Comparative Assessment of Models and Methods To Calculate Grid Electricity Emissions.
Comparative Assessment of Models and Methods To Calculate Grid Electricity Emissions.
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DOI：
10.1021/acs.est.5b05216
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发表时间：
2016-08
影响因子：
11.4
通讯作者：
N. A. Ryan;Jeremiah X. Johnson;G. Keoleian
中科院分区：
文献类型：
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作者：
N. A. Ryan;Jeremiah X. Johnson;G. Keoleian
由于电力系统的复杂性，跟踪可归因于特定电力负荷的排放是一项艰巨的挑战，但对于许多环境影响研究至关重要。目前，对于量化特定电力负荷排放的适当方法还没有达成共识。本文回顾了广泛的现有方法，详细介绍了它们的功能、可追溯性和适当的使用。我们鉴定并回顾了32种方法和模型，并将它们分为两大类：经验数据和关系模型和电力系统优化模型。为了说明方法选择的影响，我们在美国各地的9个充电站使用10种方法计算了与电动汽车充电相关的二氧化碳燃烧排放因子。在这些方法中，我们发现给定充电点的边际和平均排放系数与平均二氧化碳排放系数相差高达68%，与平均排放系数相差高达63%。我们的研究结果强调了方法选择的重要性，以及在适合特定负载和研究问题的方法上达成共识的必要性，以便在研究中获得更一致的结果，并允许有充分支持的政策决策。本文通过提供一组基于负载特性和研究目标确定适当模型类型的建议来解决这个问题。
Due to the complexity of power systems, tracking emissions attributable to a specific electrical load is a daunting challenge but essential for many environmental impact studies. Currently, no consensus exists on appropriate methods for quantifying emissions from particular electricity loads. This paper reviews a wide range of the existing methods, detailing their functionality, tractability, and appropriate use. We identified and reviewed 32 methods and models and classified them into two distinct categories: empirical data and relationship models and power system optimization models. To illustrate the impact of method selection, we calculate the CO2 combustion emissions factors associated with electric-vehicle charging using 10 methods at nine charging station locations around the United States. Across the methods, we found an up to 68% difference from the mean CO2 emissions factor for a given charging site among both marginal and average emissions factors and up to a 63% difference from the average across average emissions factors. Our results underscore the importance of method selection and the need for a consensus on approaches appropriate for particular loads and research questions being addressed in order to achieve results that are more consistent across studies and allow for soundly supported policy decisions. The paper addresses this issue by offering a set of recommendations for determining an appropriate model type on the basis of the load characteristics and study objectives.