EAGER: SSDIM: Synthetic and Simulated Data for American Multi-Modal Energy Systems

这个早期概念探索性研究补助金(AGER)项目旨在开发和提供关于美国四个不同但高度相互依赖的关键基础设施(ICIS)的模拟和合成数据：电网、天然气供应链、石油供应链和煤炭供应链。作为一个系统，这四个基础设施共同定义了美国多模式能源系统(AMES)。该项目的所有数据和软件将免费和公开提供，以促进学术界、工业界和政府对Ames的研究，以及软件代码的重复使用和改进。通过这项研究开发的方法将被整合到本科生和研究生的达特茅斯工程系统工程课程中，并通过欧文能源与电力社会研究所和edX平台在网上进行更广泛的交流。AMES机械和人类方面的模拟和合成数据的开发将从根本上提高对这些系统的结构和行为的理解。这一目标将通过解决如何通过算法将原始数据转换为Ames的模拟数据集，以及通过对Ames系统行为的高级数学建模来丰富模拟数据集来实现。这项工作将导致Ames的结构异功能图模型，以及与Ames上最好的可用数据相对应的动态、空间分布的模拟。

This EArly-concept Grant for Exploratory Research (EAGER) project seeks to develop and make available simulated and synthetic data on four distinct but highly interdependent critical infrastructures (ICIs) in the United States: the electric power grid, the natural gas supply chain, the oil supply chain, and the coal supply chain. When viewed together as a single system, these four infrastructures define the American Multi-Modal Energy System (AMES). All data and software from this project will be made freely and publicly available in order to facilitate academic, industry, and government research on the AMES, as well as reuse and refinement of software code. Methods developed through this research will be integrated into the Dartmouth engineering systems curriculum at the undergraduate and graduate levels and communicated more broadly online through the Irving Institute for Energy & Society and the edX platform. The development of simulated and synthetic data on mechanistic and human aspects of AMES will fundamentally improve understanding of the structure and behavior of these systems. This objective will be achieved by addressing how can raw data be algorithmically converted into a simulated dataset of the AMES, and by enriching the simulated dataset through advanced mathematical modeling of AMES system behavior. This work will lead to a structural hetero-functional graph model of the AMES, as well as to a dynamic, spatially-distributed simulation that corresponds to the best available data on the AMES.