Assessment of Capacitor Voltage Transformer Affect On Distance Relay

A capacitor voltage transformer (CVT) comprises a capacitor voltage divider connected to an iron-core voltage transformer. The capacitor voltage transformer is used in the transmission and distribution circuit for stepping down voltages for metering or protection. The performance of the capacitor voltage transformer described in this dissertation is assessed by computer simulation. The simulation tools MATLAB and PSCAD/EMTDC were used. Various types of fault have been made to investigate the transient response of the CVT. It can be seen that as the location of the fault becomes more remote the period of oscillation becomes longer. The results obtained indicate that the CVT transient behaviour is controlled by the sum of the stack capacitances, the shape and parameters of the ferroresonance suppression circuits and the point on wave at which the fault occurs. Experiment results are presented in this dissertation. The objective of the experiment is to investigate the effect on the performance of a distance relay of the CVT transient response. From the results obtained we can see that the CVT transient will slow down the relay for in zone faults. The type of fault applied in this experiment is single phase to ground. x

A High Step-Up Switched Z-Source Converter (HS-SZC) with Minimal Components Count for Enhancing Voltage Gain

Some applications such as fuel cells or photovoltaic panels offer low output voltage, and it is essential to boost this voltage before connecting to the grid through an inverter. The Z-network converter can be used for the DC-DC conversion to enhance the output voltage of renewable energy sources. However, boosting capabilities of traditional Z-network boost converters are limited, and the utilization of higher parts count makes it bulky and expensive. In this paper, an efficient, high step-up, switched Z-source DC-DC boost converter (HS-SZC) is presented, which offers a higher boost factor at a smaller duty ratio and avoids the instability due to the saturation of inductors. In the proposed converter, the higher voltage gain is achieved by using one inductor and switch at the back end of the conventional Z-source DC-DC converter (ZSC). The idea is to utilize the output capacitor for filtering and charging and discharging loops. Moreover, the proposed converter offers a wider range of load capacity, thus minimizing the power losses and enhancing efficiency. This study simplifies the structure of conventional Z-source converters through the deployment of fewer components, and hence making it more cost-effective and highly efficient, compared to other DC-DC boost converters. Furthermore, a comparison based on the boosting capability and number of components is provided, and the performance of the proposed design is analyzed with non-ideal elements. Finally, simulation and experimental studies are carried out to evaluate and validate the performance of the proposed converter

Noninvasive Methods for Condition Monitoring and Electrical Fault Diagnosis of Induction Motors

This chapter provides a comprehensive analysis of noninvasive methods to diagnose stator winding insulation faults of an induction motor. Further, a novel noninvasive method is proposed to diagnose the root cause of winding failure due to unbalanced voltage to avoid catastrophic failure. Therefore, a winding function approach is utilized to derive an analytical expression for stator winding distribution and magnetomotive force (MMF). This tactic qualifies the conductor segment that generates MMF, and it also helps to analyze a healthy current spectrum. One can easily observe higher order harmonics in current spectrum; therefore, a new series of rotor harmonics is introduced to diagnose unbalanced supply. The locus of these harmonics is dependent on the poles, rotor bars, and slip. Due to the rapid complexity in industrial plants, it is inconceivable to continue human inspection to diagnose the faults. Thus, to avoid human inspection, in addition to new series of rotor harmonic, a fully automatic method based on neural network is proposed. This method not only diagnoses unbalanced voltage but it also recognize the percentage of unbalanced voltage by use of feed-forward multilayer perceptron (MLP) trained by back propagation. Finally, the experimental results shows the validation of this research work proposed method

An Intelligent Automated Method to Diagnose and Segregate Induction Motor Faults

In the last few decades, various methods and alternative techniques have been proposed and implemented to diagnose induction motor faults. In an induction motor, bearing faults account the largest percentage of motor failure. Moreover, the existing techniques related to current and instantaneous power analysis are incompatible to diagnose the distributed bearing faults (race roughness), due to the fact that there does not exist any fault characteristics frequency model for these type of faults. In such a condition to diagnose and segregate the severity of fault is a challenging task. Thus, to overcome existing problem an alternative solution based on artificial neural network (ANN) is proposed. The proposed technique is harmonious because it does not oblige any mathematical models and the distributed faults are diagnosed and classified at incipient stage based on the extracted features from Park vector analysis (PVA). Moreover, the experimental results obtained through features of PVA and statistical evaluation of automated method shows the capability of proposed method that it is not only capable enough to diagnose fault but also can segregate bearing distributed defects

Newton-Raphson State Estimation Solution Employing Systematically Constructed Jacobian Matrix

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Impact of Photovoltaic Plant Outputs in Distribution Networks

This paper evaluates the potential of Quaid-e-Azam Solar Park (QASP), Pakistan and examines its impact on distribution networks. To estimate the PV plant yields, solar park’s historical hourly weather data from the years 2000 - 2014 is used. For handling of such huge data, the yearly data is partitioned into four seasons. Further, the seasonal data is modelled by using Beta Probability Density Function (PDF) and a 24 hour solar curve for each season is generated. The solar farm power outputs are tested in IEEE 33 bus distribution network by using time-varying seasonal hourly loads, meanwhile system losses and bus voltages are calculated. The results show that with the passage of time, the impact of solar PV power on reduction of system losses gradually decrease due to yearly degradation of PV module efficiency. System losses at end of PV farm life are 10 - 12% higher than those losses as in the first year. Furthermore, low voltage buses also pose to risk as system voltages also start to decrease. From the analysis, it is suggested that for maintaining the quality of network, time varying detailed assessments should be performed during the calculations of sizing of distributed generation