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The concept of the magnetic amplifier, a common electromagnetic device in electronic applications in the past, has seldom been used in power systems. The magnetic amplifier-based power-flow controller (MAPFC), an innovative low-cost device that adopts the idea of the magnetic amplifier for power-flow control applications, is introduced in this paper. The uniqueness of MAPFC is in the use of the magnetization of the ferromagnetic core, shared by an ac and a dc winding, as the medium to control the ac winding reactance inserted in series with the transmission line to be controlled. Large power flow in the line can be regulated by the small dc input to the dc winding. A project on the R&D of an MAPFC has been funded by the U.S. Department of Energy (DOE) and conducted by the Oak Ridge National Laboratory (ORNL), the University of Tennessee-Knoxville, and Waukesha Electric Systems, Inc. since early 2012. Findings from the project are presented along with some results obtained in a laboratory environment. [ABSTRACT FROM AUTHOR]

This paper presents a summary of the available single-phase ac–dc topologies used for EV/PHEV, level-1 and -2 on-board charging and for providing reactive power support to the utility grid. It presents the design motives of single-phase on-board chargers in detail and makes a classification of the chargers based on their future vehicle-to-grid usage. The pros and cons of each different ac–dc topology are discussed to shed light on their suitability for reactive power support. This paper also presents and analyzes the differences between charging-only operation and capacitive reactive power operation that results in increased demand from the dc-link capacitor (more charge/discharge cycles and increased second harmonic ripple current). Moreover, battery state of charge is spared from losses during reactive power operation, but converter output power must be limited below its rated power rating to have the same stress on the dc-link capacitor. [ABSTRACT FROM AUTHOR]

A new approach for modulation of an 11-level cascade multilevel inverter using selective harmonic elimination is presented in this paper. The dc sources feeding the multilevel inverter are considered to be varying in time, and the switching angles are adapted to the dc source variation. This method uses genetic algorithms to obtain switching angles offline for different dc source values. Then, artificial neural networks are used to determine the switching angles that correspond to the real-time values of the dc sources for each phase. This implies that each one of the dc sources of this topology can have different values at any time, but the output fundamental voltage will stay constant and the harmonic content will still meet the specifications. The modulating switching angles are updated at each cycle of the output fundamental voltage. This paper gives details on the method in addition to simulation and experimental results. [ABSTRACT FROM PUBLISHER]

This work approximates the selective harmonic elimination problem using artificial neural networks (ANNs) to generate the switching angles in an 11-level full-bridge cascade inverter powered by five varying dc input sources. Each of the five full bridges of the cascade inverter was connected to a separate 195-W solar panel. The angles were chosen such that the fundamental was kept constant and the low-order harmonics were minimized or eliminated. A nondeterministic method is used to solve the system for the angles and to obtain the data set for the ANN training. The method also provides a set of acceptable solutions in the space where solutions do not exist by analytical methods. The trained ANN is a suitable tool that brings a small generalization effect on the angles' precision and is able to perform in real time (50-/60-Hz time window). [ABSTRACT FROM AUTHOR]