Pricing for the Optimal Coordination of Opportunistic Agents

We consider a system where a load aggregator (LA) serves a large number of small-sized, economically-driven consumers with deferrable demand, as envisioned in the smart electricity grid and data networks. In these systems, consumers can behave opportunistically by deferring their demand in response to the prices, to obtain economic gains. However, if not controlled properly, such opportunistic behavior can be detrimental to the system by creating aggregate effects that lead to undesirable fluctuations in price and total load. To avoid the unwanted effects of demand-side flexibilities and to reap system-wide benefits from them, we propose two novel real-time dynamic pricing algorithms. The first algorithm communicates individual prices to consumers by adding small random perturbations to a common price. The second algorithm introduces a secondary price that penalizes the change in users' consumption in time. The common feature of both algorithms is creating differentiation among consumers and, thus, regulating the aggregate load. We conduct comprehensive numerical investigations and show that the LA and consumers economically benefit under the proposed pricing schemes.