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Voltage fluctuation (flicker) is a power quality disturbance that can produce several undesirable effects on industrial equipment. This paper aims to present the methodology and results of investigations undertaken to examine the speed and torque of an induction motor (IM) under voltage fluctuation conditions.

The IM response to different characteristics of voltage fluctuations is presented. It will be shown that under a special condition the IM torque can even reach two times the rated torque. To show how this occurs, a qualitative discussion is given on the motor response by linearized equations.

The small-signal analysis was used to determine the frequency which leads to maximum speed fluctuations. It was shown that, if the motor is excited with a modulation frequency (resonant frequency) which is one of its natural frequencies (modes), the mode will act as a fluctuating amplifier and greatly increase the amplitude of torque and speed fluctuations. Sensitivity analysis is also carried out to evaluate the influence of motor parameters on the resonance frequency. The results show that the resonance frequency is not affected at all by the changes in magnetizing reactance. This has been shown that magnetic saturation does not have any impact on the resonance frequency. The most effective parameters are rotor and stator resistances.

With the increasing popularity and use of arc furnace loads in the metallurgy industry and due to the wide application of large IMs in the industry, it is possible that the frequency of torque pulsation locates near a natural frequency and then will create an oscillation with a large magnitude, potentially leading to accelerated fatigue or severe damage of shaft. However, if this phenomenon occurs in industries, the resonance frequency must be filtered from the input voltage. Experimental results on a 1.1 kW, 380 V, 50 Hz, 2 pole IM are used to validate the accuracy of simulation results.

This paper aims to propose a novel matrix-based systematic approach for vulnerability assessment.

The proposed method consists of two major steps. First, the power network is modeled as a topological combination of edges (transmission lines, transformers, etc.) and nodes (buses, substations, etc.). The second step is to use an axiomatic design-based index for topology analysis. This index is based on the systematic counting of possible routes from the start (generators) to destination (loads), considering load importance, before and after a disruption.

The effectiveness of the proposed method is demonstrated through an illustrative example and the Institute of Electrical and Electronics Engineers (IEEE) 14-bus power system. It was shown that the load’s importance influences the results of the vulnerability analysis. The proposed method has some advantages over traditional graph theory such as an explicit description of multiple transmission nodes and assets with multiple conversion processes. Furthermore, it would help the power grid operators and asset investment managers to be better to assess the vulnerable components.

The proposed method can be used in planning, optimization, robustness and hardening of power systems.

The paper presents a matrix-based systematic approach to evaluate and quantify the vulnerability of the power grid’s components.

Squirrel cage induction motors suffer from several faults such as rotor broken bar. One of the powerful methods to detect induction motor faults is the line current signature analysis. This paper aims to present a novel algorithm based on continuous wavelet transform (CWT) to diagnose a rotor broken bar fault.

The proposed CWT has high flexibility in monitoring any frequency of interest in a waveform. Based on this transform, stator current frequency spectrum is analyzed to diagnose the rotor broken bar fault. The algorithm distinguishes the healthy motor from the faulted one based on a proper index. The method can be used in steady-state running time of induction motor and under different loading conditions. Experimental results are presented to show the validity of the proposed approach.

The proposed index considerably increases at the broken bars conditions compared to the healthy conditions. It can clearly diagnose the faulty conditions. The experimental results are found to be in good agreement with the theoretical and simulated results. The proposed method can reduce the noise and spectral leakage effects.

The main contribution of the paper are as follows: using CWT for detection of broken bar faults; introducing a proper index for diagnosing broken bars; and introducing a supplementary index to reduce the noise and spectral leakage effects.