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Energy system analysis of utilizing hydrogen as an energy carrier for wind power in the transportation sector in Western Denmark

机译:丹麦西部交通运输业中利用氢作为风力发电的能源载体的能源系统分析

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Hydrogen is an energy carrier that can potentially be used for introducing renewably generated electricity into the transportation sector. This paper presents a methodology for an overall energy system analysis of a hydrogen infrastructure, which meets a transportation hydrogen demand profile. The methodology starts by building a mathematical model for optimizing the economic operation of electrolyzers on the electricity market by use of Genetic Algorithms. Demand profiles from the optimization are then included in an overall energy system analysis model studying the electricity market and power balance system effects. A sample 2030 scenario analysis of Western Denmark is presented to demonstrate the applicability of the devised methodology. It is shown that Genetic Algorithms is a flexible tool that can be adapted to optimization problems involving energy storage. On the other hand, it is found that the ability of Genetic Algorithms to find a solution is highly dependent on initial variables and the storage constraint. Further analysis is required in order to test and expand the methodology and scenario results.
机译:氢是一种能源载体,可以潜在地用于将可再生发电的电能引入运输部门。本文提出了一种用于氢基础设施的整体能源系统分析的方法,该方法可以满足运输氢的需求量。该方法首先建立一个数学模型,以使用遗传算法优化电市场上电解槽的经济运行。然后,将来自优化的需求曲线包含在研究能源市场和电力平衡系统影响的整体能源系统分析模型中。本文介绍了西丹麦的2030年情景分析示例,以证明该方法论的适用性。结果表明,遗传算法是一种灵活的工具,可以适应涉及能量存储的优化问题。另一方面,发现遗传算法找到解的能力高度依赖于初始变量和存储约束。为了测试和扩展方法论和方案结果,需要进行进一步的分析。

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