Optimal Operation for Smart City with Model Predictive Control

Abstract

In recent years, the concentration of the world's population in urban areas has become a big issue. Countermeasures to the problems brought about by the concentration of population in cities require the efficient management and use of energy and environmental measures. In the field of microgrids, model predictive control (MPC), which can determine the future behavior of a system by incorporating both predictions and updates of data, and can efficiently handle various types of system constraints, has been attracting attention. In this research, we show the effectiveness of the Model Predictive Control as an optimization problem in smart city by operating the system to minimize the total cost.