Identification methods of SV distortion of smart substation relay protection

The identification methods of sample value (SV) distortion are proposed in this paper to avoid protection mal-operation in smart substations. The methods contain abnormity identification using data from same sources, using relevant data, and according to data features. The same source data include the double A/D data of one merging unit (MU), doubled communication networks of one protection, and doubled independence protection system. The relevant data include current data from a same branch, voltage data from a same node, and current differential data from a close district. Data feature identification will set algorithms which can distinguish abnormal SV points whose characteristics are different with normal data. Finally, theory analysis and simulation results demonstrate that the above methods can identify SV distortion exactly so that solving measures can be carried out timely. Thus the reliability of protection system will be enhanced dramatically in smart substation.