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Mathematical Models and Analysis for Demand Side Management in Residential Electricity Distribution Networks

Dr. Lihui Bai
Associate Professor of Industrial Engineering
University of Louisville
Friday, October 23, 2020
3:30-4:30pm Zoom


Demand response (DR) is a market-based mechanism to shave peak electricity consumption at the system level under a smart grid. In this talk, we first develop a control algorithm for Heating Ventilation Air-Conditioning (HVAC) systems in households during a peak period. A dynamic programming based model will determine the optimal temperature set-points of a thermostat given the lower and upper limits of temperature that household feels comfortable and the desired duration of the control. Second, we propose a mixed-integer linear fractional programming (MILFP) model to optimally deploy the dynamic programming based HVAC controllers among a pool of homes in a staggered fashion so as to maximize the load factor for the entire distribution network. Third, we study price-responsive behavior of consumers when subject to dynamic pricing under a DR program, using a bi-level programming model to estimate the coefficients of a utility function.  Consumption data from the advanced metering infrastructure (AMI) in the field demonstration project was used in the numerical study. The computational results show a strong positive correlation between the utility coefficients and the widely used price elasticity in the economic theory.


Dr. Lihui Bai is an associate professor of Industrial Engineering at the University of Louisville.  Dr. Bai’s research interests include operations research, optimization models and algorithm development, transportation in logistics and supply chain management, energy systems and healthcare logistics.  Her recent works have been funded by DHS, GE Appliances, FHWA through Kentucky Transportation Cabinet, and National Science Foundation.