ABSTRACT:In this work, distribution system load flow analysis is formulated and tested for fundamental steady-state and harmonics power flow. For the steady-state analysis, a novel power flow formulation method for the general multiphase balanced and/or unbalanced radial distribution systems is presented. The special topology of the power distribution system has been fully exploited to facilitate obtaining a direct solution using the graph theory. Only one developed matrix used in conjunction with simple standard formulation is enough to obtain the power flow solution. This matrix is the branch-path incident matrix. A feature of using this method is that it significantly reduces the number of power flow equations, as compared to conventional methods, hence very low computation time and memory storage. The presence of nonlinear loads in the power system causes the circulation of harmonics currents in the system, leading to harmonics voltage drops. The harmonics flow analysis in this paper, uses the network techniques in conjunction with graph theory resulting in a powerful algorithm for nonlinear load flow analysis. Six pulse converters model were used to represent the nonlinear load. Two MATLAB programs have been built and used to solve for the load flow solution of standard test systems in both steady-state and harmonics cases. The results of the distribution system cases studies are presented and shows a very good resemblance with a standard results.

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Proportional integral derivative (PID) control is the most commonly used  control algorithm in the industry today. PID controller popularity can be attributed to the  controller’s effectiveness in a wide range of operation conditions, its functional simplicity, and the ease with which engineers can implement it using current computer technology . In this paper,the Dc servomotor model is chosen according to his good electrical and mechanical performances more than other Dc motor models , discuss the novel method for  tuning PID controller and comparison with Ziegler - Nichols method from through parameters of transient response of any system which uses PID compensator

Context The computerization of both fetal heart rate (FHR) and intelligent classification modeling of the cardiotocograph (CTG) is one of the approaches that are utilized in assisting obstetricians in conducting initial interpretation based on (CTG) analysis. CTG tracing interpretation is crucial for the monitoring of the fetal status during weeks into the pregnancy and childbirth. Most contemporary studies rely on computer-assisted fetal heart rate (FHR) feature extraction and CTG categorization to determine the best precise diagnosis for tracking fetal health during pregnancy. Furthermore, through the utilization of a computer-assisted fetal monitoring system, the FHR patterns can be precisely detected and categorized. Objective The goal of this project is to create a reliable feature extraction algorithm for the FHR as well as a systematic and viable classifier for the CTG through the utilization of the MATLAB platform, all the while adhering to the recognized Royal College of Obstetricians and Gynecologists (RCOG) recommendations. Method The compiled CTG data from spiky artifacts were cleaned by a specifically created application and compensated for missing data using the guidelines provided by RCOG and the MATLAB toolbox after the implemented data has been processed and the FHR fundamental features have been extracted, for example, the baseline, acceleration, deceleration, and baseline variability. This is followed by the classification phase based on the MATLAB environment. Next, using the guideline provided by the RCOG, the signals patterns of CTG were classified into three categories specifically as normal, abnormal (suspicious), or pathological. Furthermore, to ensure the effectiveness of the created computerized procedure and confirm the robustness of the method, the visual interpretation performed by five obstetricians is compared with the results utilizing the computerized version for the 150 CTG signals. Results The attained CTG signal categorization results revealed that there is variability, particularly a trivial dissimilarity of approximately (+/−4 and 6) beats per minute (b.p.m.). It was demonstrated that obstetricians’ observations coincide with algorithms based on deceleration type and number, except for acceleration values that differ by up to (+/−4). Discussion The results obtained based on CTG interpretation showed that the utilization of the computerized approach employed in infirmaries and home care services for pregnant women is indeed suitable. Conclusions The classification based on CTG that was used for the interpretation of the FHR attribute as discussed in this study is based on the RCOG guidelines. The system is evaluated and validated by experts based on their expert opinions and was compared with the CTG feature extraction and classification algorithms developed using MATLAB.

In variable speed drive (VSD), it is desirable to reduce the harmonic effects, which causes current distortion and torque pulsation, besides, the harmonic power losses is an additional power losses that is introduced in the motor due to the presence of harmonic voltages. However, the problem of the high total harmonic current distortion (THD) still exists specially at low and medium speeds by using sub-optimal pulse width modulation (PWM) strategy. In the past to generate optimized PWM, is done by defining a general PWM in terms of a set of switching angles. Which result in a set of nonlinear equations in terms of the unknown switching angles. These equations are nonlinear as well as transcendental in nature. There is no efficient method that can be applied to solve such equations. The practical method of solving these equations is a trial and error process. Taking all the factors into account, a numerical technique can be applied to solve these set of nonlinear equations, but with some limitations.  To overcome these limitations, Genetic algorithms (GAs) serves to search for optimal switching angles setting. In addition, the (THD) will be reduced, this lead to obtain the optimal PWM waveform and to simplify the practical implementation, and then improving the performance of the system output.  GAs were employed as a search and optimization engine. Normally the tuning of the switching angles is a trail and error problem. In this paper, GAs provides a much simpler approach to off-line tuning of PWM switching angles than the rather complicated non-genetic optimization algorithms