Model Predictive Control Based Demand Response for Optimization of Residential Energy Consumption

This article describes a method for establishing an appliance scheduling scheme that can optimally coordinate a group of appliances in a consumer's premises. Finite-horizon scheduling optimizations are formulated to schedule the operation of appliances using a modeled predictive control method that incorporates both forecasts and newly updated information. A complex mixed discrete-continuous non-linear model is here in established, and a novel algorithm that hybridizes particle swarm optimization and constraint handing methods is proposed to derive optimum solutions within a limited computational time. Simulation results showed that the proposed algorithm can efficiently resolve real-life instances and can be embedded in resource limited devices.