A Study on Demand Response Potential of a Residential Area Using Census Data
Demand response (DR) allows consumers to adapt their power usage at peak hours such that it is financially beneficial for them as well as induces lesser stress for the electric grid, paving the way for a greener future with less energy wastage. However, the daily routines of the average electricity consumer might prohibit the active participation in the demand response program. In this work the power profiles of different types of electricity users (more than million users in total) are built using census data and user interview results and a sample demand response program is simulated. To build the profiles, data from different types of customers in different household types and different income states are used. The demand response potential of each of the customer type is then analyzed and identified. A direct control service provider based demand response program is used to simulate the power usage under demand response. Cooperative Particle Swarm Optimization (CPSO) algorithm running on a high performance GPU cluster is employed to calculate the optimum power usage of the million customer profiles generated.