Grading With Grace: Optimizing Utility Scale Solar Site Grading Using Data Science

Presentation Description: This poster targets civil engineers working on utility-scale solar projects and software engineers interested in civil applications. It showcases how advanced algorithms—weighted linear regression, dynamic programming, and simulated annealing—can automate and optimize earthwork estimation for solar sites by determining the optimal placement of linear torque tube and terrain-following trackers. The methodology behind each algorithm is clearly outlined: weighted regression for linear torque tube alignment, dynamic programming for terrain-following trackers, and simulated annealing for overall optimization. Results from two trial utility sites will demonstrate the practical impact of these techniques.

By integrating manufacturer specifications and comparing linear versus terrain-following tracker designs, this approach directly influences project profitability—not only by reducing costs for EPCs but also by significantly improving engineering team efficiency. Users adopting these methods can expect a 10–44% reduction in cut/fill quantities and a 10x decrease in site design time compared to traditional processes.

This data-driven strategy revolutionizes solar site grading, offering engineers a streamlined, cost-effective solution that enhances throughput and maximizes project returns.