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Power switches and electrolytic capacitors are the most vulnerable components in the power electronic converters. Any failure in these components may result in severe damages, if no remedial action is employed. Prior to any remedy, the first step is fault diagnosis. In this paper, a new type of Rogowski coil sensor is proposed. The sensor captures the inductor current derivative, which contains suitable signatures for switch fault diagnosis and capacitor lifetime monitoring in nonisolated single-switch dc–dc converters. Using the captured signal, detection of switch open-circuit and short-circuit faults is realized by a simple logic circuit. Furthermore, a new capacitor lifetime monitoring technique is proposed, which employs this signal for calculating equivalent series resistance of the capacitor. The proposed sensor has some remarkable advantages. Due to its nonmagnetic core, the problem related to nonlinear response of magnetic cores at high frequencies will not be encountered. Furthermore, the proposed cost-efficient approach can be easily implemented even for already fabricated converters. The performance of the proposed sensor is evaluated using some finite-element simulations and experiments for a buck converter. The results confirm the capabilities of the sensor for switch fault diagnosis and capacitor lifetime monitoring in nonisolated single-switch dc–dc converters. [ABSTRACT FROM PUBLISHER]

Electric train system is a very large load for the power network. This load consumes a large amount of reactive power. In addition, it causes a massive unbalance to the network, which results in many problems such as voltage drops, high transmission losses, reduction in the transformer output ability, negative sequence current, mal-operation of protective relays, etc. In this paper, a novel real-time optimization approach is presented to adjust the static VAR compensator (SVC) for the traction system to realize two objectives; current unbalance reduction and reactive power compensation. A multi-objective optimization technique entitled non-dominated sorting genetic algorithm (NSGA-II) is used to fulfill the regarded objectives simultaneously. A comprehensive simulator has been designed for electric train network modeling that is able to adjust the parameters of SVC in an optimum manner at any time and under any circumstances. The results illustrate that the provided method can efficiently reduce the unbalancing in current as well as supply the demanded reactive power with acceptable precision. [ABSTRACT FROM AUTHOR]