1. Optimization of heliostat field distribution based on improved Gray Wolf optimization algorithm
- Author
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Qiyue Xie, Xiaoli Wang, Chen Zhisheng, Ziqi Guo, Zhongli Shen, and Daifei Liu
- Subjects
Heliostat ,060102 archaeology ,Field (physics) ,Power station ,Renewable Energy, Sustainability and the Environment ,Computer science ,business.industry ,020209 energy ,Attenuation ,Thermal power station ,06 humanities and the arts ,02 engineering and technology ,Software ,Control theory ,Electromagnetic shielding ,Convergence (routing) ,0202 electrical engineering, electronic engineering, information engineering ,0601 history and archaeology ,business - 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.
- Published
- 2021