Home Energy saving for Heating/cooling system by distributed intelligent energy controller

In this paper we propose an intelligent energy controller algorithm that efficiently manages energy consumption for both heating and cooling spaces. Our approach is based on considering the home's occupancy and sleep patterns as well as outdoor temperature and user's preferences as inputs. The proposed approach has been evaluated by considering the well-known energy home simulation software HOT2000. Therefore our model follows the same house specifications that include the home's dimensions and energy performance characteristics among others. We have calculated how much energy a home modeled will use under emulated conditions. Our findings show that considering human's occupancy patterns could reduce the overall energy consumption up to 50% in an ideal case.