Adaptive Event-Triggered Strategy for Economic Dispatch in Uncertain Communication Networks

This article investigates the economic dispatch problem in a smart grid with the event-triggered framework under uncertain communication networks. Unlike most of the existing works on economic dispatch, where the distributed consensus-based algorithms are conducted continuously or periodically, the event-triggered mechanism is employed for saving communication resources. For uncertainties, whose upper bounds may be even more significant than nominal weights, we design a general framework for the distributed event-triggered algorithm and an adaptive law for adjusting the coupling weights. The upper bounds of the communication uncertainties are not required in the design, and the adaptive tuning of coupling weights is proved to be able to compensate for the adverse effects caused by uncertainties in the consensus-seeking phase. Noteworthy, the design of event-triggered parameters is independent of the communication topology, which makes the proposed algorithm fully distributed. We also prove that the Zeno triggering of the event-triggered algorithms does not exist. Finally, a case study with the communication network represented by the random multiradius geographical graph is conducted to verify the effectiveness of the derived algorithms.