Optimization Design of Heliostat Field Based on Big Data Technology
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Keywords

Geometric modeling
Flat projection
Particle swarm algorithm
Genetic algorithm

DOI

10.26689/jera.v9i4.11454

Submitted : 2025-07-08
Accepted : 2025-07-23
Published : 2025-08-07

Abstract

In this paper, the optical efficiency and output thermal power of the heliostat mirror field are analyzed and optimized by constructing a geometric model and an optimization algorithm for the optimal design of the heliostat mirror field of a tower-type solar photovoltaic power plant. First, based on the solar position model and the optical efficiency model of the heliostat mirror field, the annual average optical efficiency, the annual average output thermal power, and the annual average output thermal power per unit mirror area of the heliostat mirror field are calculated. Secondly, the EB layout was used to optimize the heliostat field, and the parameters of heliostat size and mounting height were optimized by genetic algorithm and particle swarm algorithm to maximize the annual average output thermal power per unit mirror surface area. The results show that the optimized heliostat mirror field significantly increases the annual average output thermal power per unit mirror area under the condition of achieving the rated power, which provides theoretical basis and technical support for the design and operation of the tower solar thermal power plant.

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