Simulating energy management strategies for microgrids with smart meter demand management

This paper considers the simulation of microgrids with smart meters that make it possible to control the demand at individual consumer buildings. To create effective system-level models for simulation studies of energy management strategies, probability distributions for the aggregate demand of all system loads are computed from probability distributions for the individual loads of each consumer. These models of the aggregate load behavior are then used in a simulation model that includes the generation and storage components of the system to perform Monte Carlo simulation studies. The paper describes the design of components in a Simulink model of the microgrid system. It then presents the results of a case study for a typical application, a microgrid in rural East Africa. The case study demonstrates how smart meters able to control residential demand make it possible to reduce the occurrence and duration of power cuts when the total system demand exceeds the total available power from generators. The average amount of power from renewable vs. non-renewable sources is also computed. The concluding section identifies several directions for future research.