Research on Optimization Design of Heliostat Field Based on Particle Swarm Optimization Algorithm

Abstract

In the optimization design process of heliostats, this article constructs physical equations by establishing a spatial Cartesian coordinate system and quantifies the obtained data. The penalty function is used to intervene in the particle swarm intelligence algorithm and iterate repeatedly to obtain the optimal parameters. Firstly, the coordinates of the heliostat were visualized in three dimensions, and a spatial Cartesian coordinate system centered on the light collecting tower was established. Use the two-dimensional relationships between internal components of the system to calculate the angle between incident and outgoing rays and reflected rays, and then calculate the cosine efficiency. Secondly, based on the calculation of the sun's altitude angle and azimuth angle, the shadow occlusion efficiency was obtained. Finally, the known formula is used to calculate the annual average optical efficiency, which is 71.14%. The output thermal power is 42.628 MW, and the annual average output thermal power per unit mirror area is 0.678249917 kW/m².