Adaptive Dynamic Event-triggered Algorithm for Economic Dispatch Problem with Discrete Communication and Control

This article investigates the distributed economic dispatch problem of smart grid under discrete communication and algorithm updates. By introducing virtual adaptive gains and time-varying threshold dynamics, a novel adaptive dynamic event-triggered distributed optimization algorithm is proposed for balancing supply and demand at a minimum of economic cost. Compared with existing algorithms, the prominent advantage of this algorithm is that both communication among generations and algorithm updates are only at event-triggered instances, saving communication resources and control efforts. Strict proof shows that the proposed algorithm copes with distributed economic dispatch problem, and Zeno behavior can be excluded. At last, its effectiveness is validated by a simulation example.