performance and triggering automated solutions which maintain high energy output. AI's predictive capabilities ensure that solar energy generation aligns more closely with consumption patterns, leading to less waste and a smoother integration into the power grid.

Grid-Scale Enhancements

Beyond a single solar installation, AI can also improve the efficiency of the broader energy grid.

By analyzing historical weather data and real-time conditions, AI algorithms can predict solar energy generation with high accuracy, which helps optimize energy storage and distribution. Predictive maintenance and fault detection algorithms can detect and address issues in solar systems before they escalate, minimizing downtime and maximizing performance.

Green.org said adaptive control strategies help solar systems adjust to changing environmental conditions, maximizing energy output. They also assist in load balancing and demand response, allowing for a more stable and reliable power grid.

In Australia, for instance, a user leveraged an AI-based solar forecasting system to improve grid integration. The system analyzed weather patterns and historical energy generation to predict solar output accurately, which allowed grid operators to optimize energy distribution and minimize the need for fossil fuel-based backup power.

At Baldy Mesa in California, Amazon uses machine learning models to help predict when and how the project’s battery unit should charge and discharge energy back to the grid. The software dynamically optimizes when to buy, store and sell energy based on grid conditions. The same solution at a similar site helped anticipate the state-wide heatwave in 2023 and stabilize the grid by delivering stored solar energy when it was needed the most.

Beyond the Solar Sites and Grids

AI is also being used for innovative solar-related solutions beyond home solar systems, solar farms and grid operations.

Renewable energy company Low Carbon and scientists at Lancaster University have combined novel acoustic monitoring techniques with AI to assess the real-time dynamics and biodiversity of insect pollinators at Westmill Solar Park in Oxfordshire. Lead researcher Hollie Blaydes explained to Edie that “data we collect will also tell us more about how pollinators respond to solar farms, compared to similar land uses, which is key when trying to embed biodiversity benefits into solar developments.”

Solar-powered AI algorithms can also optimize freshwater production and reduce energy consumption in desalination processes, Omdena said, as well as to optimize vehicle charging schedules or routes to reduce energy consumption in transportation.

The combination of simulation-driven digital prototyping powered by AI with rapid physical testing can cut development timelines for next-generation solar cells blogger Oluwafemidiakhoa observed. AI can facilitate intricate redesigns of conventional silicon architectures and strategies for higher efficiency along with virtual modeling of novel tandem multi-junction cells. At MIT, this technique achieved over 40 percent efficiency by optimizing tandem stacking of perovskites, silicon, and gallium phosphide cells. On the manufacturing side, AI control systems are being used to tailor chemical vapor deposition processes for complex internal solar cell architectures unattainable through conventional fabrication approaches.

Selling Solar

As a last point, AI has the potential to enhance the entire sales process for businesses or residential consumers considering solar energy.

Generative AI already plays a role in the front end, for instance, by assisting or even replacing traditional salespeople. AI chatbots can handle customers, CNET noted, and it can help customers reduce costs or predict when their system will need maintenance. "Long-term maintenance matters a lot, and generally end consumers don't put that in their calculations,” Eletriq Power CEO Frank Magnotti told CNET.

In Conclusion

While AI in solar may be less prominent than in other sectors, it’s already delivering significant benefits and promises far more in the future.

Magnotti, interviewed in the CNET article, perceives minimal risk and numerous advantages in the expanding influence of AI in the solar industry. AI is expected to greatly improve the efficiency of solar panels and the processes surrounding them, propelling us towards more sustainable energy solutions.

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