Fast and accurate measurement of harmonic parameters employing hybrid adaptive linear neural network and filtered‐x least mean square algorithm

Garanayak, Priyabrat; Panda, Gayadhar

doi:10.1049/iet-gtd.2015.0684

Cited by 31 publications

(34 citation statements)

References 22 publications

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“…The process of envelope parameter estimation is as follows. The coefficients p 1 and p 2 are given by linear fitting of the envelope, and the envelope parameters a * and b * are given by Formula (8). For the simulation model, the harmonic amplitude parameter in the Formula (8) can be a set value which is able to investigate the performance of the fitting algorithm.…”

Section: The Analysis Of Wifft and Envelope Parameters Estimationmentioning

confidence: 99%

“…Several approaches have been reported to analyze harmonics, including wavelet transform [6,7], neural network [8,9], multiple signal classification (MUSIC) algorithm [10,11], fast Fourier transform (FFT)-based method [12,13] and so on. So far, it has been a difficult and important research direction to find a suitable wavelet basis function for harmonic analysis [14,15].…”

Section: Introductionmentioning

confidence: 99%

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Improved Parameter Identification Method for Envelope Current Signals Based on Windowed Interpolation FFT and DE Algorithm

Su¹,

Zhang²,

Chen³

et al. 2018

Algorithms

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Envelope current signals are increasingly emerging in power systems, and their parameter identification is particularly necessary for accurate measurement of electrical energy. In order to analyze the envelope current signal, the harmonic parameters, as well as the envelope parameters, need to be calculated. The interpolation fast Fourier transform (FFT) is a widely used approach which can estimate the signal frequency with high precision, but it cannot calculate the envelope parameters of the signal. Therefore, this paper proposes an improved method based on windowed interpolation FFT (WIFFT) and differential evolution (DE). The amplitude and phase parameters obtained through WIFFT and the envelope parameters estimated by the envelope analysis are optimized using the DE algorithm, which makes full use of the performance advantage of DE. The simulation results show that the proposed method can improve the accuracy of the harmonic parameters and the envelope parameter significantly. In addition, it has good anti-noise ability and high precision.

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Section: The Analysis Of Wifft and Envelope Parameters Estimationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Improved Parameter Identification Method for Envelope Current Signals Based on Windowed Interpolation FFT and DE Algorithm

Su¹,

Zhang²,

Chen³

et al. 2018

Algorithms

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“…Deploying the retrodiction method in a cyber-physical energy system described in Section 2, the distributed harmonic measurement is scheduled as follows:

Sensor nodes of the electric monitoring network measure the harmonics in each branch. The harmonic measurement algorithm is ADALINE [45]. The distributed nodes calculate the amplitudes and phases of each order of harmonics in their branches and send the harmonic data up to the data management system through the two-way sensing network.

Upon the arrival of the harmonic information of the network, the data management system updates the cached electrical state.

…”

Section: Data-aware Retrodiction For Out-of-sequence Measurementmentioning

confidence: 99%

Data-Aware Retrodiction for Asynchronous Harmonic Measurement in a Cyber-Physical Energy System

Liu

Wang

Liu

et al. 2016

Sensors

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Cyber-physical energy systems provide a networked solution for safety, reliability and efficiency problems in smart grids. On the demand side, the secure and trustworthy energy supply requires real-time supervising and online power quality assessing. Harmonics measurement is necessary in power quality evaluation. However, under the large-scale distributed metering architecture, harmonic measurement faces the out-of-sequence measurement (OOSM) problem, which is the result of latencies in sensing or the communication process and brings deviations in data fusion. This paper depicts a distributed measurement network for large-scale asynchronous harmonic analysis and exploits a nonlinear autoregressive model with exogenous inputs (NARX) network to reorder the out-of-sequence measuring data. The NARX network gets the characteristics of the electrical harmonics from practical data rather than the kinematic equations. Thus, the data-aware network approximates the behavior of the practical electrical parameter with real-time data and improves the retrodiction accuracy. Theoretical analysis demonstrates that the data-aware method maintains a reasonable consumption of computing resources. Experiments on a practical testbed of a cyber-physical system are implemented, and harmonic measurement and analysis accuracy are adopted to evaluate the measuring mechanism under a distributed metering network. Results demonstrate an improvement of the harmonics analysis precision and validate the asynchronous measuring method in cyber-physical energy systems.

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“…Adaptive control techniques such as Kalman filter (KF), deadbeat control, least mean square (LMS), least mean fourth (LMF), and modified LMS techniques have been presented for power quality improvement in grid‐tied systems. The fundamental current extraction technique presented in Singh et al shows superior performance than the conventional technique, but real‐time implementation of this technique is difficult and steady‐state performance of the discussed control technique is poor.…”

Section: Introductionmentioning

confidence: 99%

Kalman filter variant intelligent control for power quality improvement in photovoltaic active power filter system

Prince

Panda

2019

Int Trans Electr Energ Syst

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Summary The increased usage of nonlinear loads in the distribution system network with deep integration of renewable energy sources imposes the need for advanced control to improve power quality. With the objective to attain desired sinusoidal voltage waveshape at the common utility point, unity power factor operation, and reduction in harmonics, a swarm intelligent enhanced dual extended Kalman filter (DEKF) control technique for improving the performance of shunt active power filter (SAPF) is proposed in this paper. A photovoltaic (PV) array is integrated at the DC‐bus which supplies the required load power thus reducing the grid power demand. A single sensor‐based control is used to track the maximum power from the two‐stage PV array. The enhancement of the SAPF performance requires proper tuning of parameters; constriction factor‐based particle swarm optimization (PSO) is adopted in this regard. The DEKF estimates both state and parameter from the nonlinear system for generating a reference signal. The performance of the proposed control algorithm is compared with the Extended Kalman filter (EKF)‐based PV‐SAPF system using MATLAB/Simulink. To verify the efficacy of the controller, an experimental PV‐SAPF prototype is developed in the laboratory and tested under balanced and unbalanced supply, dynamic load as well as varying irradiance conditions.

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Fast and accurate measurement of harmonic parameters employing hybrid adaptive linear neural network and filtered‐x least mean square algorithm

Cited by 31 publications

References 22 publications

Improved Parameter Identification Method for Envelope Current Signals Based on Windowed Interpolation FFT and DE Algorithm

Improved Parameter Identification Method for Envelope Current Signals Based on Windowed Interpolation FFT and DE Algorithm

Data-Aware Retrodiction for Asynchronous Harmonic Measurement in a Cyber-Physical Energy System

Kalman filter variant intelligent control for power quality improvement in photovoltaic active power filter system

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