Towards closing the data gap: A project-driven distributed energy resource dataset for the U.S. Grid

R. Haider, Yixing Xu, Weiwei Yang
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Abstract

Designing future energy systems with high penetrations of variable renewable energy and third-party owned devices requires information with high spatial and temporal granularity. Existing public datasets focus on specific resource classes (ex. bulk generators, residential solar, or electric vehicles), and cannot inform holistic planning or policy decisions. Further, with the high penetration of distributed energy resources (DERs) located in the distribution grid, datasets and models which focus only on the bulk system will no longer be sufficient. To meet this modelling need, this paper presents a project-driven dataset of DERs for the contiguous U.S., generated using only publicly available data. We integrate the resources into a high-resolution test system of the U.S. grid. Our integrated U.S. grid model and DER dataset enables planners, operators, and policy makers to pose questions and conduct data-driven analysis of rapid decarbonization pathways for the electricity system. We pose a set of research questions in our Research Project Database.
迈向数据鸿沟:美国电网项目驱动的分布式能源数据集
设计具有可变可再生能源和第三方自有设备高渗透率的未来能源系统,需要具有高时空粒度的信息。现有的公共数据集侧重于特定的资源类别(如大型发电机、住宅太阳能或电动汽车),不能为整体规划或政策决策提供信息。此外,随着分布式能源(DERs)在配电网中的高度渗透,仅关注批量系统的数据集和模型将不再足够。为了满足这种建模需求,本文提出了一个项目驱动的美国邻近地区的DERs数据集,该数据集仅使用公开可用的数据生成。我们将这些资源整合到美国电网的高分辨率测试系统中。我们集成的美国电网模型和DER数据集使规划者、运营商和政策制定者能够提出问题,并对电力系统的快速脱碳路径进行数据驱动分析。我们在我们的研究项目数据库中提出了一系列研究问题。
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