针对塔式太阳能热发电电站中定日镜场优化布置问题,提出一种基于自适应引力搜索算法的定日镜场优化布置方法。以Campo布置规则为基础建立比目标定日镜场大1.5倍的密集型初始镜场,将定日镜所在环的半径作为输入变量并将年均效率作为镜场优化布置的评价标准。通过在引力搜索算法中引入动态调整因子α,可提高算法在高维搜索问题方面的求解能力。最后以塞维利亚Gemasolar电站的定日镜场为例进行优化布置,证明使用自适应引力搜索算法优化后的定日镜场具有更高的年均效率。
Abstract
To solve the problem of heliostat field layout optimization in tower CSP （Concentrating Solar Power） station, a method based on AGSA （Adaptive Gravity Search Algorithm） is proposed. According to the Campo layout rules, a dense initial heliostat field 1.5 times larger than the target heliostat field is established,and the radius of each row of heliostats is used as an input variable and the annual average efficiency is used as the evaluation criterion for the optimal layout of the heliostat field. In addition, a dynamic adjustment factor α is introduced into the gravitational search algorithm, which improves the algorithm's ability to solve high-dimensional search problems. Finally,taking the heliostat field of Gemasolar in Sevilla as an example to optimize the layout, and the results have suggested that the heliostat field optimized by the AGSA has a higher average annual efficiency.
关键词
塔式太阳能热发电 /
定日镜 /
优化设计 /
自适应引力搜索算法
Key words
tower solar thermal power /
heliostats /
optimization /
adaptive gravity search algorithm
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参考文献
[1] 张茂龙, 卫慧敏, 杜小泽, 等. 塔式太阳能镜场阴影与遮挡效率的改进算法[J]. 太阳能学报, 2016, 37(8): 1998-2003.
ZHANG M L, WEI H M, DU X Z, et al.Modified algorithm of shadow and blocking efficiency for heliostat field of solar power tower[J]. Acta energiae solaris sinica, 2016, 37(8): 1998-2003.
[2] ATIF M, AL-SULAIMAN F A. Optimization of heliostat field layout in solar central receiver systems on annual basis using differential evolution algorithm[J]. Energy conversion and management, 2015, 95(1): 1-9.
[3] ARRIF T, BENCHABANE A, GERMOUI M, et al.Optimisation of heliostat field layout for solar power tower systems using iterative artificial bee colony algorithm: a review and case study[J]. International journal of ambient energy, 2021, 42(1): 65-80.
[4] LI C, ZHAI R R, LIU H T, et al.Optimization of a heliostat field layout using hybrid PSO-GA algorithm[J]. Applied thermal engineering, 2018, 128(8): 33-41.
[5] COLLADO F J, GUALLAR J.Campo: generation of regular heliostat fields[J]. Renewable energy, 2012, 46(3): 49-59.
[6] ABATUT J L, ACHAIBOU A.Analysis and design of a field of heliostats for a solar power plant[J]. Pergamon, 1978, 21(6): 453-463.
[7] BESARATI S M, YOGI G D.A computationally efficient method for the design of the heliostat field for solar power tower plant[J]. Renew energy, 2014, 69(2): 226-232.
[8] SASSI G.Mathematical model for a noniterative optimization of each system for exploiting solar energy[J]. IL nuovo cimento C, 1982, 5(1): 99-111.
[9] LIPPS F W.A numerical approach to the flux density inte-gral for reflected sunlight[J]. Solar energy, 1980, 24: 461-469.
[10] COLLADO F J, GOMEZ A, TUREGANO J A.An ana-lytic function for the flux density due to sunlight reflected from a heliostat[J]. Solar energy, 1986, 37(3): 215-234.
[11] 程小龙, 尹延国, 马少波. 塔式电站定日镜场布局的优化设计研究[J]. 能源与环境, 2018(2): 64-66, 70.
CHENG X L, YIN Y G, MA S B.Research on the optimal design of the layout of the heliostat field of tower power station[J]. Energy and environment, 2018(2): 64-66, 70.
[12] ESMAT R, HOSSEIN N, SAEID S, et al.GSA: a gravitational search algorithm[J]. Information sciences, 2009, 179(13): 2232-2248.
[13] LATA J, Alcalde S, FERNANDEZ D, et al.First surrounding field of heliostats in the world for commercial solar power plants, Gemasolar[J]. Proceedings of solarpaces, 2010, 56(3): 236-245.
[14] REDA I, ANDREAS A.Solar position algorithm for solar rad-iation applications[J]. Solar energy, 2004, 76(5): 577-589.
基金
国家重点研发计划（SQ2020YFF0413296）
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