Energy and CO2 efficient scheduling of smart appliances in active houses equipped with batteries

In this paper, we present a novel method for scheduling smart appliances and batteries, in order to reduce both the electricity bill and the CO₂ emissions. Mathematically, the scheduling problem is posed as a multi-objective Mixed Integer Linear Programming (MILP), which can be solved by using standard algorithms. A case study is performed to assess the performance of the proposed scheduling framework. Numerical results show that the new formulation can decrease both the CO₂ emissions and the electricity bill. Furthermore, a survey of studies that deal with scheduling of smart appliances is provided. These papers use methods based on MILP, Dynamic Programming (DP), and Minimum Cut Algorithm (MCA) for solving the scheduling problem. We discuss their performance in terms of computation time and optimality versus time discretization and number of appliances.