Incentives and targeting policies for automated demand response contracts

Abstract

Demand Response (DR) programs constitute an efficient way to alleviate the problem of peak demand in smart grids. While the potential impact of DR can be significant, its success essentially depends on the participation and responsiveness of consumers. In this paper, we focus on the design of effective contract-based automated DR programs by energy providers that own supportive generators to meet excess demand and employ DR as a means to avoid their costly activation. We derive a theoretically justified formula for the amount of incentives that should be offered to a consumer to accept such a contract. Based on this, we introduce an algorithm for selecting the optimal set of consumers in terms of total incentives. This algorithm is employed under two different policies for restricting (in a different way) the discomfort caused to consumers. We evaluate these policies using real-world data and present interesting insights about the efficient selection of consumers to be targeted for DR and the total amount of incentives offered to them by the provider.