Distributed Fixed-Time Economic Dispatch under Time-Varying Topology and Uncertain Information

The centralized power generation infrastructure that defines the U.S. electric grid is slowly moving to the distributed architecture due to the explosion in use of renewable generation and distributed energy resources (DERs), such as residential solar, wind turbines and battery storage. Furthermore, variable pricing policies and profusion of flexible loads entail frequent and severe changes in power outputs required from each generation unit. In view of the above challenges, a fixed-time convergent, fully distributed economic dispatch algorithm for scheduling optimal power generation among a set of DERs is proposed. The proposed algorithm addresses both load balance, as well as generation capacity constraints. The algorithm subsumes and betters the existing economic dispatch algorithms on three fronts: (a) It is shown that the distributed algorithm converges to optimal dispatch solution in a fixed-time, regardless of the initial states of every generation unit. Additionally, the time of convergence can be user-prespecified. (b) Regardless of the physical topology of the power network, the proposed framework allows for time-varying communication topology. (c) Finally, we show that our algorithm is robust to uncertain information resulting from noisy communication with neighbors. Several case studies are presented that corroborate computational and robustness aspects of the proposed distributed economic dispatch algorithm.