Backtracking 3D: A Novel Approach to Conventional Backtracking Algorithms for Improved PV Performance in Complex Terrains

Backtracking strategies are widely used in photovoltaic (PV) plants to reduce shading, but they become ineffective on the irregular terrains typical of large-scale installations. Slope-aware approaches improve performance but rely on simplified terrain models, which fail to represent the diverse slopes of real PV layouts. As a result, current methods remain limited in mitigating shading losses, reducing irradiance capture, and lowering overall energy yield. To overcome these limitations, an innovative tracking strategy based on Machine Learning is proposed to optimize the performance of PV plants in complex terrains.