Optimal Hierarchical Power Scheduling for Cooperative Microgrids

As advances are made in single Microgrid (MG) systems, the problem of cooperation among MGs and the Macrogrid has attracted considerable interest only recently. As in wireless communications systems, exploiting the temporal, spatial, and technological diversities in multiple cooperative MGs could bring about more efficient power generation and distribution. This paper investigates a hierarchical power scheduling approach to optimally manage the power trading, storage and distribution in a smart power grid with a Macrogrid and cooperative MGs. We first present a two-tier formulation: the first-tier problem jointly considers user utility, transmission cost, and grid load variance, while the second-tier problem minimizes the power generation and transmission cost and exploits distributed storage in the MGs. We develop an effective online algorithm to solve the first-tier problem and prove its asymptotic optimality, and develop a distributed optimal algorithm for solving the second-tier problem. The proposed hierarchical power scheduling algorithms are evaluated with trace-driven simulations and are shown to outperform several existing schemes with considerable gains.