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 α-model, have a greater reduction on their electricity bill.1

Chapter Contents:

• Abstract
• 6.1 Customer modeling introduction
• 6.2 Aggregator-based residential demand response
• 6.2.1 CPSS
• 6.2.2 Aggregator
• 6.2.3 Aggregator demand response
• 6.2.4 Aggregator profit function
• 6.3 Customer models
• 6.3.1 Customer overview: Gamma parameter
• 6.3.2 Alpha model
• 6.3.2.1 Alpha model overview
• 6.3.2.2 Coefficient-of-variation-based method
• 6.3.3 Customer loads
• 6.4 Pricing mechanisms
• 6.5 Heuristic framework
• 6.5.1 Problem formulation
• 6.5.2 Genetic algorithm implementation
• 6.6 Simulation study
• 6.6.1 Simulation setup
• 6.6.2 Results
• 6.7 Conclusions
• References

Inspec keywords: power markets; pricing; power distribution economics; smart power grids

Other keywords: large-scale system; pricing-mechanisms; customer modeling; demand response; SGRA; smart electric distribution grids; smart grid resource allocation

Subjects: Power system management, operation and economics; Distribution networks