Snow loss estimation for photovoltaic single-axis tracker systems

Single-axis tracker (SAT) photovoltaic (PV) systems dominate the utility-scale solar market in the United States, yet research to quantify and optimize their performance under snow conditions remains limited. To address this gap, we developed a novel snow-sensing system for monitoring snow on SAT systems to calculate snow losses by comparing measured DC power output in winter with modeled power under no-snow conditions. By isolating and mapping the generation losses based on observations, we are now positioned to develop models to predict snow-induced energy deficits for SAT configurations. Overall, Our work 1) demonstrates the need for, and provides a technical basis for, SAT-specific performance models; 2) offers crucial insights for optimizing tilt angles to reduce snow accumulation and 3) details a methodology for quantifying snow losses across different designs, providing a technical rationale for snow-shedding strategies. Moreover, we demonstrate the potential for refining SAT snow-loss estimation by incorporating factors such as panel temperature, and real-time snow depth. Extending these investigations to multi-year datasets will further improve the design of reliable and cost-effective PV plants deployed in snow-prone regions and guide the future development of robust, SAT-specific snow-loss models. Performance data from January to March 2025 are still being collected, and the final analysis will include these data as well as snow less estimates over the monitored period.