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Solving the thin-wire electric field integral equation (EFIE) by the multiresolution wavelet expansion method involves a time-consuming double numerical integration for each nonzero element of the moment matrix which in turn can outweigh the advantages of achieving a sparse matrix. To speed up the matrix fill process in wavelet-based moment method codes, first, the triangular scaling functions of a nonorthogonal piecewise liner wavelet at the finest spatial resolution are appropriately replaced by sinusoidal dipoles for which mutual impedances are available in closed-form analytical expressions. The fast wavelet bases transform is then exploited to effectively transfer the resultant matrix equation to multiresolution wavelet domain. Numerical results obtained by the compactly supported semi-orthogonal linear B-spline wavelet demonstrate dramatic reduction of the overall solution time without any degradation in the accuracy of the final solution. Index Terms--Fast wavelet transform, moment matrix sparsification, sinusoidal dipoles, thin-wire EFIE, wavelet expansion method.

This paper presents a battery-integrated multi-input step-up DC-DC converter (BI-MISUC) as a unified interface for multiple energy sources in the frame of a sustainable hybrid energy supply. The proposed converter comprises one bidirectional port for a battery and several unidirectional input power ports. Battery can be charged by input sources, discharged into load or bypassed while charging/discharging durations are independent of switching duty ratios for input sources. In the presented BIMISUC, higher voltage gains with lower duty ratios are achieved not only by increasing the number of inputs but also using the switched inductor (SI) modules. It therefore enables BI-MISUC to be used for a wide range of applications from low to high voltage/power. Furthermore, input sources can be operated individually or simultaneously to supply load energy at the desired output voltage. The converter operation is described for three scenarios (i.e. no battery, battery charging and discharging). A linear quadratic regulator (LQR) control is also used to regulate the output voltage and output power of input sources at the desired references for different scenarios. Finally, the performance of the BI-MISUC is validated by simulations and experimental results. [ABSTRACT FROM AUTHOR]

This paper presents an efficient two-stage classifier based on artificial neural network (ANN) concept to discriminate different types of three-phase unbalanced voltage sags at the location of power quality monitoring. In the first stage, the general type of unbalanced voltage sag (C and D) in terms of number of phases undergoing voltage drop is detected. In the next stage, the symmetrical phase is identified. Different classification approaches such as six-phase (SP), symmetrical components (SC) and three-phase three-angle (TPTA) algorithms have been previously developed to characterize and discriminate six types of unbalanced voltage sags, but they are not fully reliable because of possible incorrect results reported. The proposed classifier is widely tested and compared with three aforementioned algorithms to validate its reliability and efficiency. It is concluded that the learning intelligence of the proposed classifier is its strong point to be superior to those classifiers exclusively employing mathematical operations. [ABSTRACT FROM AUTHOR]