2 Search Results

In this study, we propose a strategy to model the required spatiotemporal charging demand from light-duty (LD) and medium- and heavy-duty (MHD) electric vehicles (EVs) using actual transportation data by mapping the demand for the required EV charging to a realistic and coordinated distribution and transmission electric grid at the predicted times of the day to study their impact on the power system in a variety of load, weather, and EV penetration scenarios. This work is the first study that includes the actual weather data and transportation data with realistic and coordinated distribution and transmission grid data in a largemore » industry-scale level study. The main goal of this study is to identify possible issues and required upgrades in the electric grid, caused by an increase in EV integration. The transmission case study is a large grid with 6717 buses over a Texas footprint, and the distribution grid is over Houston, a city in Texas, covering over three million customers. The resulting overloads and voltage violations experienced in the system are discussed, and required planning upgrades to avoid these issues are suggested.« less

The spatiotemporal distribution of pollutants plays a significant role on their impact on ecosystems and human health. This article presents a strategy for calculating spatiotemporal operational emissions (OEs) of road transportation and the electric grid to quantify the impact of transportation electrification. Emissions from internal combustion engine vehicles and offset emissions from electric vehicles (EVs) are considered using actual transportation networks and travel data. The spatiotemporal charging demand for light-, medium-, and heavy-duty EVs is estimated in a behaviorally informed way and mapped to electrical buses within the power grid and an ac optimal power flow with unit commitment ismore » solved. The methodology is demonstrated with ten scenarios simulated on a grid with 7000 electrical buses geographically sited in Texas, created with actual generator data for the 2020 grid, and a future case, including anticipated generator updates by 2030. Results show overall transportation emission reductions in daily OEs of up to 20%–30% for all pollutants studied, outweighing the increase in emissions from the electric grid. Furthermore, considering emissions on an hourly basis, up to approximately 1000% reduction in CO emissions is observed.« less