Novel protection approach for renewable energy-based direct current (DC) distribution systems using unscented-transform (UT)-based Unscented Kalman filter (UKF)

Renewable energy-based DC distribution systems (REBDCDS) are more potential solutions to cutting-edge power and clean energy issues. However, the distinctive characteristics of REBDCDS necessitate specialized protection schemes to ensure safe and reliable operation. This paper proposed a novel protection method using an UT-based UKF on identifying, categorizing, and localizing different types of DC-faults in REBDCDS. In the first step, the UKF residuals (UKFR) are generated by subtracting the locally estimated current signal from the measured current signal. Next, the deviation in the UKFR is compared to a predetermined threshold level to detect the fault occurrence. In the second step, the aggregated covariance-based prediction energy (ACBPE) is calculated from the estimated current signature supplied by UKF. Ultimately, the polarity characteristics in the ACBPE are used to classify and localize the fault events and associated DC lines in the REBDCDS. The usefulness of the suggested scheme is proven through plenty of MATLAB®/Simulink simulations on REBDCDS test beds with radial looped and meshed topological structures. The results illustrated that the suggested scheme is highly robust with 99.95% accuracy. Furthermore, the proposed scheme identifies, categorizes, and localizes all kinds of DC faults in less than 2 ms without any maloperation.