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Optimization of heliostat field distribution based on improved Gray Wolf optimization algorithm

delete2021-10-01
delete47
PRE
AI
谢七月 (Qiyue Xie)
Z
Ziqi Guo
D
Daifei Liu *
陈志盛 (Zhisheng Chen)
Z
Zhongli Shen
王小莉 cover
王小莉 (Xiaoli Wang)
DOI:10.1016/j.renene.2021.05.058delete
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Abstract

Abstract

En 中文
The heliostat field of tower solar thermal power station accounts for 40%-50% of the total cost, and influences the concentrating efficiency. Accordingly, it is necessary to optimize the layout of the heliostat field. Based on the optical efficiency model, an improved Gray Wolf Optimization (GWO) algorithm is proposed to optimize the field parameters of the heliostats, improve the convergence factor and weight updating formula, and effectively avoid the local optimal problem. Then SolarPILOT software is used to simulate the heliostat field distribution. In order to reduce the shadow and shielding efficiency loss, improve the land utilization rate and atmospheric attenuation efficiency, the heliostat field is initialized by radial staggered arrangement, which is easy to be optimized. By using the optical efficiency model, the program of heliostat field optimization algorithm is developed, and a Delingha tower power station is used to verify the algorithm. After the improved GWO algorithm optimizing the heliostat field, the op-tical or concentrating efficiency of the heliostat field is increased by 8.2% compared with the GWO al-gorithm. The improved GWO algorithm reduces the heliostat number by 3.4% compared with the Gray Wolf algorithm, and that reducing the cost of the heliostat field. (c) 2021 Elsevier Ltd. All rights reserved.
Keywords:
Heliostats layout
Optical efficiency
Gray wolf optimization
Solar power system
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Journal

Renewable Energy cover
Renewable Energy
IF:
9.1
Papers:
2.6W
Citations:
12.1W

Organization

C
Central South University
Scholars:
10.0W
Papers: 7.2W
Citations: 10.9W