Abstract:In order to reduce the energy loss of the heliostat field in tower solar thermal power plants and improve the efficiency of tower solar power generation, a Monte Carlo ray tracing model is developed based on the particle swarm algorithm optimization and related data. This paper combines the actual situation of tower-type power station and related data, establishes a Monte Carlo ray tracing model based on the simulated annealing algorithm optimized by particle swarm algorithm, and researches how to optimize the layout design of the heliostat mirror field in order to improve its power generation efficiency. Firstly, the Monte Carlo ray tracing model is established, and then the theoretical model of simulated annealing algorithm is used to find the local optimal solution of the annual average thermal power output per unit mirror area, and the size parameters of heliostat mirrors are constantly changed, and the simulated annealing algorithm is used to calculate the local optimal solutions under different sizes for comparison. Finally, the simulated annealing algorithm based on particle swarm algorithm optimization is added on the basis of Monte Carlo ray tracing model by changing the size of each heliostat and its mounting height, so as to make the annual average output thermal power per unit mirror area as large as possible, which provides an effective guidance for the layout and design of heliostats in the next generation of tower-type solar power plants.