Abstract

To ensure the balance between power generation and demand at the peak hours, power utilities need to keep additional power generation capacity on standby which usually causes higher operational cost. This will result in variations in hourly to seasonal electricity prices. With a focus on the physical layer integration, we developed a methodology which includes a prototype of a cluster of smart homes with energy management systems (SHEMS) to study and harvest the flexibility in the demand side in the residential building sector by monitoring and controlling the loads at appliances level. For this goal, we developed and fabricated the electronic circuit of five custom-designed smart plugs (DC, MQTT based) and integrated a vendor-based smart plug (AC) to the system. The devices were equally allocated to three home hubs. As opposed to a standalone SHEMS, this methodology is applied at a cluster scale: through awareness of the electricity consumption of all houses, under certain assumptions optimized load patterns can be generated not only to decrease consumers’ electricity bills, but also to meet the grid’s constraints. We crafted 3 scenarios as showcases of the methodology performance, with two electricity price plans and different load configurations. The results show both smart plug types were successful in measuring the loads and communication with other layers resulting in decreased electricity cost. Additionally, using a hybrid cloud-fog based architecture, a function was designed for saving the smart plugs records during cloud service or internet disconnection to enable later synchronization of the local and cloud database.