Randomized pricing for the optimal coordination of opportunistic agents

In this work, we study the design of pricing mechanisms for the efficient and stable service of a large consumer base with deferrable demands, as envisioned in future smart electricity and data networks. When users with flexible demand are introduced into such large-scale dynamic markets with dynamic prices, they exhibit opportunistic behavior to minimize their cost per unit amount of service-received. This, in turn, generates highly fluctuating aggregate demand patterns that are destabilizing or costly to serve. To avoid this undesired outcome, we propose a randomized pricing mechanism that preserves the strengths of dynamic pricing in tracking a targeted aggregate demand while preventing the destabilizing effect of opportunistic users. Price randomization creates information asymmetry among consumers, but preserves fairness and also the economic benefits of the consumers. We show that the randomization operation can be captured by augmenting a related utility function to the cost minimization problem. This interesting connection enables the study of the steady-state behavior of our randomized pricing solution through the study of the associated optimization problem. Based on this connection, we investigate key metrics of supplier cost and profit and consumer payments.