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  4. Vol 4, Issue 3, 2023

Research on Heliostat Field Based on Multi-objective Optimization Intelligent Algorithm

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DOI: 10.23977/autml.2023.040310 | Downloads: 4 | Views: 202

Author(s)

Yang Zhengshuai 1

Affiliation(s)

1 Department of Business, Nantong Institute of Technology, Nantong 226000, China

Corresponding Author

Yang Zhengshuai

ABSTRACT

By employing the discretization principle, ray tracing method, and coordinate system transformation technique, this paper has made significant advancements in optimizing heliostat field parameters. Through a comprehensive examination of the optical efficiency of the heliostat and utilizing genetic algorithm, systematic optimization of the heliostat field parameters is conducted to seek out the optimal solution. Firstly, it is essential to clarify the optimization criteria, which include the position coordinates of the absorption tower, size of the heliostat, installation height, number of heliostats, and their respective positions. To address multiple constraints effectively, an objective function is formulated based on the annual average thermal power output per unit mirror area. The position coordinates of absorbers are considered separately by calculating thermal power output for both (0,0) and non-(0,0) coordinates to determine optimal conditions through comparison. After that, using genetic algorithm and MATLAB software package enables obtaining optimized parameters for the heliostat field. In this optimal scenario, the absorption tower's position coordinate is (0, 0), each heliostat measures 8m*8m with an installation height of 4; there are a total of 2172 heliostats covering a combined area measuring 139008 m2. The innovation in this research methodology lies in its comprehensive utilization of the discretization principle while accurately analyzing optical properties through the ray tracing method. Additionally, the complex structure within the heliostat field is aptly described through clever coordinate system transformations. Finally, the combination that optimizes parameters for heliostat fields is effectively searched using genetic algorithms. This provides robust theoretical support for designing light energy utilization systems.

KEYWORDS

Discretization principle; Heliostat field; Ray tracing model; Genetic algorithm

CITE THIS PAPER

Yang Zhengshuai, Research on Heliostat Field Based on Multi-objective Optimization Intelligent Algorithm. Automation and Machine Learning (2023) Vol. 4: 80-86. DOI: http://dx.doi.org/10.23977/autml.2023.040310.

REFERENCES

[1] Liu J X. Modeling and simulation of optical efficiency of tower photothermal power station and optimization of heliostat field placement [D]. Lanzhou jiaotong university, 2023. 
[2] Sun H. Research and optimization of heliostat field layout based on hybrid strategy whale optimization algorithm [D]. Lanzhou jiaotong university, 2023. 
[3] Yao M K. Research on focus imaging strategy and control system design of tower solar heliostat [D]. Zhejiang University,2012.
[4] Gao Weidong. Solar power tower heliostat field scheduling optimization research [D]. North China electric power university, 2022.
[5] Ding Tingting. Optimization and Simulation research on the field of tower solar thermal generator mirror [D]. Nanjing Normal University,2013.
[6] Cheng Xiaolong, Yin Yanguo, Ma Shaobo. Optimization design of heliophoid field layout for tower power station [J]. Energy and Environment,2018(02):64-66+70.
[7] Xiao Yixing. Distribution optimization and cluster control of heliostat field in tower solar thermal power plant. Changsha University of Science and Technology,2020.
[8] Zhang Ping, et al. Calculation method of field optical efficiency of solar tower photothermal mirror [J], Technology & Market, 2021,28 (6):5-8.
[9] N. Srinivas and K. Deb, "Muiltiobjective Optimization Using Nondominated Sorting in Genetic Algorithms," In Evolutionary Computation, vol. 2, no. 3, pp. 221-248, Sept. 1994, doi: 10.1162 / evco 1994.2.3.221.
[10] Du Yuhang et al. Influence Analysis of Different Focusing Strategies of Heliostat in Tower Solar thermal Power Station [J]. Chinese Journal of Power Engineering, 2020, 40(5):426-432.

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