Simulation of Household Appliances with Energy Disaggrigation using Deep Learning Technique

Energy disaggregation is one of the major concerns in the modern power management in domestic utilities. Main aim is to read the individual load appliance readings from the whole data. There are so many techniques to the field, deep learning being promising. This paper state about simulation of household appliances for data aggregation and energy disaggregation of individual appliances using deep learning technique. For data collection we have used data of individual standalone house for summer season. Deep learning technique such as complex tree and linear modules are studied in this paper with the incorporation of complex technique for better efficiency. The performance efficiency of both the modules are tested and evaluated in this paper. To make it cost-effective the system is simulated in MATLAB/SIMULINK for the different trial cases.