Dr. Michael Smith, Assistant Professor, University of North Carolina at Charlotte, will give a talk entitled "Determining a preferred energy system configuration: A multi-parameter adaptable technology selection framework for nuclear-renewable hybrid energy systems"

November 15, 2024

@ 10:10 am, 440 Goodwin, Blacksburg (in-person), 6-051 VTRC, Arlington
For remote access, register by clicking here.

Abstract
Globally, nuclear-renewable hybrid energy systems (N-R HESs) are being explored as a viable way to maximize the advantages of nuclear energy while reducing the issues experienced with renewable-based energy technologies (e.g., stochastic behavior). Choosing the best generation resources to align with end-use loads requires careful consideration by organizations interested in implementing N-R HESs. Preferred HES design choices can be influenced by a number of criteria (e.g., technical maturity, scalability, location characteristics, carbon reduction potential, economic factors, alignment with an organization’s goals and objectives, and impacts on the environment). The viability of N-R HES configurations is considered in a number of recent studies, with an emphasis on determining the best N-R HES configurations primarily based on economic performance. However, decision-makers frequently need to consider a number of factors, including some that are not solely related to economics, so more than one factor (e.g., economics) needs to be considered when determining the preferred N-R HES configuration option. Therefore, to address this need, a multi-criteria technology selection framework is proposed that facilitates finding the preferred combination of energy generation resources and end-use loads to achieve the desired priority outcomes based on several factors via the multi-criteria decision-making methodology. Results from a representative N-R HES case study (i.e., configuration selection framework) are presented, including a performance evaluation via the HOMER Pro application.

Bio
Dr. Michael Smith is an Assistant Professor in the Department of Engineering Technology and Construction Management (ETCM) within the William States Lee College of Engineering at the University of North Carolina at Charlotte (UNC Charlotte). His background includes instrumentation-based process control, process modeling, data analytics, data-driven decision making, and software development, with over 10 years of industrial experience in the energy industry and more than 15 years of teaching experience. With a particular interest in industry applications, his research focus areas include: (a) control systems (e.g., adaptive control, optimal control, system dynamics, and stability), (b) process modeling and data analytics (e.g., physics-based and data-driven methods, including machine learning), and (c) monitoring/instrumentation. He has published numerous research articles (e.g., refereed journals and conference papers) in his field. He is a member of the American Nuclear Society (ANS), American Society of Mechanical Engineers (ASME), Institute of Electrical and Electronics Engineers (IEEE, Senior Member), and SME. In addition, he currently serves as an Associate Editor for IEEE Transactions on Industry Applications, Secretary for the Industrial Automation and Control Committee with the IEEE Industry Applications Society, Treasurer for IEEE Charlotte, and Vice-Chair for the ANS Fuel Cycle & Waste Management Division. Dr. Smith received a B.S. in Mechanical Engineering Technology, M.S. in Mechanical Engineering, M.S. in Electrical Engineering, and Ph.D. in Electrical Engineering from UNC Charlotte.