Solar Hydrogen System Configuration Using Genetic Algorithms

I. Mohamed
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Abstract

For standalone power supply systems based on solar hydrogen technology to work efficiently, the photovoltaic generator and electrolyser stack have to be con?gured so that they produce the needed amount of hydrogen in order for the fuel cell to produce sufficient power to operate the load. This paper discusses how genetic algorithms were applied to optimise the design of the photovoltaic generator and electrolyser combination by searching for the best con?guration in terms of number parallel and series PV modules, number of electrolyser cells, and cell surface area. First, a mathematical simulation model based on the current-voltage PV characteristics and the polarisation characteristics of the electrolyser was developed. The models parameters were obtained by ?tting the mathematical models to experimental data. A genetic algorithm code was then developed. The code is based on the PV and electrolyser models as an evaluation measure for the ?tness of the solutions generated. Results are presented con?rming the effectiveness of using the genetic algorithm technique for solar hydrogen system con?guration.
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基于遗传算法的太阳能氢系统配置
为了使基于太阳能氢能技术的独立供电系统有效地工作,光伏发电机和电解槽堆栈必须连接在一起。使它们产生所需数量的氢,以便燃料电池产生足够的电力来运行负载。本文讨论了如何将遗传算法应用于光伏发电机组和电解槽组合的优化设计,通过寻找最佳方案。按光伏组件并联和串联数量、电解槽数量和电解槽表面积计算。首先,建立了基于电流-电压PV特性和电解槽极化特性的数学仿真模型。将数学模型与实验数据进行比较,得到了模型参数。然后开发了遗传算法代码。该代码基于PV和电解槽模型,作为生成溶液的完整性的评估措施。结果显示为:验证了遗传算法在太阳能氢能系统配置中的有效性。
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