Smart Home Energy Management Supported by Cloud Computing

The current work studies optimal management of electrical appliances in smart homes. An appliance scheduling problem is addressed via optimisation approaches with the goal of minimising the overall energy bill over a week. Scheduling of electrical appliances must take into account non-controllable domestic demand, grid prices and local energy production by photovoltaic panels. Here, a preliminary cloud architecture is proposed to support smart home sensor data collection, storage, processing and scheduling computation. Optimal schedules achieve a balance between local energy production and grid prices, exploring periods of higher generation to attenuate non-controllable demands and favouring night periods (during which energy is cheaper) for controllable appliances operations.