Dynamic Electric Dispatch for Wind Power Plants: A New Automatic Controller System Using Evolutionary Algorithms

In this paper, we use an evolutionary swarm intelligence approach to build automatic electric dispatch controller for offshore wind power plant (WPP). The optimal flow (OPF) problem WPP is solved by the Canonical Differential Evolutionary Particle Swarm Optimization algorithm (C-DEEPSO). C-DEEPSO works as a control system reactive sources in energy production. operation takes place daily dispatch, scheduled into 15 min intervals and resulting 96 operating test scenarios. As nature of optimization dynamic, fine-tuning initialization parameters performed at each interval. Therefore, version has been built automatically learn best set scenario. For this, have coupled with irace tool (an extension iterated F-race (I/F-Race)) using inferential statistic techniques. experiments carried out showed that methodology employed here robust able tackle OPF-like modeling. Moreover, dynamic schedule operation.