Unified optimization of intelligent home appliances with a cost-effective energy management system

The scheduling in smart houses is a pivotal concern in power consumption networks on the demand side owing to the expanding usage of renewable energy resources (RERs). To address the issue of distributed energy management raised due to the expanded use of RERs, a peak-limiting distributed-time-bound strategy is proposed and executed, providing a flexible distribution for the scheduling of appliances under real-time and time-of-use pricing schemes. This paper presents a case study based on the pilot project initiated in Gujarat, India, to better understand the scenario. The current work engenders a smart home energy management system harmonizing with a residential grid. By embracing the proposed methodology, the electricity cost can be curtailed to the bare minimum while concurrently reducing the peak demand, harnessing the maximum potential of renewable energy sources, and optimizing the peak-to-average ratio. Multiple scenarios have been enacted, encompassing various applicable tariff structures, methodologies, and the integration of renewable energy sources. The electricity bill using the proposed strategy is significantly reduced by about 95.25% compared to a random scheduling case (base case) considered in the paper. The maximum peak reduction compared to the random scheduling case is about 70.8 % in one of the presented scenarios.