Nonlinear identification approach for black-box modeling of voltage source converter harmonic characteristics

Abdelsamad, Ahmed S.; Myrzik, M.A. Johanna; Kaufhold, Elias; Meyer, Jan; Schegner, Peter

doi:10.1109/epec48502.2020.9320079

Cited by 11 publications

(4 citation statements)

References 9 publications

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“…A typical representation of PV inverters consists of the decoupled Norton model, which is represented by a current source in parallel to an admittance Y Inv (Figure 1) or the more advanced coupled Norton model that can also reflect the frequency couplings between voltage and current at different frequencies. The Hammerstein-Wiener model has also been studied for the feasibility as a black-box model structure [16], but still faces major challenges to reflect the frequency coupling appropriately. Frequency coupling implies that a single-frequent excitation at the system input leads to a multi-frequent system output.…”

Section: Black-box Approachmentioning

confidence: 99%

“…The use of ANNs has been proposed in previous work, e.g., for impedance estimations in power electronic (PE) systems by recurrent neural networks (RNN) [13]. In terms of device modeling, the Hammerstein-Wiener (HW) model ( [14][15][16]) has been introduced for which an ANN has been integrated to represent the nonlinear model part within the HW model. Though the HW model can be used as a time domain model, as of yet it is not able to represent frequency coupling components in the spectrum of grid-side inverter current and has not been studied for transitions between different steady states.…”

Section: Introductionmentioning

confidence: 99%

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Feasibility of Black-Box Time Domain Modeling of Single-Phase Photovoltaic Inverters Using Artificial Neural Networks

et al. 2021

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This paper introduces a new black-box approach for time domain modeling of commercially available single-phase photovoltaic (PV) inverters in low voltage networks. An artificial neural network is used as a nonlinear autoregressive exogenous model to represent the steady state behavior as well as dynamic changes of the PV inverter in the frequency range up to 2 kHz. The data for the training and the validation are generated by laboratory measurements of a commercially available inverter for low power applications, i.e., 4.6 kW. The state of the art modeling approaches are explained and the constraints are addressed. The appropriate set of data for training is proposed and the results show the suitability of the trained network as a black-box model in time domain. Such models are required, i.e., for dynamic simulations since they are able to represent the transition between two steady states, which is not possible with classical frequency-domain models (i.e., Norton models). The demonstrated results show that the trained model is able to represent the transition between two steady states and furthermore reflect the frequency coupling characteristic of the grid-side current.

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Section: Black-box Approachmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Feasibility of Black-Box Time Domain Modeling of Single-Phase Photovoltaic Inverters Using Artificial Neural Networks

et al. 2021

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“…While alternative model representations study the use of nonlinear structures, e.g. in terms of the Hammerstein model [20], the Hammerstein-Wiener model [21], [22] or Neural Networks [23], the conventional representation makes use of classical circuit elements in terms of the decoupled Norton model, i.e. a current source and an admittance.…”

Section: ) Black-box Approachmentioning

confidence: 99%

Impact of harmonic distortion on the supraharmonic emission of pulsewidth modulated single-phase power electronic devices

Kaufhold¹,

Meyer²,

Schegner³

2021

REPQJ

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This study demonstrates the frequency coupling in pulse width modulated (PWM) single-phase converters and inverters. As current state of the art, the harmonic frequency range, e.g. from fundamental frequency up to 2 kHz, is typically assessed separately from the so-called supraharmonic frequency range, i.e. above 2 kHz up to 150 kHz. The frequency coupling between the harmonic and supraharmonic frequency range has not been thoroughly studied and is currently often neglected in the design process as well as for the analysis of the emission of power electronic devices. The aim of this study is to analyse the behaviour of the frequency coupling between the harmonic and the supraharmonic range. In addition, laboratory measurements of a commercially available single-phase inverter for photovoltaic applications are shown to verify the findings.

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“…In order to improve the detection accuracy of harmonics in the system, Sun proposed a new harmonic detection method based on the synchronous serialization transform and a Hilbert operator based on local spectral maximum [8]. Abdelsamad et al suggested a Hammerstein-Wiener identifcation method to establish a black-box model for a voltage source converter, which could satisfy the requirement of obtaining harmonic characteristics and a low computational cost [9]. Taking advantage of the advantages of the FFT to detect steady-state harmonics and dynamic harmonics, a method combining FFT and wavelet transform was put forward by Zheng et al [10].…”

Section: Introductionmentioning

confidence: 99%

Harmonic Detection Method Based on Particle Swarm Optimization and Simulated Annealing Algorithm of Electrohydraulic Servo System

Wang

Song

2022

Journal of Robotics

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Due to the comprehensive influence of many nonlinear coupling factors within a system, when the input signal provided by an electrohydraulic servo shaker is sinusoidal, it often leads to the existence of high-order harmonic components of the system, which makes the output servo signal parameters exist extremely serious. Therefore, the detection of harmonics of the electrohydraulic servo shaker has very important application significance. In this paper, by using simulated annealing (SA) based harmonic detection, a kernel function is introduced to study area influence-based particle swarm optimization (PSO). Using a super accurate and fast global convergence brought by the combination of hybrid particle swarm optimization algorithm and simulated annealing algorithm, it can quickly jump out of the trap of traditional local optimization algorithms and a more stable, high-precision, as well as fast global convergence optimal solution can be obtained. Through the detection and simulation of the amplitude and phase of the harmonics in the system, by comparing the PSO-SA detection with PSO detection, it is proved that the PSO-SA algorithm can well satisfy the accuracy of the detection system, which has advantages such as a fast convergence speed, a high search accuracy, etc.; meanwhile, it is simple and easy to implement.

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Nonlinear identification approach for black-box modeling of voltage source converter harmonic characteristics

Cited by 11 publications

References 9 publications

Feasibility of Black-Box Time Domain Modeling of Single-Phase Photovoltaic Inverters Using Artificial Neural Networks

Feasibility of Black-Box Time Domain Modeling of Single-Phase Photovoltaic Inverters Using Artificial Neural Networks

Impact of harmonic distortion on the supraharmonic emission of pulsewidth modulated single-phase power electronic devices

Harmonic Detection Method Based on Particle Swarm Optimization and Simulated Annealing Algorithm of Electrohydraulic Servo System

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