An IoT Platform-based Multi-objective Energy Management System for Residential Microgrids

An IoT Platform-based multi-objective energy management system of smart appliance scheduling by considering the energy cost and residents living quality for renewable energy resources integrated residential microgrids is proposed in this paper. A simplified thermal energy model for a residential house is developed to estimate the indoor temperature. The support vector machine method is used to predict solar/wind energy generation and outdoor temperature with limited historical data. Furthermore, a particle swarm optimization-based multi-objective rolling optimization process is presented to balance the energy cost and indoor temperature to maintain the indoor temperature within the comfort level with the lowest energy cost. The simulation and experimental results verify the effectiveness of the proposed approach.