Energy Management System for Smart Microgrids Considering Energy Theft

In this paper, a proposed energy management system for a smart microgrid (SMG) has been implemented. It is based on demand response and electricity theft detection. The objectives of the proposed algorithm are electricity cost minimization and user comfort maximization. A genetic algorithm (GA) has been used to obtain the optimal load management decisions to achieve the system's objective functions with the satisfaction of different operational constraints as maximum and minimum values for charging and discharging batteries and distributed energy resources (DER) limits. All the system loads are controlled using sensors connected to each appliance at the consumer's side. The data are sent to the central management unit that indicates the system load operation status as controllable, shedable, and shiftable. The results show the effectiveness of the proposed algorithm in the reduction of electricity costs and detecting energy theft.