A Service Provider Model for Demand Response Management

A demand response management model that is characterized by the use of a service provider as the middleman between the customers and their respective utility is presented. The task of the service provider is to continually find an optimum solution where energy consumption is favorable to the utility and customer. The service provider solves for an optimal solution based on two objectives, a better demand curve for the utility to meet and satisfaction of the customer with some degree of acceptable comfort level while maximizing the monetary savings for both parties. This solution involves a two-stage two-algorithm ( TSTA) based method. The first stage of the algorithm involves using discrete particle swarm optimization to find a reasonable intermediate solution via global search. The second stage involves using a shift-left-shift-right time scheduling algorithm to drive the first stage solution to a near optimum solution, via local search. Customer satisfaction and the utility expected demand are mathematically modeled with the service provider earning a percentage of the savings of both utility and customer. TSTA simulation studies were based on data from the Real-Time Power and Intelligent Systems Laboratory's smart neighborhood research platform. The potential of customer participation in demand response was also categorized based on their profiles.