Optimal incentive-based demand response management of smart households

Nowadays, the emerging smart grid technology opens up the possibility of two-way communication between customers and energy utilities. Demand response (DR) management offers the promise of saving money for commercial customers and households while helps utilities operate more efficiently. In this paper, an incentive-based DR optimization (IDRO) model is proposed to efficiently schedule household appliances for minimum usage during peak hours. Proposed method is a multi-objective optimization technique combined with Regression Analysis (RA) which is flexible and scalable. In exchange for a discount on electricity prices while minimizing the customer's welfare, the proposed IDRO algorithm coordinates all the monitored and enrolled household appliances for a better use of electricity energy. It is a cost-effective method where a data acquisition device with only one single minimal set of voltage and current sensors is required. Proposed method is tested and verified using 300 case studies (household). Data analysis for a period of one year shows up to %15 power factor improvement, up to %15 cost saving and 5 Kw/h usage reduction during peak hours for individual households.