Currently solar panels are vulnerable to high-wind events, with possible structural collapse and failures. Tracking mounts that rotate the panels for maximum sunlight exposure remain in operation until a certain wind speed is reached. Then the panel goes into a presumed safe stow position parallel to the ground. While this method is sometimes effective, the panels lose energy output in this position and are often not protected from higher wind speeds. A new framework combines advanced wind simulations with machine learning to optimize individual solar panel angles under strong winds. It treats panels as independent decision-makers and identifies creative, data-driven solutions to reduce stress, significantly outperforming current safeguards.