Researchers at Stony Brook Using AI to Improve Solar Panel Efficiency

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Researchers at Stony Brook University in New York have developed new machine learning technology to analyze large solar panel arrays and identify defects. Commercial and grid-scale solar utilizes anything from hundreds to millions of solar panels. Small per-panel defects can result in significant efficiency losses. A new study has developed an AI-based algorithm that uses live weather and solar inverter data to identify panels that require maintenance, replacement, and repair.

Solar panel defects cost American solar facilities almost $6,000 per megawatt last year. New solar monitoring technology developed at Stony Brook University could be refined and deployed to improve grid-scale efficiency.

This is a great development for large projects, and it’s also a reminder that monitoring solutions are also essential for residential solar installations.

How Residential Customers Save with Long Island Solar Installations

Long Island families enjoy solar savings through consumption offset and net metering. Understanding how this works can help you decide if a solar installation is right for your home.

  • Solar panels reduce your reliance on the grid. You will take most of your daily energy needs from solar before consuming electricity from the utility network.
  • Excess electricity produced by solar panels is sent to the grid. This spins your electric meter backwards, helping to offset future consumption.
  • Any excess (the net difference) is carried over per month, and the annual excess is calculated at a buy-back rate (also known as an avoided cost rate or wholesale energy price).

Is Solar Efficiency More Important for Households?

Solar efficiency is more important for households because even small losses can significantly affect the payback period and return on investment.

  • In New York, residential solar usually pays for itself with savings in the first ten years.
  • Any efficiency losses can potentially increase the payback period.
  • Solar panels last an average of 25 to 30 years, but the biggest savings occur in the first 15 years. It’s crucial that solar panels are efficient and free of defects.

The SMART Solar Program Uses Live Monitoring to Ensure Efficiency

The machine learning research at Stony Brook University is a great example of how live data is used to improve solar panel efficiency. Similar principles are applied to residential solar arrays.

Power Solutions is one of the top-rated solar installers on Long Island, offering custom solar solutions for families. The SMART Solar Program is a unique customer experience program offered for free to all Power Solutions customers.

In addition to essentials like a 25-year solar panel warranty and 24/7 support, the SMART Solar Program also includes live monitoring.

  • Power Solutions monitors all systems with data generated by solar panel microinverters. This indicates when there are rare defects or failures.
  • Because Power Solutions uses microinverters rather than consolidated string inverters, the insights are generated per panel.
  • You can also monitor your system with free solar apps that generate live data showing production, consumption, and storage (if you add an optional solar battery storage system).

While the Stony Brook study uses AI to find hidden defects in giant solar farms, Power Solutions brings the same granular visibility to your roof. With advanced microinverters, we see exactly how much energy each panel produces in real time. If even a single panel underperforms, we can act quickly and ensure your system operates efficiently to maximize production and solar savings.

Efficient Solar Generates Better Savings

Whether considering a large grid deployment or residential solar on Long Island, efficient solar improves savings and the return on investment.

Choose one of the most experienced solar installers near you on Long Island for efficient and dependable solar. Learn how much you could save, starting with your free home solar estimate, or call us now at (631) 348-0001.

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