Demand Side Management (DSM) proposes a novel paradigm that generates energy savings on the demand side and views energy usage optimization as an alternative supply source. DR is a type of DSM that refers to market participation behavior in which consumers take the initiative to change their initial energy consumption habits in response to market pricing signals/incentives. However, most research works show that the consumers' satisfaction has not been focused on by researchers. In this thesis, the NILM based User-Centric DSR is proposed. The suggested NILM technique based on edge detection is utilized for the automatic determination of physical characteristics of power-intensive home appliances from users' life patterns. Then, ENN is applied in this study to predict the next day switching events status as well as total power consumption for the next day. Moreover, Q- learning is used to minimize the energy consumption cost while considering users' comfort satisfaction.