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Volume 10,Issue 8

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7 August 2025
Optimization Design of Heliostat Field Based on Big Data Technology
Xinyu Wu ,  Hongjun Zeng ,  Hewen Wei
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1 School of Artificial Intelligence, Jianghan University, Wuhan, China,
JERA 2025 , 9(4), 204–213; https://doi.org/10.26689/jera.v9i4.11454
© 2025 by the Authors. Licensee Whioce Publishing, Singapore. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
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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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