Communication-less adaptive overcurrent relay coordination for service restoration in distribution systems

Abstract

Numerous adaptive protection schemes (APS) have been developed to tackle the issue of changing fault current magnitudes and directions in a reconfigurable network. System-wide communication systems are the primary enablers in these proposed APS. However, these systems require expensive infrastructure and are prone to cyberattacks and communication errors. Therefore, a subclass of studies has proposed decentralized schemes to eliminate the downsides of communicative systems. However, these studies rely on fault parameters to determine the correct relay settings in their proposed APS and applies for a limited number of network topologies only. In contrast, this paper combines the use of local load flow information and the customary fault parameters to realize a comms-less adaptive protection scheme that maintains OCR coordination after service restoration in highly reconfigurable network topologies. Relay settings are selected from setting groups optimized using k-means clustering and linear programming. A locally deployed artificial neural network determines the appropriate setting group by referring to the fault location estimates and load flow measurements. The scheme produced promising results in most overcurrent relay settings selections when demonstrated on the IEEE 33-bus test distribution system under various fault and loading conditions.