A High-Resolution Irradiance-Based Optimization Framework for Fixed and Seasonal Photovoltaic Tilt Selection Using NSRDB Data

Photovoltaic (PV) tilt optimization is commonly guided by latitude-based rules, but these heuristics do not explicitly account for sub-daily irradiance variability, diffuse-fraction behavior, or local atmospheric attenuation. This study presents FT-PVOT, a geometry-resolved framework that integrates National Solar Radiation Database (NSRDB) irradiance data with solar-position and plane-of-array (POA) transposition equations to identify irradiance-maximizing fixed and seasonal PV tilt angles. Direct normal irradiance, diffuse horizontal irradiance, and global horizontal irradiance were evaluated using a brute-force tilt sweep from 0° to 90° at 1° increments. The method was tested for Gainesville, Florida (29.65° N), using 2018-2023 NSRDB data and benchmarked against PVWatts tilt trends. The annual fixed optimum remained highly stable across the six-year period, ranging from 28° to 29° with a mean of approximately 28.8° and a standard deviation of approximately 0.41°. PVWatts produced an annual optimum of 29°, yielding a mean difference of approximately 0.17°. Relative to flat mounting, latitude tilt increased annual POA irradiation by approximately 9.2%, annual optimization by 9.6%, biannual adjustment by 13.5%, and monthly adjustment by 15.1%. However, monthly adjustment added only 1.6 percentage points, or approximately 27 kWh/m²/year, beyond biannual adjustment. Cloudy-sky conditions reduced annual POA irradiation by approximately 35.5% relative to the clear-sky case, but the annual optimum fixed tilt remained approximately 29°. These results show that high-resolution irradiance integration can convert latitude-based tilt guidance into a quantified, reproducible, location-specific design recommendation while preserving a clear distinction between irradiance optimization and full PV electrical-output prediction.: