Speaker :Leah Guzowski, Decision and Information Sciences Division, Argonne National Laboratory
Location: University of Chicago, Searle 240A, 5735 S. Ellis Ave. This talk will be broadcast via Adobe Connect
Estimates of long-term operational energy and peak energy demand are essential for the sustainable development of new and existing urban areas. Improving energy efficiency and reducing demand in the built environment are also vital to urban development. Building the models required to simulate energy demand and consumption in existing facilities is time consuming and expensive. In addition, a great deal of uncertainty is inherent in these models because building energy use is primarily dictated by stochastic weather and building operations. The static energy models used by researchers fail to capture the variability of facility energy use.
This presentation will provide an overview of a reduced-order building energy model, based on International Organization for Standardization (ISO) standards, that allows users to incorporate both stochastic variation and input parameter uncertainty into predictions of both long-term energy use and peak demand. This tool provides a basis for probabilistic risk/benefit analysis of energy conservation measures, integration of renewable energy, and use of alternative fuels in urban environments. Finally, we will discuss the integration of this model, including directions for future research, into the Lakeside demonstration project.
Leah Guzowski is an energy policy scientist in the Decision and Information Science division at Argonne National Laboratory. She currently leads the Laboratory’s multidisciplinary Energy Security team and also the Building Energy Decision and Technology Research (BEDTR) program; her team is creating innovative, integrated systems approaches to inform global energy security solutions that are affordable, reliable, safe, sufficient and sustainable. Her current key research interests include the intersection of energy science and technology with policy. This includes the development of computational tools, methods, and analysis to better inform energy policy from a dynamic systems perspective, with a particular emphasis on economic, climate change and geo-political considerations. She is also co-leading the development of a new city-scale computational model, designed to improve urban systems integration modeling and visualization for complex decision making. This includes model integration and operational data acquisition to improve our understanding of the economic, social, safety, and other factors to predict non-deterministic city-scale phenomena and trends. In addition, she has expertise in strategically developing and leading cross disciplinary and cross institutional teams.
Prior to joining Argonne, Leah’s work spanned private industry and international trade development and policy, with particular interest in the research, development and commercialization of energy technologies. Leah graduated from Harvard University and the University of Wisconsin- Madison. She also studied economics and policy at the University of Oxford (UK). She currently serves on the Board of Directors for the Midwest Energy Efficiency Alliance. She has authored or co-authored dozens of related articles and is a frequently invited speaker at conferences across the country.
Lunch will be provided
This talk will be broadcast to Argonne National Laboratory, TCS Building 240, Room 5172.