Research on Modeling Simulation and Optimal Layout of Heliostat Field Optical Efficiency for Solar Power Tower Plant

The heliostat field is an important subsystem of the tower CSP station. The optimal layout of the heliostat field is one of the key issues to be solved in the early stage of the tower CSP station construction. Comprehensive efficiency of the heliostat field directly determines the highest performance of the power generation system. After analyzing the optical efficiency composition, optical efficiency distribution and related layout methods of the heliostat field, the goal is to have the highest annual average optical efficiency of the heliostat field. A dense simulated heliostat field with 2640 heliostats is established by the radial grid method. After selecting the appropriate heliostat field parameters, the cosine efficiency, shadow and block efficiency, atmospheric attenuation efficiency and comprehensive efficiency at different time points in the heliostat field are affected. In the optimization process, different search strategies are automatically selected, which improves the solving ability of the algorithm. Based on the Campo layout method, a new heliostat field layout method is proposed combined with the Adaptive Gravity Search Algorithm. The layout process starts from a dense heliostat field that is 1.5 times larger than the target heliostat field. The radius of the ring where the heliostat is located is used as the input variable and the annual average efficiency is used as the evaluation standard for the optimal layout of the heliostat field. After setting the corresponding constraints, the Adaptive Gravity Search Algorithm is used to find the best line spacing combination until the energy gain of the heliostat field reaches the maximum. Then, according to the design requirements, the inefficient heliostats are eliminated to obtain the final heliostat field arrangement. Finally, the heliostat field of the Gemasolar tower solar thermal power station in Seville is taken as an example to verify the method and prove the feasibility of the method.