Research on Heliostat Field Design Based on Intelligent Optimization Algorithm

In this paper, a nonlinear goal programming model is established by analyzing the incidence and reflection of solar rays on heliostats. The method comprises the following steps of: calculating a sun altitude angle and an azimuth angle at different times, obtaining a direction vector of a solar ray in a ground coordinate system through angle transformation, obtaining a direction vector of corresponding reflected light rays by traversing position coordinates of different heliostats, and calculating cosine efficiency through an included angle of an incident light ray and a reflected light ray. Based on the ray tracing method of Monte Carlo random simulation, the shadow occlusion efficiency is calculated. A light cone model is established, and the input and output of reflected sunlight energy are replaced by the projected and received areas, and the truncation efficiency is calculated, and finally solving the atmospheric transmittance and obtaining the optical efficiency at different times according to a certain specular reflectance. In order to maximize the average output heat power per unit mirror surface area, the number, size and mounting height of heliostats, as well as the positions of heliostats, are optimized by using differential evolution algorithm. The cosine efficiency, shadow shielding efficiency and truncation efficiency in the optical efficiency are calculated, and the number, position, size, installation height and other parameters of heliostats are searched and solved to maximize the annual average output heat power of unit mirror surface area. The establishment of nonlinear goal programming model to optimize the parameters of heliostat field has certain practical significance and can be used in a wide range of fields.