Reduction of source current harmonics in ANN controlled induction motor

Sivakumar, A.; Selvan, N.B. Muthu

doi:10.1016/j.aej.2017.03.048

Cited by 8 publications

(2 citation statements)

References 12 publications

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“…For stability study, to analyze the stability of a system including a power converter and constant power loads. We need to analyze the system stability from the ac side [6], [10]. The analysis was carried out for two different loads.…”

Section: Type Of Loadmentioning

confidence: 99%

Multiple AI based Controlling Techniques for Power Filter Output Quality Improvement

Raghuvanshi

Lomash

2021

IJOSCIENCE

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The excessive of power electronics devices in distribution system has evolved the problem of power quality. This work represents the effective solution of shunt active power filter for eliminating the harmonics to maintain the quality of utility power supply. In the proposed scheme shunt active filter acts as a voltage source and eliminates harmonics by injecting equal but opposite harmonics components at the point of common coupling. Simulation of shunt active filter based on instantaneous reactive has been achieved in the MATLAB/SIMULINK environment. The controllers are being designed with the objective of reducing the THD% in voltage and current available at the nonlinear load terminal of the system. The controller incorporated optimization algorithms based on the artificial intelligence techniques as well. The comparative analysis of the effectiveness and efficiency of the controllers in improving the quality factors has been carried out. The distortion level in the output voltage waveforms in both the cases being fed to the load when compared, it is found that proposed hybrid structure of control for the filter is more effective in reducing the distortion as compared to standard PQ theory based architecture. The study concluded that the total harmonic distortion in the voltage output waveform being fed to the load using only PQ theory based online learning algorithm is found to be 1.59 % while in case of the output voltage at the load terminal from the power filter using proposed hybrid algorithm comprising of NN learning with CSA optimizing control and PQ_RLS algorithm for THD reduction the THD% level is 0.43 %.

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Section: Type Of Loadmentioning

confidence: 99%

Multiple AI based Controlling Techniques for Power Filter Output Quality Improvement

Raghuvanshi

Lomash

2021

IJOSCIENCE

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“…By design, an induction motor can tolerate reasonable levels of voltage unbalance but when the unbalance becomes excessive the motor must be derated to prevent early damage due to voltage-unbalance induced harmonic currents [7]. In the study by [15], a Neural Network controller was proposed for reducing torque ripple and current harmonics. The derating factor of an induction motor is determined by analysing comparatively the performance of the motor under unbalanced and balanced voltage operational conditions, and it is calculated as the ratio of the mechanical output power during unbalance voltage to that under balanced supply [16], [17].…”

Section: Introductionmentioning

confidence: 99%

Determining the operational status of a three phase induction motor using a predictive data mining model

Adekitan

Adewale

Alashiri

2019

IJPEDS

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<span lang="EN-GB">The operational performance of a three phase induction motor is impaired by unbalanced voltage supply due to the generation of negative sequence currents, and negative sequence torque which increase motor losses and also trigger torque pulsations. In this study, data mining approach was applied in developing a predictive model using the historical, simulated operational data of a motor for classifying sample motor data under the appropriate type of voltage supply i.e. balanced (BV) and unbalance voltage supply (UB = 1% to 5%). A dataset containing the values of a three phase induction motor’s performance parameter values was analysed using KNIME (Konstanz Information Miner) analytics platform. Three predictive models; the Naïve Bayes, Decision Tree and the Probabilistic Neural Network (PNN) Predictors were deployed for comparative analysis. The dataset was divided into two; 70% for model training and learning, and 30% for performance evaluation. The three predictors had accuracies of 98.649%, 100% and 98.649% respectively, and this confirms the suitability of data mining methods for predictive evaluation of a three phase induction motor’s performance using machine learning</span>

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Improved Exergy in Three Phase Induction Motor by Eliminating Harmonics Using Wavelet Packet Transform

Anuroopa¹,

Therese²,

Biju³

2022

Green Energy and Technology

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Reduction of source current harmonics in ANN controlled induction motor

Cited by 8 publications

References 12 publications

Multiple AI based Controlling Techniques for Power Filter Output Quality Improvement

Multiple AI based Controlling Techniques for Power Filter Output Quality Improvement

Determining the operational status of a three phase induction motor using a predictive data mining model

Improved Exergy in Three Phase Induction Motor by Eliminating Harmonics Using Wavelet Packet Transform

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