GPU-based roofs' solar potential estimation using LiDAR data

Solar potential estimation using LiDAR data is an efficient approach for finding suitable roofs for photovoltaic systems' installations. As the amount of LiDAR data increases, the non-parallel methods take considerable time to accurately estimate the solar potential. Although supercomputing provides a possible solution, it is still too expensive and thus infeasible for general usage. Fortunately, the recent graphics processing units (GPUs) can now be utilized to ensure fast computations. This paper proposes a novel method for fast solar potential estimation using GPU-based CUDA technology. This method employs LiDAR data, irradiance measurements, multiresolutional shadowing from solid objects, and heuristic shadowing from vegetation. Experimental results demonstrate the method's effectiveness, in comparison with a multi-core CPU-based approach.

► Novel GPGPU solar potential estimation method using LiDAR data is proposed.
► The GPU-based implementation using CUDA is presented.
► The GPU approach is significantly faster compared to multi-core CPU approach.