Demand response through smart home energy management using thermal inertia

In this paper, the value of thermal inertia in demand response to benefit customers is determined through a Mixed Integer Linear Programming (MILP) algorithm. Thermal models with different sophistications for a smart house are investigated. The energy consumption for cooling a smart house is optimized to minimize the expenditure of cooling load. One parameter and two-parameter thermal models are integrated into the optimization. The optimization of thermal load for maintaining the smart house within thermal comfort level is formulated as a MILP algorithm under the dynamic pricing policy. It is observed that the utilization of thermal inertia could potentially benefit both smart house owners and grid operators in the context of smart grid.