  A market consisting of a generator with thermal and renewable generation
capability, a set of non-preemptive 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.
