The use of solid state transformers (SSTs) in microgrids has created a new kind of network called Future Renewable Electric Energy Delivery and Management (FREEDM) microgrid. The FREEDM microgrid provides an appropriate means for enhanced energy management, loss reduction, and network flexibility by reducing the number of converters used for a variety of AC-DC links. In this work, we propose a novel method for fault detection in FREEDM microgrids when considering uncertainties in network topology. The proposed method makes use of the Clarke and S-transforms to characterize the transients in three-phase current and voltage waveforms in the event of a fault. The extracted features of the waveforms will be used to form appropriate indices for detection, location, and characterization of the fault. The main feature of the proposed method is its capability to operate in a dynamic microgrid with varying topology. The performance of the proposed method is investigated by applying it to a sample FREEDM microgrid with ring and radial structures. It is shown that the proposed method is well capable of fault detection and diagnosis while being able to differentiate between short-circuit faults and switching transients due to variations in the network topology.
A Novel Method for Fault Detection in Future Renewable Electric Energy Delivery and Management Microgrids, Considering Uncertainties in Network Topology
Electric power components and systems ; 45 , 10
2017
Aufsatz (Zeitschrift)
Englisch
Electric converters , signal energy , FREEDM microgrid , Clarke components , Converters , Circuits , S-transform , Topology , Fault diagnosis , Waveforms , Energy management , Feature extraction , Switching , Solid state , Fault detection , Distributed generation , Electric power grids , fault detection , Electric utilities , Network topologies , Alternating current , Phase current , Energy use , Phase transformations
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