典型的时间段还是典型的时间段？确定能源系统模型最佳时间聚集的多模型分析
Typical periods or typical time steps? A multi-model analysis to determine the optimal temporal aggregation for energy system models
摘要：
能源系统模型面临的挑战是需要高的时间和空间分辨率，以适当地描绘间歇性可再生能源，存储技术和能源部门之间日益增长的互联互通的份额。本研究通过分析不同的时间聚合技术来评估维持这些模型的计算可行性的方法，这些技术减少了输入时间序列中的时间步数。两种常用的方法是通过单个（典型）时间步长的子集或通过连续时间步长（典型周期）的组来表示时间序列。我们测试这些技术的两个不同的能源系统模型，实现使用框架的综合能源系统评估（FINE）基准的优化结果的基础上聚合的完全解决的模型，并调查是否最佳的聚合方法可以，先验，基于聚类指标确定。结果表明，典型的时间步长一致优于典型的日子就集群指标，但不导致更准确的优化结果时，应用到一个模型，考虑到许多存储技术。虽然这两种聚合技术都可以耦合聚合的时间步长，但典型日提供了更多描述存储操作的选项，而典型时间步长对于忽略时间链接约束的模型更有效。总之，聚合方法的适当选择强烈地依赖于所考虑的能量系统最优化模型的数学结构，并且充分的时间聚合的先验决定仅在充分了解该数学结构的情况下才是可能的。
英文摘要：
Energy system models are challenged by the need for high temporal and spatial resolutions in or-der to appropriately depict the increasing share of intermittent renewable energy sources, storage technologies, and the growing interconnectivity across energy sectors. This study evaluates methods for maintaining the computational viability of these models by ana-lyzing different temporal aggregation techniques that reduce the number of time steps in their in-put time series. Two commonly-employed approaches are the representation of time series by a subset of single (typical) time steps, or by groups of consecutive time steps (typical periods). We test these techniques for two different energy system models that are implemented using the Frame-work for Integrated Energy System Assessment (FINE) by benchmarking the optimization results based on aggregation to those of the fully resolved models and investigating whether the optimal aggregation method can, a priori, be determined based on the clustering indicators. The results reveal that typical time steps consistenly outperform typical days with respect to cluster-ing indicators, but do not lead to more accurate optimization results when applied to a model that takes numerous storage technologies into account. Although both aggregation techniques are ca-pable of coupling the aggregated time steps, typical days offer more options to depict storage oper-ations, whereas typical time steps are more effective for models that neglect time-linking con-straints. In summary, the adequate choice of aggregation methods strongly depends on the mathematical structure of the considered energy system optimization model, and a priori decisions of a sufficient temporal aggregation are only possible with good knowledge of this mathematical structure.
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