Concentrating Simulation And Aiming Strategy Optimization Of Solar Tower Power System

Solar tower power system is an ideal form for collecting solar energy and generating electricity in a large scale, thus having a broad prospect. The function of the concentration and collection subsystems, which are comprised of the heliostat field and the receiver, has a direct influence on the operation of the subsequent subsystems and even affects the performance of the whole system. In order to provide a reference basis for the design and operation of real plants, it is of realistic significance to conduct research on the concentrating simulation and the aiming strategy of the concentration and collection subsystems.Fast and accurate concentrating simulation and effective aiming strategy are studied in this thesis. The main contributions of this thesis are as follows:(1) On the basis of non-parallel sunlight, the model for the concentration and collection subsystems is established and the concentrating procedure is analyzed. A technique which is a combination of geometric projection method and ray-tracing method is proposed to achieve the concentrating simulation. As a consequence, the optical efficiency of the heliostat field and the flux density distribution on the receiver are obtained. The validity of the proposed technique is verified by the comparison between the simulation results and experimental data.(2) GPU (Graphic Processing Unit) based parallel computing accomplished on CUDA (Compute Unified Device Architecture) platform is introduced to reduce the running time of the simulation program. The results demonstrate that the simulation is greatly accelerated by utilizing GPU while maintaining the same accuracy.(3) On the basis of the completed work aforementioned, an aiming strategy optimization model is presented to achieve uniformly distributed flux density on the receiver on the premise of high energy collected by the receiver. The aiming point for each heliostat field sub-region is determined via an improved genetic algorithm. The optimized aiming strategy is beneficial for the operating performance of the system.