Pacific Northwest National Laboratory, Richland, WA, USA.
University of Washington, Seattle, WA, USA.
Sci Data. 2022 Nov 4;9(1):675. doi: 10.1038/s41597-022-01748-x.
The U.S. Energy Information Administration (EIA) conducts a regular survey (form EIA-923) to collect annual and monthly net generation for more than ten thousand U.S. power plants. Approximately 90% of the ~1,500 hydroelectric plants included in this data release are surveyed at annual resolution only and thus lack actual observations of monthly generation. For each of these plants, EIA imputes monthly generation values using the combined monthly generating pattern of other hydropower plants within the corresponding census division. The imputation method neglects local hydrology and reservoir operations, rendering the monthly data unsuitable for various research applications. Here we present an alternative approach to disaggregate each unobserved plant's reported annual generation using proxies of monthly generation-namely historical monthly reservoir releases and average river discharge rates recorded downstream of each dam. Evaluation of the new dataset demonstrates substantial and robust improvement over the current imputation method, particularly if reservoir release data are available. The new dataset-named RectifHyd-provides an alternative to EIA-923 for U.S. scale, plant-level, monthly hydropower net generation (2001-2020). RectifHyd may be used to support power system studies or analyze within-year hydropower generation behavior at various spatial scales.
美国能源信息署（EIA）定期进行调查（表格 EIA-923），以收集超过一万家美国发电厂的年度和月度净发电量。在本次数据发布中，大约 90%的~1500 座水力发电厂仅以年度分辨率进行调查，因此缺乏月度发电量的实际观测值。对于这些工厂中的每一个，EIA 使用相应普查分区内其他水力发电厂的组合月度发电模式来推断月度发电量。这种推断方法忽略了当地的水文和水库运行情况，使得月度数据不适合各种研究应用。在这里，我们提出了一种替代方法，可以使用月度发电量的代理指标（即历史月度水库放水和每个大坝下游记录的平均河川流量）来分解每个未观测到的工厂的报告年度发电量。对新数据集的评估表明，与当前的推断方法相比，它有显著且稳健的改进，特别是如果有水库放水数据。这个名为 RectifHyd 的新数据集为 EIA-923 提供了替代方案，用于美国规模、工厂级、月度水力发电净发电量（2001-2020 年）。RectifHyd 可用于支持电力系统研究，或在各种空间尺度上分析年内水力发电行为。
