Optimization design of heliostat field parameters based on gray Wolf algorithm

Abstract

Tower solar thermal power generation is the most promising way of light energy utilization in China at present, and it is also an important program to achieve the strategic goal of "carbon neutrality" and "carbon peak". In order to obtain the best solar optical efficiency and maximize the use of solar energy, how to design the relevant parameters of the heliostats field, the core equipment of tower solar solar thermal power generation, is extremely important. In this paper, the objective function, constraint conditions and decision variables are established based on the premise that the average annual output thermal power per unit mirror area is maximum and the rated average annual output thermal power of heliostat field is 60MW. Five specific times on the 21st day of each month are used to solve the relevant values, and several calculation models, including the sun position model and the optical efficiency model of heliostat field, are established. Then the grey Wolf algorithm is selected to optimize the model, and the decision variables are substituted into the grey Wolf optimization algorithm. When the Wolf pack updated the data every time, the decision variables were substituted into the DELSOL3 empirical layout, and finally the accurate and reliable heliostat field related layout parameters were obtained.