Residential load control system based analytical optimization method for real residential data consumption

Abstract

Abstract Peak load periods have a great impact for energy demand in smart grid. These times is directly related to the consumption of residential sector, thus utility need to add additional generation capacity during peak time to support the demand required. This paper proposes a demand response system for residential household. Analytical Method (AM) is used to optimize the load consumption based real data of typical residential home. The consumption data are measured using smart plugs that have been designed and implemented to communicate with household’s smart devices. The simulation results show the peak load was reduced by 37.64% and the energy consumption cost bill was reduced by 29.52%. The proposed method is compared with other optimization methods such as Bacterial Foraging Optimization (BFO), and Particle Swarm Optimization (PSO) to highlight the finding. The proposed approach indicated a greater saving period to produce the final results.