Distributed demand side management among foresighted decision makers in power networks

We consider a power network with an independent system operator (ISO), and geographically 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 minimizes 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 minimizes the long-term total cost of the network (i.e. energy generation costs and aggregators´ costs) by dispatching energy generation among the generators. The decision making of the foresighted entities is complicated because 1) the information required to make optimal decisions is decentralized among the entities, and 2) the coupling (through the prices) among the aggregators is complicated. 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 the decentralized information and complex coupling among the entities. Simulation results demonstrate significant reduction in the total cost by the proposed foresighted demand side management (DSM), compared to the optimal myopic DSM (up to 60% reduction), and the foresighted DSM based on the Lyapunov optimization framework (up to 30% reduction).