A Bi-level Decision Support System for Home Energy Management in Smart Homes

Effective home energy management requires addressing user preferences and the operational needs of household appliances with minimal human intervention. This paper presents a dedicated decision support system (DSS) for managing time-shiftable and controllable appliances. The system minimises energy costs and thermal discomfort by optimising the operation of appliances like washing machines (WM), dishwashers (DW) and air conditioners (AC). The complexity of managing appliances at different times is tackled using a bi-level DSS, incorporating particle swarm optimisation (PSO). In level 1, WM and DW's operation time is shifted to minimise the operating cost. In level 2, the AC power is adjusted in real-time to minimise both the cost paid to the upstream network and the thermal discomfort of the users. The proposed method is tested on a smart home dataset and observes an energy saving of 22.29kW h and bill saving of 287.65cents compared to uncontrolled operation and also maintains the room temperature variations within <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\pm 2^{\mathrm{o}}C$</tex> from the user choice.