On October 5, 2022, Dr. Renee Obringer from Penn State’s Department of Energy and Mineral Engineering will present “A Data-driven Systems Approach for Modeling the Climate-induced Shifts in Future Electricity Demand” as part of the EEEP Seminar Series.
Abstract: Soaring temperatures and increased frequency of heatwaves have changed the way many people use electricity, often leading to higher consumption during the summer months. This trend is likely to continue as climate change progresses and temperatures increase. In order to ensure our electricity grid is prepared for these changes, it is important to develop accurate predictive models that account for climate-induced shifts in demand. Here, I will present results from two studies that leverage state-of-the-art data analytics to investigate the impact of climate change on electricity demand. The first study focuses on city-wide demand, while the second aims to evaluate changes in household-level air conditioning use. Together, these studies demonstrate the impact climate change is likely to have on the larger electricity grid, as well as the implications for residents. Understanding these shifts is a critical step to improving the resilience of our electricity infrastructure in the face of climate change.
Speaker Bio: Dr. Renee Obringer is an assistant professor with the Department of Energy and Mineral Engineering, where her research focuses on leveraging data science methods to better understand the impact of weather and climate on critical infrastructure systems. She is particularly interested in studying climate change impacts to interdependent infrastructure systems (e.g., water-energy nexus). Dr. Obringer is also a faculty associate in the Earth and Environmental Systems Institute. She holds a Ph.D. in environmental and ecological engineering from Purdue University and a B.S. in environmental engineering from Ohio State University. Prior to working at Penn State, Dr. Obringer was a postdoctoral research fellow at the National Socio-Environmental Synthesis Center (SESYNC) within the University of Maryland.