Study on the Optimisation Scheme of Heliostat Field Based on Particle Swarm Algorithm

Tower solar thermal power generation stands as a crucial technology within the realm of renewable energy, contributing significantly to the reduction of carbon emissions. The importance of these findings is underscored in China's pursuit of 'carbon peak' and 'carbon neutrality.' Commencing with the definition of incident light unit vector L and reflected light unit vector K to ascertain cosine loss, the annual average cosine efficiency is determined as 0.6635 through traversal and averaging. Subsequently, a transformation of the heliostat coordinate system into the heliostat field coordinate system occurs, utilizing analytic geometric coordinate axis transformation. This facilitates the calculation of the mirror's ground projection. To further optimize the system, a single-objective nonlinear optimization model is formulated. The objective function is the annual average thermal power output per unit mirror area, with decision variables encompassing the Y-axis coordinates of the absorption tower's position, heliostat dimensions, and position coordinates. Stringent constraints are applied: the mirror width must not be less than its height, with the mirror size ranging between 2 m and 8 m, and the installation height falling within the 2 m to 6 m bracket. Crucially, the installation height must ensure that the rotating mirror, mounted around the horizontal shaft, does not contact the ground. Additionally, the distance between adjacent heliostat bases' centers exceeds the mirror width by at least 5 m. The conclusive phase involves the utilization of MATLAB programming, employing the particle swarm optimization algorithm to derive the final results.