HeFAAL: A tool to design, analyze and optimize a solar heliostat field layout on a flat as well as uneven terrain

• Published in: Solar energy Vol. 301; p. 113915
• Main Authors: Raj, Manish, Bhattacharya, Jishnu
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 15.11.2025
• Subjects: Central receiver tower; Computational tool; Heliostat field; Layout optimization; Shading and blocking; Uneven terrain; Uneven terrain; Heliostat field; Shading and blocking; Computational tool; Central receiver tower; Layout optimization
• ISSN: 0038-092X
• DOI: 10.1016/j.solener.2025.113915

•A new tool, HeFAAL, is developed for efficient optical efficiency estimation.•It enables precise simulation of heliostat fields on flat and mountainous terrains.•PSO and GA are integrated for the layout optimization on diverse terrains.•A filtration method is developed to exclude unsuitable areas on an uneven terrain.•An algorithm is developed to accurately identify potential shaders and blockers in a hilly terrain. The performance evaluation and optimization of a heliostat field are essential steps in the development of a central receiver tower (CRT) plant. This article introduces and demonstrates Heliostat Field Analysis on Assorted Landscape (HeFAAL) − a novel computational tool designed to accurately estimate the optical efficiency of heliostat fields at a reduced computational cost on both flat and uneven terrains. Additionally, it is capable of optimizing the layout using heuristic techniques such as particle swarm optimization (PSO) and genetic algorithm (GA) on any type of terrain. A key feature of HeFAAL is its ability to simulate heliostat fields on uneven terrain. An uneven terrain presents unique challenges unlike flat fields where other existing tools such as SolarPILOT are not applicable. HeFAAL implements a systematic filtering technique to identify and exclude unusable areas within an undulated terrain. Moreover, a novel algorithm is developed to precisely identify potential shading and blocking interactions within a heliostat field on an uneven terrain. This algorithm facilitates an accurate estimation of different efficiency terms at a cheaper computational cost by eliminating double counting and by implementing sequential checks. Moreover, HeFAAL leverages parallel computing through high-performance Python libraries such as NumPy and Pandas to enhance computational efficiency.