Optimization design model of heliostat field based on gravitational search algorithm

Abstract

In todays society, non-renewable resources are becoming increasingly precious, making the utilization and conversion of renewable resources more critical. Heliostat fields play a significant role in the actions taken by various countries to achieve carbon peaking and carbon neutrality. How can the installation and arrangement of heliostats maximize the annual average thermal power output per unit mirror area while achieving the rated power? This paper establishes an efficiency calculation model based on the flat-plate projection-Monte Carlo algorithm and an optimization design model of heliostat fields based on the gravitational search algorithm. The research progresses from shallow to deep, investigating methods to maximize the output thermal power under different constraints. First, it addresses the issue of maximizing the average thermal power output per unit mirror area under fixed heliostat field parameters and rated power conditions. Next, it solves the problem of maximizing the annual average thermal power output per unit mirror area under varying heliostat sizes and installation heights, with fixed rated power. Finally, it points out that the models established in this paper are applicable to complex real-world situations and can effectively improve the thermal efficiency of heliostat fields.