Harmonic Elimination and Reactive Power Compensation with a Novel Control Algorithm based Active Power Filter

Garanayak, Priyabrat; Panda, Gayadhar

doi:10.6113/jpe.2015.15.6.1619

Cited by 10 publications

(6 citation statements)

References 20 publications

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“…Case 1 : If the APF monitors harmonic components only (Blasko, 2007; Garanayak and Panda, 2015; Pereira et al, 2011; Ponnusamy and Narri, 2012), then load current becomes…”

Section: Harmonics and Reactive Power Compensationmentioning

confidence: 99%

“…However, it is restricted by its high rating inverter used as an APF and large value of DC bus capacitor voltage; that is, the required voltage should be more than 50% of the supply voltage. A shunt hybrid active power filter (SHAPF) topology has been proposed for the sake of improving filtering performance, scale down the rating of an APF and avoiding the resonance problems introduced by the PPFs (Garanayak and Panda, 2015; Lam and Wong, 2014; Rahmani et al, 2013; Srianthumrong and Akagi, 2003). The structure of three-phase SHAPF is shown in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

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An adaptive linear neural network with least mean M-estimate weight updating rule employed for harmonics identification and power quality monitoring

Garanayak

Panda

2017

Transactions of the Institute of Measurement and Control

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This paper describes a combined adaptive linear neural network and least mean M-estimate (ADALINE-LMM) algorithm for estimating the amplitude and phase of the individual harmonic contained in a distorted power system current signal. The weight vector of the ADALINE is updated iteratively by LMM algorithm. A Hampel’s three parts redescending M-estimator function is incorporated in the instantaneous cost function to provide thresholds for identifying and eliminating the effect of temporary fluctuation owing to the presence of impulsive noise. This type of combined approach shows more accurate and faster tracking capability than the combined ADALINE and variable step size least mean square (ADALINE-VSLMS) algorithm. In addition to this, the proposed algorithm is suggested in shunt hybrid active power filter (SHAPF) for extracting the harmonics and reactive power components from the distorted load currents. Extensive time domain simulation is carried out to evaluate the performance of the SHAPF for maintaining the power quality of a system under various demanding situations. Moreover, an experimental setup is developed in the laboratory for verification of the proposed control technique in a real-time application using a Spartan 3A DSP processor.

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“…Case 1 : If the APF monitors harmonic components only (Blasko, 2007; Garanayak and Panda, 2015; Pereira et al, 2011; Ponnusamy and Narri, 2012), then load current becomes…”

Section: Harmonics and Reactive Power Compensationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An adaptive linear neural network with least mean M-estimate weight updating rule employed for harmonics identification and power quality monitoring

Garanayak

Panda

2017

Transactions of the Institute of Measurement and Control

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“…A least mean square (LMS) control based on Variable step‐size leaky least mean square based algorithm has been used to control shunt active power compensator for removing the harmonics from the supply current. The step size for weight adjustment changes automatically . However, the application of improved Adaline as a new PLL as well as for load compensation is not reported in literature.…”

Section: Introductionmentioning

confidence: 99%

Design and performance analysis of improved Adaline technique for synchronization and load compensation of grid‐tied photovoltaic system

Saxena

Singh

Nath

2020

Int Trans Electr Energ Syst

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Summary The paper discusses the design, modeling, simulation, and implementation of improved Adaline technique, which has been used for grid synchronization as well as extended further for load compensation. A simple but effective method is proposed to improve the performance of the conventional Adaline technique. The conventional Adaline controller uses a fixed learning rate while the proposed Adaline is developed using variable learning, which improves both the steady‐state and dynamic response. Simulation and experimental results have been demonstrated, which confirm the feasibility of the proposed approach. Suitable performance comparisons highlight the effectiveness of the proposed approach.

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“…The currents of the linear motor and the loads of the pump differ according to the working conditions of the oil well [13,14]. The operating current curves of the linear motor in different working conditions are shown in Figure 2.…”

Section: Feature Extractionmentioning

confidence: 99%

A Fault Diagnosis Method for Oil Well Pump Using Radial Basis Function Neural Network Combined with Modified Genetic Algorithm

Sun

et al. 2017

Journal of Control Science and Engineering

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This paper presents a new method to diagnose oil well pump faults using a modified radial basis function neural network. With the development of submersible linear motor technology, rodless pumping units have been widely used in oil exploration. However, the ground indicator diagram method cannot be used to diagnose the working conditions of rodless pumping units because it is based on the load change of the polished rod suspension point and its displacement. To solve this problem, this paper presents a new method that is applicable to rodless oil pumps. The advantage of this new method is its use of a simple feature extraction method and advanced genetic algorithm to optimize the threshold and weight of the RBF neural network. In this paper, we extract the characteristic value from the operation parameters of the submersible linear motor and oil wellhead as the input vector of the fault diagnosis model. Through experimental analysis, the proposed method is proven to have good convergence performance, high accuracy, and high reliability.

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Harmonic Elimination and Reactive Power Compensation with a Novel Control Algorithm based Active Power Filter

Cited by 10 publications

References 20 publications

An adaptive linear neural network with least mean M-estimate weight updating rule employed for harmonics identification and power quality monitoring

An adaptive linear neural network with least mean M-estimate weight updating rule employed for harmonics identification and power quality monitoring

Design and performance analysis of improved Adaline technique for synchronization and load compensation of grid‐tied photovoltaic system

A Fault Diagnosis Method for Oil Well Pump Using Radial Basis Function Neural Network Combined with Modified Genetic Algorithm

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