Layered power scheduling optimization of PV hydrogen production system considering performance attenuation of PEMEL

IF 1.9 Q4 ENERGY & FUELS
Yanhui Xu , Haowei Chen
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引用次数: 0

Abstract

To analyze the additional cost caused by the performance attenuation of a proton exchange membrane electrolyzer (PEMEL) under the fluctuating input of renewable energy, this study proposes an optimization method for power scheduling in hydrogen production systems under the scenario of photovoltaic (PV) electrolysis of water. First, voltage and performance attenuation models of the PEMEL are proposed, and the degradation cost of the electrolyzer under a fluctuating input is considered. Then, the calculation of the investment and operating costs of the hydrogen production system for a typical day is based on the life cycle cost. Finally, a layered power scheduling optimization method is proposed to reasonably distribute the power of the electrolyzer and energy storage system in a hydrogen production system. In the up-layer optimization, the PV power absorbed by the hydrogen production system was optimized using MALTAB+Gurobi. In low-layer optimization, the power allocation between the PEMEL and battery energy storage system (BESS) is optimized using a non-dominated sorting genetic algorithm (NSGA-II) combined with the firefly algorithm (FA). A better optimization result, characterized by lower degradation and total costs, was obtained using the method proposed in this study. The improved algorithm can search for a better population and obtain optimization results in fewer iterations. As a calculation example, data from a PV power station in northwest China were used for optimization, and the effectiveness and rationality of the proposed optimization method were verified.

考虑 PEMEL 性能衰减的光伏制氢系统分层功率调度优化
为了分析质子交换膜电解槽(PEMEL)在可再生能源波动输入下的性能衰减所带来的额外成本,本研究提出了一种在光伏电解水情景下制氢系统电力调度的优化方法。首先,提出了 PEMEL 的电压和性能衰减模型,并考虑了波动输入下电解槽的衰减成本。然后,根据生命周期成本计算制氢系统典型日的投资和运营成本。最后,提出了一种分层功率调度优化方法,以合理分配制氢系统中电解槽和储能系统的功率。在上层优化中,使用 MALTAB+Gurobi 对制氢系统吸收的光伏功率进行优化。在低层优化中,使用非支配排序遗传算法(NSGA-II)结合萤火虫算法(FA)优化 PEMEL 和电池储能系统(BESS)之间的功率分配。使用本研究提出的方法获得了更好的优化结果,其特点是降低了退化和总成本。改进后的算法可以搜索到更好的种群,并以更少的迭代次数获得优化结果。以中国西北某光伏电站的数据为计算实例进行优化,验证了所提优化方法的有效性和合理性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Global Energy Interconnection
Global Energy Interconnection Engineering-Automotive Engineering
CiteScore
5.70
自引率
0.00%
发文量
985
审稿时长
15 weeks
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