This paper presents simulated hybridized solar-wind generation as an alternative for rural dwellers that do not have access to a conventional grid connection. Solar and wind were used as the main sources of energy with battery storage. Each power source has a DC-DC converter to control the power flow. An axial flux permanent magnet generator, which is suitable for a location with a low wind speed, was driven by the wind turbine. By using this generator, the efficiency of the system increased since certain losses were removed. The perturbation and observation method of MPPT is used to achieve maximum power extraction from the solar panel. The hybrid system was modelled in Matlab/Simulink software. A squirrel cage induction motor was used as the electrical load to the system load. The results obtained for the proposed hybrid system indicates that it can be used as an isolated power supply. By doing so, it improves the standard of living and hence, increasing total number of citizens using energy in the country.

Feature selection improves the classification performance of machine learning models. It also identifies the important features and eliminates those with little significance. Furthermore, feature selection reduces the dimensionality of training and testing data points. This study proposes a feature selection method that uses a multivariate sample similarity measure. The method selects features with significant contributions using a machine-learning model. The multivariate sample similarity measure is evaluated using the University of California, Irvine heart disease dataset and compared with existing feature selection methods. The multivariate sample similarity measure is evaluated with metrics such as minimum subset selected, accuracy, F1-score, and area under the curve (AUC). The results show that the proposed method is able to diagnose chest pain, thallium scan, and major vessels scanned using X-rays with a high capability to distinguish between healthy and heart disease patients with a 99.6% accuracy.

This paper presents a comprehensive mathematical modelling of a DC to DC Buck-Boost converter. The different power losses associated with the Buck-Boost circuit are also presented. Analysis of the converter power loss is graphically represented at varied duty cycles and load resistance values. A low frequency pulse width modulated inverter is interfaced with the Buck-Boost converter using MATLAB/SIMULINK. For an efficient performance and attenuation of low order harmonics, the low frequency pulse width modulated inverter is substituted with a high frequency pulse width modulated voltage source inverter. A comparison is therefore drawn to show the significant change in the percentage harmonic reduction of the two different frequency modulations. All simulation results are achieved using MATLAB 7.14 version. The simulation results however show that Mosfet switching loss decreases with an increase in the duty cycle whereas Diode and Inductor conduction losses increase with an increase in the duty cycle values.Contribution/ Originality: This study contributes in the existing literature by showing that at a reduced duty cycle and varied resistance values of a dc-dc buck boost converter, the Mosfet switching loss is increased whereas the Diode and Inductor conduction losses decrease correspondingly with the decrease in the duty cycle.

Electrical power generated and transmitted at a long distance away from the power stations is usually affected by inherent transmission line losses. The Ohmic and Corona losses which are predominantly common in power transmission lines are considered in this paper. These two losses are mathematically modeled with and without embedded bundled conductors. The resultant model which is a non-linear multivariable unconstrained optimized equation is minimized using the Hessian matrix determinant method for stability test purposes. The results obtained show that corona losses are minimized with embedded bundled conductors at a very low current value with large spacing distance between the bundled conductors. The decrease in the corona loss which is a consequence of spacing adjustment of the 2, 3, and 4 strands of bundled conductors was plotted using MATLAB 7.14. The plots obtained are in conformity with the inverse relation between corona loss and conductor spacing.

Abstract:The matrix converter or pulse width modulated frequency changer, invented in the mid-1980s, is a direct power conversion device that can generate a variable voltage and frequency from a variable input source. Industrially, it is applied in adjustable speed control of induction motor drive, power quality conditioner, and traction applications.The aim of this paper is to evaluate the steady state characteristic behavior of an induction machine in terms of its speed and torque when driven by a three phase indirect matrix converter at reduced harmonics. Similarly, projecting an AC-AC matrix converter that ensures a uniform synchronization in frequency and voltage supplies between the three phase wound rotor machine and the transformer's grid voltage supply is discussed in the Scherbius scheme. The different methods of torque calculations pertaining to some selected machine circuit diagrams are presented for comparison and analysis. Emphasis on the torque-speed characteristics of the machine at varied resistance and slip values were graphically analyzed in MATLAB to determine the degree of torque-speed dependence on the rotor resistance and slip. The overall behavior of the machine under motoring, plugging, and regenerative modes was considered in this work, while a detailed Simulink modeling of an indirect matrix converter on the Scherbius drive scheme is also presented for further analysis.

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<p class="Default">This paper assesses the efficiency level and power loss minimization of a doubly fed induction generator (DFIG). A modified DFIG equivalent circuit with multi-core resistance connected in parallel was adopted. State-space differential equations of the DFIG was developed incorporating iron and copper loss components while a minimum flux linkage that aids in the minimization of the overall losses was derived. Simulation results showed that losses were minimized when the equivalent core resistances were connected in parallel with minimum permissible current flow. The results obtained during a transient disturbance showed that at different core resistance values of Rfe = 0.75Ω and 0.25Ω, different efficiency values of 83.45% and 41.21% were realized. An unconstrained optimization test carried out on the DFIG variable parameters showed that the DFIG power loss model was controllable with a positive definite value of 691.9801 and 2.9156〖e〗^(+5) for the leading principal determinants of the Hessian matrix. All simulation processes were achieved in MATLAB/Simulink 2020.</p>

<span lang="EN-US">Permanent magnet synchronous machines (PMSMs) are gaining popularity due to renewable energy and the electrification of transportation. Permanent magnet synchronous machines are receiving interest because to their great dependability, low maintenance costs, and high-power density. This research compares surface mounted permanent magnet (SMPM) with interior permanent magnet (IPM) synchronous machines using MATLAB. Mathematical models and simulation analyses of two permanent magnet synchronous machines under regenerative braking are presented. Maximum regeneration power point (MRPP) and torque (MRPP-torque) for two machine types were simulated at variable electrical speed and q-axis current. Simulation results showed IPMSM produced more output power due to saliency than SMPM at varying speed and current with higher MRPP and MRPP-Torque. Simulation was used to compare the dynamic impacts of constant and variable braking torques on an auto-electric drive's speed and produced torque on a plain surface and a sloppy driving plane. 81.68% and 74.95% braking efficiency were measured on level ground and a sloppy plane, respectively. Simulations indicated that lithium-ion battery state of charge varied linearly with constant braking torque and exponentially with varying braking torque, reflecting efficiency values. All simulations were in MATLAB/Simulink 2014.</span>