Customer modeling and pricing-mechanisms for demand response in smart electric distribution grids

We describe and contrast different market mechanisms to incentivize residential electricity customers to perform demand response (DR) via load shifting of schedulable assets. A customer-incentive pricing (CIP) mechanism from our past research is discussed, and compared to flat-rate, time-of-use (TOU), and real-time pricing (RTP). The comparison is made using a for-profit aggregator-based residential DR approach to solve the ``Smart Grid resource allocation'' (SGRA) problem. The aggregator uses a heuristic framework to schedule customer assets and to determine the customer-incentive price to maximize profit. Different customer response models are proposed to emulate customer behavior in the aggregator DR program. A large-scale system consisting of 5,555 residential customer households and 56,588 schedulable assets using real pricing data over a period of 24 h is simulated and controlled using the aggregator. We show that the aggregator enacts a beneficial change on the load profile of the overall power system by reducing peak demand. Additionally, the customers who are more flexible with their loads, represented as a parameter in the proposed customer a-model, have a greater reduction on their electricity bill.(1)