Abstract: |
This paper proposes a pattern recognition based differential spectral energy protection scheme for ac microgrids
using a Fourier kernel based fast sparse time-frequency representation (SST or simply the sparse S-Transform). The
average and differential current components are passed through a change detection filter, which senses the instant
of fault inception and registers a change detection point (CDP). Subsequently, if CDP is registered for one or more
phases, then half cycle data samples of the average and differential currents on either side of the CDP are passed
through the proposed SST technique, which generates their respective spectral energies and a simple comparison
between them detects the occurrence and type of the fault. The SST technique is also used to provide voltage and
current phasors and the frequency during faults which is further utilized to estimate the fault location. The proposed
technique as compared to conventional differential current protection scheme is quicker in fault detection and
classification, which is least effected from bias setting, has a faster relay trip response (less than one cycle from fault
incipient) and a better accuracy in fault location. The significance and accuracy of the proposed scheme have been
verified extensively for faults in a standard microgrid system, subjected to a large number of operating conditions and
the outputs vindicate it to be a potential candidate for real time applications. |
Key words: Microgrid, Differential spectral energy protection, Time-frequency representation, Fault classification, Faultlocation |
DOI:10.1186/s41601-017-0062-0 |
|
Fund: |
|