Seminar: Joohyun Kim

Friday, January 21, 2022 11:00 am - 11:00 am EST (GMT -05:00)

Optimization of Consumer-Producer Storage in Renewable Energy Markets: A Mean Field Approach

Joohyun Kim

Department of Operations Research and Engineering Management
Southern Methodist University



We quantitatively study the dynamic competition among a large number of interacting households who own local storage with a self-generated renewable energy system and a grid operator. Each can decide the amount of charging or discharging energy based on the market environment and the level of energy stored. Despite the importance of the optimal inventory management of local energy storage in the grid system, little is explored analytically in a lack of proper analytical modeling. We consider a dynamic integration model between a grid and a large number of households using an extended mean field type approach, where both the state equation and the pay-off depend on the evolution of the probability distribution of the state and the control. We explicitly obtain the explicit solution regarding the optimal energy charging or discharging decision rule of local energy storage, which can be interpreted as an optimal policy suggestion by a central planner who is willing to enhance the resilience of the grid system. Further numerical experiments suggest that a local storage strategy can remedy and reduce the fluctuation of the market price of energy.

Biographical Sketch

Joohyun Kim is a Post-doctoral Fellow in the Operations Research and Engineering Management Department at Southern Methodist University. He earned his PhD degree in management science with a concentration in operations management from The University of Texas at Dallas. Prior to his Ph.D. study, he received a bachelor’s degree in mechanical engineering from Sogang University and a master’s degree in management science from Korea Advanced Institute of Science and Technology. His research interests involve developing and improving the application of analytical models to business decision-making processes.