Undergraduate Research on Big Data Analysis: Towards Large-Scale Electric Vehicle Integration Studies

With the increase in electric vehicles (EV) and heavy-duty electric vehicles (HDEV) on the roads today, an appropriate increase in charging infrastructure needs to be made to keep up with the growing load demand they”re making. To appropriately plan for developing new charging infrastructure, preliminary studies with synthetic grids that can accurately simulate how the electric grid may react are necessary. However, previous synthetic models have been insufficient as they”re either too restricting or assume ideal conditions for distribution or transmission grid aspects. With new large-scale combined transmission and distribution (T&D) grid models, the impact of both EVs and HDEVs can be accurately measured, and corresponding changes to the grid can be ensured. In a recent study to test how the I45 highway from Dallas to Houston within the U.S. state of Texas can withstand 96 test case scenarios, full T&D synthetic model simulations resulted in roughly 67.9 GB of resultant data. This paper aims to present methods for aggregating, summarizing, and analyzing the optimal power flow (OPF), generator cost, least marginal price (LMP), and overload results into easily interpretable sizes.