Training solar panels to dance with the wind
Solar energy is currently the fastest growing energy field in the world. Solar photovoltaic plants convert sunlight into electricity, and their huge potential to produce clean, renewable energy makes solar energy a cornerstone of the Net Zero 2050 initiative, which aims to cut carbon dioxide emissions to zero by 2050.
Wind energy has both positive and negative impacts on the solar grid. It helps maintain solar panel performance by eliminating the buildup of dirt and dust, and since solar panels typically lose effectiveness as they heat up, airflow over and around the panel surface can increase cooling and efficiency. However, the slender panels are easily affected by strong winds, which can even lead to structural collapse and failure that can take weeks to repair. Additionally, as the use of solar energy increases, there has been a significant increase in insurance claims due to the vulnerability of photovoltaic panels to severe weather.
exist fluid physics, Researchers at the Center for Material Forming at PLS University Sophia Antipolis in France have proposed a unique numerical decision-making framework for protecting solar panels from extreme weather conditions.
“By combining advanced fluid dynamics and artificial intelligence, we see an opportunity to innovatively address wind damage risks and contribute to the resilience of renewable energy systems,” said author Elie Hachem.
Row spacing, ground clearance and tilt angle have been key areas of focus for research teams looking to mitigate the effects of wind on solar panel damage. The tracking bracket, which rotates the panels for maximum sunlight exposure, remains in operation until a certain wind speed is reached. At this point, the panel enters a presumed safe stowed position parallel to the ground. While this stowing method can be effective in some situations, the panels lose energy output in this position and, more importantly, are often not protected from higher wind speeds.
The team used a framework that combined advanced wind simulations with machine learning to optimize the angle of a single solar panel under strong winds. Unlike previous approaches developed to protect panels, this new approach treats panels as independent decision-makers and identifies creative, data-driven solutions to reduce stress that significantly outperform current conservation measures.
“It’s like teaching the panels to dance with the wind, minimizing damage while protecting energy production at high wind speeds,” Hachem said.
Decision-making frameworks for solar panel protection challenge traditional engineering practices. It provides a scalable solution that enhances real-world resiliency while opening the door to smarter, adaptable systems to meet the challenges of net-zero carbon emission energy production.
2024-12-17 18:09:02