针对采矿应用的双面太阳能模块平准化成本和性能分析的自适应建模

IF 8 2区 材料科学 Q1 ENERGY & FUELS
Bojja Shiva Kumar, B. M. Kunar, Ch. S. N. Murthy
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引用次数: 0

摘要

功率密度和效率通常主导着电力电子设备的设计方法。然而,这些策略无法保证成本最优。为解决这一缺陷,我们提出了一个设计框架,它能使发电系统的(i) 平准化电力成本(LCOE)、(ii) 光收集和(iii) 辐照度最小化。从改进蜂群行为优化模型以获得太阳能电池板的最小 LCOE 出发,我们设计了优化高度、倾斜角、方位角和一些参数,以求解目标函数和 LCOE 改进问题,从而获得最优设计问题。在自适应萨尔普群优化(ASSO)中,这一变化提出的模型生产者群行为被视为一个自适应过程,使算法在探索过程中不会过早收敛。利用基准测试函数证实了所提算法的性能,并将结果与萨尔普群优化(SSO)和其他高效优化算法进行了比较。在 "土地相关成本 "和 "模块相关成本 "方面的 LCOE 条件表明,双面发电场的最佳设计取决于这些参数的相互作用。该建议模型可用于评估适合采矿应用(如破碎)的建筑表面能见度。实验结果表明,在所提出的框架模型中,最低 LCOE AS 0.05(€/Kw),最低辐照度和集光度分别为 336.23(w/m2)和 83.02%。蜂群优化方法与传统求解器得出的最优参数进行了对比。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

An adaptive modeling for bifacial solar module levelized cost and performance analysis for mining application

An adaptive modeling for bifacial solar module levelized cost and performance analysis for mining application

An adaptive modeling for bifacial solar module levelized cost and performance analysis for mining application

Power density and efficiency typically dominate design approaches for power electronics. However, cost optimality is in no way guaranteed by these strategies. A design framework that minimizes the (i) levelized cost of electricity (LCOE), (ii) collection of light, and (iii) irradiance of the generation system is proposed as a solution to this flaw. From an improvement of the swarm behavior optimization model to get a minimum LCOE of solar panel, we design to optimize height, tilt angle, azimuth angle, and some parameters to solve the objective function and LCOE improvement problem to obtain the optimal design problem. In adaptive salp swarm optimization (ASSO), this change's proposed model producer swarm behavior is regarded as an adaptive process that keeps the algorithm from prematurely converging during exploration. The proposed algorithm's performance was confirmed using benchmark test functions, and the results were compared with those of the salp swarm optimization (SSO) and other efficient optimization algorithms. LCOE condition as far as “land-related cost” and “module-related cost” demonstrates that the optimal design of bifacial farms is determined by the interaction of these parameters. This proposed model can be used to evaluate visibility on building surfaces that are suitable for mining applications like crushing. Experimentation results show Minimum LCOE AS 0.05 (€/Kw)minimum irradiance and collection light as 336.23(w/m2) and 83.02%n proposed framework model. The swarm optimization method is contrasted with the optimal parameters derived from a conventional solver.

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来源期刊
Progress in Photovoltaics
Progress in Photovoltaics 工程技术-能源与燃料
CiteScore
18.10
自引率
7.50%
发文量
130
审稿时长
5.4 months
期刊介绍: Progress in Photovoltaics offers a prestigious forum for reporting advances in this rapidly developing technology, aiming to reach all interested professionals, researchers and energy policy-makers. The key criterion is that all papers submitted should report substantial “progress” in photovoltaics. Papers are encouraged that report substantial “progress” such as gains in independently certified solar cell efficiency, eligible for a new entry in the journal''s widely referenced Solar Cell Efficiency Tables. Examples of papers that will not be considered for publication are those that report development in materials without relation to data on cell performance, routine analysis, characterisation or modelling of cells or processing sequences, routine reports of system performance, improvements in electronic hardware design, or country programs, although invited papers may occasionally be solicited in these areas to capture accumulated “progress”.
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