Current phase comparison pilot scheme for distributed generation networks protection

The trends of the actual distribution networks are moving toward a high penetration of distributed generation and power electronics converters. These technologies modify contribution-to-fault current magnitudes and raise concern about new protection parameters settings to accurately detect faults on distribution networks. This paper proposes a differential phase jump pilot scheme to detect faulted branches in distribution networks. The aim of the proposed scheme is to provide an efficient algorithm with functions of fault detection and isolation, which are part of the self-healing functions used for smart grids. The proposed scheme is based on the current phase jump measured in each node with fault inception. Then, by comparing the phase jump obtained with the prefault conditions and rate changes, it determines the fault direction enabling a trip signal to the corresponding nodes to isolate the branch under fault. A distribution network has been modeled in PSCAD/EMTDC program to verify the proposed algorithm, taking into account distributed generation provided by both wind turbines (doubly fed induction generator and permanent magnet generator with full converter) and solar photovoltaic installations. The behavior of the current phase jump has been studied for both generation and load nodes. This algorithm is not affected by the magnitude of current and voltage and has been tested varying fault location and resistance along the modeled distribution network.

► An effective zone protection for DG networks is proposed based on current phase jump with fault inception.
► High penetration of DG to distribution networks will represent a source of error for conventional overcurrent and distance protections schemes.
► The proposed algorithm operates independently of short circuit current magnitudes variation due to penetration of DG.
► This algorithm has been tested varying fault location along a DG network modeled with PV solar installation and wind farms.