Solar power is rapidly becoming the fastest-growing energy sector globally. Solar photovoltaic power plants convert sunlight into electricity, and their vast potential for clean, renewable energy makes solar power a key component of the NetZero Emissions by 2050 initiative, which aims to eliminate carbon dioxide emissions by the year 2050.

Wind has both positive and negative effects on solar power grids. On the one hand, wind helps improve solar panel performance by removing dirt and dust. Additionally, as solar panels lose efficiency due to heat buildup, wind flow across the surface increases cooling, thereby enhancing their effectiveness.

However, high-wind events pose a significant risk to solar panels, potentially causing structural collapse and damage that can take weeks to repair. As solar energy use grows, so too do insurance claims related to weather-induced damage to photovoltaic panels.

In a recent study published in Physics of Fluids by AIP Publishing, researchers at the Centre for Material Forming at PLS University in Sophia Antipolis, France, presented a novel decision-making framework for protecting solar panels from extreme weather events.

"By combining advanced fluid dynamics and artificial intelligence, we saw an opportunity to address the risks of wind damage innovatively and contribute to making renewable energy systems more resilient," said Elie Hachem, the study’s lead author.

Previous research has focused on factors such as row spacing, ground clearance, and tilt angles to reduce wind damage. One common solution involves tracking mounts that adjust solar panels to maximize sunlight exposure. When wind speeds reach a certain threshold, these mounts reposition the panels to a flat, presumed safe position. While effective in some cases, this approach reduces energy output and often fails to protect against high winds.

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The researchers' new framework uses advanced wind simulations combined with machine learning to optimize the angle of each solar panel under strong winds. Unlike traditional methods, this framework treats panels as independent decision-makers, identifying innovative, data-driven solutions to minimize stress and outperform existing safeguards.

"It's like teaching the panels to dance with the wind, minimizing damage while still maintaining energy production during high wind events," Hachem explained.

This new decision-making framework challenges conventional engineering approaches and offers a scalable solution to improving the resilience of solar energy systems. It also paves the way for more intelligent, adaptive technologies to help achieve net-zero carbon emissions.