Foresighted Demand Side Management

We consider a smart grid with an independent system operator (ISO), and distributed aggregators who have energy storage and purchase energy from the ISO to serve its customers. All the entities in the system are foresighted: each aggregator seeks to minimize its own long-term payments for energy purchase and operational costs of energy storage by deciding how much energy to buy from the ISO, and the ISO seeks to minimize the long-term total cost of the system (e.g. energy generation costs and the aggregators' costs) by dispatching the energy production among the generators. The decision making of the entities is complicated for two reasons. First, the information is decentralized: the ISO does not know the aggregators' states (i.e. their energy consumption requests from customers and the amount of energy in their storage), and each aggregator does not know the other aggregators' states or the ISO's state (i.e. the energy generation costs and the status of the transmission lines). Second, the coupling among the aggregators is unknown to them. Specifically, each aggregator's energy purchase affects the price, and hence the payments of the other aggregators. However, none of them knows how its decision influences the price because the price is determined by the ISO based on its state. We propose a design framework in which the ISO provides each aggregator with a conjectured future price, and each aggregator distributively minimizes its own long-term cost based on its conjectured price as well as its local information. The proposed framework can achieve the social optimum despite being decentralized and involving complex coupling among the various entities

Intervention in Power Control Games With Selfish Users

We study the power control problem in wireless ad hoc networks with selfish users. Without incentive schemes, selfish users tend to transmit at their maximum power levels, causing significant interference to each other. In this paper, we study a class of incentive schemes based on intervention to induce selfish users to transmit at desired power levels. An intervention scheme can be implemented by introducing an intervention device that can monitor the power levels of users and then transmit power to cause interference to users. We mainly consider first-order intervention rules based on individual transmit powers. We derive conditions on design parameters and the intervention capability to achieve a desired outcome as a (unique) Nash equilibrium and propose a dynamic adjustment process that the designer can use to guide users and the intervention device to the desired outcome. The effect of using intervention rules based on aggregate receive power is also analyzed. Our results show that with perfect monitoring intervention schemes can be designed to achieve any positive power profile while using interference from the intervention device only as a threat. We also analyze the case of imperfect monitoring and show that a performance loss can occur. Lastly, simulation results are presented to illustrate the performance improvement from using intervention rules and compare the performances of different intervention rules.Comment: 33 pages, 6 figure