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In order to improve the dependability and security of transformer differential protection, the energisation conditions should be effectively distinguished from internal fault conditions. In this study, a new method with a low computational burden and high robustness against measurement noises is proposed for discriminating between the transformer inrush current and internal faults. In the proposed method, sine waves are fitted to the sample points of the normalised differential currents for different phases using recursive extended least‐squares (RELS) algorithm in an online manner. The extended kernel enables the algorithm to effectively estimate the dynamics of the measurement noises. Three residual signals which are defined as the differences between the normalised differential currents and the fitted sine wave signals are considered as the decision criteria. Based on the selected criteria, the energisation condition is identified in about a half‐cycle of power system frequency. A large number of simulation and experimental test cases are used to demonstrate the effectiveness of the proposed method. The results show that the proposed algorithm achieves an accuracy of ∼98% and has a relatively low operating time, while the computational burden for the embedded implementation is favorably low. [ABSTRACT FROM AUTHOR]

Supercapacitor is being widely used in electric transportation applications, particularly in electric vehicles (EVs). In the EV, the supercapacitor mainly serves as energy storage system for accelerating the vehicle and/or capturing the braking energy due to its prominent features such as high power density and long life cycle. However, during the vehicle braking and/or accelerating, deep and fast supercapacitor charging‐discharging cycles increase the electric and thermal stresses on the supercapacitor bank. Under such circumstances, condition monitoring of the supercapacitor bank is essential in EVs for safe operation of the storage system. In this paper, an effective method for condition monitoring and fault diagnosis of the supercapacitor banks is proposed. First, it is shown that the equivalent series resistance (ESR) and double‐layer capacitance (CDL) can be used as the key signatures for indicating the state‐of‐health. Subsequently, the recursive extended least‐square algorithm (RELS) is used for online estimation of the ESR and capacitance of the supercapacitor bank. Based on a residual signal which is defined as the difference between the voltages of the supercapacitor bank and RELS algorithm, the abnormal conditions of the supercapacitor bank are distinguished. Experimental results are presented to confirm the feasibility and precision of the proposed method. [ABSTRACT FROM AUTHOR]

This study presents a new resistive capacitor switching transient limiter (RCSTL) for mitigating power capacitor switching transients. The RCSTL is composed of three limiting resistors, a three‐phase full bridge diode rectifier, a thyristor and a three‐phase coupling transformer. The limiting resistors are connected in series with the capacitor bank and the thyristor is installed at the DC side of the diode rectifier. During the capacitor bank energising, the thyristor remains off and hence, the secondary side of the coupling transformer acts as open circuit. Consequently, high impedance including the transformer's magnetic reactance in parallel with the limiting resistors is inserted in series with the capacitor bank. Under such circumstance, the limiting resistors restrain the capacitor switching transients. In the steady‐state, the control system triggers the thyristor and the coupling transformer acts as short circuit. As a result, the limiting resistors are bypassed by the coupling transformer and thus, the RCSTL has no significant effect on the circuit. Analytical analysis is performed to describe different operation modes of the proposed RCSTL. A single stage of a three‐phase wye‐connected capacitor bank with 25 kVAR is energised and the performance of the proposed limiter is investigated. Both the simulation and experimental results confirm the effectiveness of the RCSTL. [ABSTRACT FROM AUTHOR]