Abstract
The complexity metric is an effective tool to evaluate the behavioral dynamics in systems with high level of nonlinearity and interconnectivity. This paper aims to evaluate the effectiveness of using the entropic complexity as a feature to enhance situational awareness in dynamical systems. In fact, the complexity measurement aims to detect dynamical changes and the pattern recognition tool discerns a particular dynamical change from other types of dynamics. In this study, parameters associated with the permutation entropy and also the complexity are determined in real time. The test system is a small-scale microgrid in which a solid-state transformer (SST) is operating under different dynamical conditions. The complexity measurement unit provides datasets that will be used for detection and identification of particular dynamics in the system that can be potentially used in real-time decision-making. Results show the effectiveness of the proposed approach in detection and recognition of certain dynamics in microgrids.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call