Research On the Design of Fixed-Sun Mirror Field Based on Particle Swarm Optimisation Algorithm

Abstract

Solar energy, as one of the energy types mainly utilized in renewable energy, is the utilization of thermal radiation energy in the light rays irradiated to the earth by the sun. Photovoltaic power generation is a more widely used form of solar energy utilization, in order to maximize the use of solar energy, limited to the tower photovoltaic plant footprint, you can change the distribution of heliostat mirrors, so that the mirror field presents a better distribution. This paper aims to improve the efficiency of the mirror field as a whole on the use of solar energy, by analyzing the geometric relationship between the sun position and absorption tower and all the heliostat mirrors, calculate the average annual optical efficiency of the heliostat mirror field, the average annual output thermal power, and the average annual output thermal power per unit of the mirror surface area, the use of the shadow masking model the model to get the calculation of the thermal power of the parameters needed. Then, the potential geometrical dimensions and mounting height combinations of the heliostat were formulated, and an optimization scheme for the annual average thermal power based on the particle swarm optimization algorithm was constructed. The PSO particles are initialized with the heliostat to obtain the optimal solution for the heliostat installation. Finally, the annual average thermal power optimization scheme based on particle swarm optimization algorithm is constructed, and the optimal solutions for the installation of heliostat and the location of the absorber tower are obtained by iteratively eliminating the poor-quality solutions.