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Demand Response (DR) plays an important role in electricity market design, in both reducing utility’s investment on peak generation and improving electricity bill savings and incentive payments earned by customers. Improved resource-efficiency of electricity production is achieved by closer alignment of electricity pricing information with energy consumption behaviors. In this paper, a block scheduling model of load management for price-based Demand Response is presented under two different real-time pricing schemes: linear pricing scheme and threshold pricing scheme. For linear pricing, the problem is formulated as a convex optimization problem and the optimal demand response profile is given as a two-dimensional water-filling solution either with flat water levels or different water levels for different customers. From the perspectives of the customers as a whole or as selfish individuals, the demand-response computations lead to centralized or distributed optimizations, respectively. A trade-off strategy which attempts to balance these competing objectives is also provided. This trade-off strategy divides customers into local groups within which group-wise distributed optimization is performed to improve the overall performance so that the Price of Anarchy (PoA) is reduced. For threshold pricing, which might be more applicable in certain scenarios, detailed characterization of different optimal load profiles are given assuming a discrete load unit model. A search algorithm is also proposed to find the optimal load profiles for both constant and dynamic pricing threshold scenarios. The effect of dynamic pricing threshold on customers’ electricity consumption behaviors is highlighted.
Li et al. (Sat,) studied this question.