Recently, the concept of microgrids has emerged in the world due to the integration of distributed energy resources (DERs) at the distribution end. The design of a reliable protection strategy is one of the top-most challenges associated with microgrids. This is because of the transition of microgrids between grid-tied and autonomous modes of operation. This paper presents a state-of-the-art microgrid protection scheme based on the Kalman filter (KF). The proposed scheme uses the one-end current signal of a distribution line for the detection and classification of faults. Firstly, the KF is applied to each phase of a three-phase current signal individually to generate residuals and total harmonic distortion (THDs). Next, the variations in the residuals and THDs of each phase are compared with pre-specified threshold values to detect the faulty events in the microgrid. As each phase is processed through KF individually, therefore, the proposed scheme is inherently phase segregated. Afterward, the KF is applied to extract the third harmonic component from the three-phase current and voltage signals. Then, the KF-based reactive power (KFBRP) is obtained from the extracted third harmonic components. Finally, the directional properties of the threephase KFBRP are used to locate the faulty section in the microgrids. Extensive simulations in MATLAB/ Simulink software are performed for the grid-tied as well as the autonomous modes of operation under radial and meshed topologies. The results show that the proposed scheme is highly robust in all testing scenarios without any false tripping and blinding issues.
One of the challenging issues in the realization of medium-voltage DC (MVDC) distribution system is high-speed protection scheme design against quickly rising short circuit fault-DC current. This paper proposes a high-speed protection scheme based on the processing of energy signals through mathematical morphology (MM). The voltage and current signals measured at a distribution line section (DLS) are used to obtain the energy signal. The proposed scheme develops a modified MM-based filter to extract the transient information in the energy signal rapidly and distinctly in the form of positive/negative polarity. The polarity detection of any disturbance in the analysed energy signal indicates the occurrence of a sudden disturbance in the system. The sudden disturbance occurrence confirmation triggers the faulty DLS identification and classification algorithms of the proposed scheme. The faulty DLS identification and classification algorithms are based on the detected polarities of the energy signal. The protection scheme requires low bandwidth communication. The proposed protection scheme is evaluated by using a ±2.5 kV radial distribution network containing 4 feeders under different fault conditions in MAT-LAB/SIMULINK software. Simulation results verify that the proposed scheme can isolate the faulty portion within a few milliseconds after fault inception under a variety of fault cases.
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