Scheduling Flexible Nonpreemptive Loads in Smart-Grid Networks

A market consisting of a generator with thermal and renewable generation capability, a set of
nonpreemptive
loads (i.e., loads which cannot be interrupted once started), and an independent system operator (ISO) is considered. Loads are characterized by durations, power demand rates, and utility for receiving service, as well as disutility functions giving preferences for time slots in which service is preferred. Given this information, along with the generator’s thermal generation cost function and forecast renewable generation, the social planner solves a mixed-integer program to determine a load activation schedule which maximizes social welfare. Assuming price-taking behavior, we develop a competitive equilibrium concept based on a relaxed version of the social planner’s problem, which includes prices for consumption and incentives for flexibility, and allows for probabilistic allocation of power to loads. Considering each load as representative of a population of identical loads with scaled characteristics, we demonstrate that the relaxed social planner’s problem gives an exact solution to the original mixed integer problem in the large population limit, and give a market mechanism for implementing the competitive equilibrium. Finally, we evaluate via case study the benefit of incorporating load flexibility information into power consumption and generation scheduling in terms of proportion of loads served and overall social welfare.