A New Current Fingerprinting Sensing Method for Adaptive Protection of PV-Integrated Distribution Networks.

Abstract

Grid-following photovoltaic (PV) inverters inject fault currents whose magnitude and phase are set by the control mode active during the disturbance, so directional overcurrent relay (DOCR) settings coordinated for one inverter response can miscoordinate after a mode change. This paper proposes a communication-free adaptive protection scheme built on local sensing. A voltage-adaptive current fingerprinting classifier uses local positive sequence measurements to detect current-limiting (CL), active current priority (ACP) and reactive current priority (RCP) operation, as well as momentary cessation (MC) and asymmetrical faults. The classifier activates the relay setting group prepared offline for the detected mode. With pickup currents fixed, the coordination sub-problem is shown to be a linear program (LP), so every setting group is computed at its exact global optimum. Where the grid code droop law makes ACP and RCP indistinguishable by angle, the classifier declares the ambiguity and activates a group that is feasible for both. Under a class-0.5 instrument transformer noise model, the group placed in service is coordination-valid in 99.8% of cases and the expected residual miscoordination is 3.0×10-5 s, 0.01% of the 0.30 s margin. On the CIGRE medium-voltage benchmark, the scheme satisfies the margin in all operating modes for three-phase, line-to-line (LL) and single-line-to-ground (SLG) faults. The same fault types are then verified at three fault locations on a practical Egyptian 11 kV feeder model, where the sensing layer is confirmed on an electromagnetic transient (EMT) model and the scheme removes the violations of single-setting coordination using an estimated 4 kB of relay memory.