Experimental Study and Modeling of Automatic Home Energy Management System Using AI

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This paper proposes an experimental study and modeling of Fuzzy logic based-AI for home energy management system. The management model has been designed for home in the subtropical climate zone-like, i.e., Thailand, which having yearly and monthly average temperature of 28°c and 30–38°c in the hottest season respectively. The studied system model comprises of the grid-connected load of home appliances, air conditioner, type-1 EV charger and solar rooftop PV supply. The objective of energy management is to minimize grid power consuming as well as maximizing solar PV utilization with 24-hour load profile, principally running of air conditioner and EV charging load. By testing the proposed management system comparatively to the generic system without managing scheme, energy saving of 43.90% can be achieved under the same operating and environmental conditions. Those are illustrated by the simulation results.

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