  Nowadays the emerging smart grid technology opens up the possibility of
two-way communication between customers and energy utilities. Demand Response
Management (DRM) offers the promise of saving money for commercial customers
and households while helps utilities operate more efficiently. In this paper,
an Incentive-based Demand Response Optimization (IDRO) model is proposed to
efficiently schedule household appliances for minimum usage during peak hours.
The proposed method is a multi-objective optimization technique based on
Nonlinear Auto-Regressive Neural Network (NAR-NN) which considers energy
provided by the utility and rooftop installed photovoltaic (PV) system. The
proposed method is tested and verified using 300 case studies (household). Data
analysis for a period of one year shows a noticeable improvement in power
factor and customers bill.
