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

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  • Xie, Qiyue
  • Guo, Ziqi
  • Liu, Daifei
  • Chen, Zhisheng
  • Shen, Zhongli
  • Wang, Xiaoli

Abstract

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 optical or concentrating efficiency of the heliostat field is increased by 8.2% compared with the GWO algorithm. 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.

Suggested Citation

  • Xie, Qiyue & Guo, Ziqi & Liu, Daifei & Chen, Zhisheng & Shen, Zhongli & Wang, Xiaoli, 2021. "Optimization of heliostat field distribution based on improved Gray Wolf optimization algorithm," Renewable Energy, Elsevier, vol. 176(C), pages 447-458.
    • Handle: RePEc:eee:renene:v:176:y:2021:i:c:p:447-458
    DOI: 10.1016/j.renene.2021.05.058
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    References listed on IDEAS

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    1. Yao, Zhihao & Wang, Zhifeng & Lu, Zhenwu & Wei, Xiudong, 2009. "Modeling and simulation of the pioneer 1MW solar thermal central receiver system in China," Renewable Energy, Elsevier, vol. 34(11), pages 2437-2446.
    2. Wang, Jianxing & Duan, Liqiang & Yang, Yongping, 2018. "An improvement crossover operation method in genetic algorithm and spatial optimization of heliostat field," Energy, Elsevier, vol. 155(C), pages 15-28.
    3. Zhang, Maolong & Yang, Lijun & Xu, Chao & Du, Xiaoze, 2016. "An efficient code to optimize the heliostat field and comparisons between the biomimetic spiral and staggered layout," Renewable Energy, Elsevier, vol. 87(P1), pages 720-730.
    4. Siala, F.M.F & Elayeb, M.E, 2001. "Mathematical formulation of a graphical method for a no-blocking heliostat field layout," Renewable Energy, Elsevier, vol. 23(1), pages 77-92.
    5. Piroozmand, Pasha & Boroushaki, Mehrdad, 2016. "A computational method for optimal design of the multi-tower heliostat field considering heliostats interactions," Energy, Elsevier, vol. 106(C), pages 240-252.
    6. Collado, Francisco J. & Guallar, Jesus, 2019. "Quick design of regular heliostat fields for commercial solar tower power plants," Energy, Elsevier, vol. 178(C), pages 115-125.
    7. Wei, Xiudong & Lu, Zhenwu & Wang, Zhifeng & Yu, Weixing & Zhang, Hongxing & Yao, Zhihao, 2010. "A new method for the design of the heliostat field layout for solar tower power plant," Renewable Energy, Elsevier, vol. 35(9), pages 1970-1975.
    8. Collado, Francisco J. & Guallar, Jesús, 2012. "Campo: Generation of regular heliostat fields," Renewable Energy, Elsevier, vol. 46(C), pages 49-59.
    9. Besarati, Saeb M. & Yogi Goswami, D., 2014. "A computationally efficient method for the design of the heliostat field for solar power tower plant," Renewable Energy, Elsevier, vol. 69(C), pages 226-232.
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    Cited by:

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