Enhanced harmonic state estimation in unbalanced three-phase electrical grids based on the Kalman filter and physical scale-down implementation

Molina-Moreno, Ismael; Medína, A.; Cisneros-Magana, Rafael; Anaya‐Lara, Olimpo; Salazar-Torres, Juan Alfonso

doi:10.1016/j.ijepes.2020.106243

Cited by 15 publications

(3 citation statements)

References 30 publications

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“…The PF equations of the power supply and load measured via TWM are proposed in Section II, and the models of the slack bus and distribution transformers are improved in Section III. The models of the remaining components are introduced as follows: the PF equations of buses measured via THM take the phase-to-neutral active power, reactive power, and voltage magnitude as the input of the PF model; the PF equations of the load and power supply measured via THM can be found in [12] and [13]; and the line of MVDS is three-phase three-wire and its model can be obtained from [24].…”

Section: A Models Of Other Components In Pf Modelmentioning

confidence: 99%

Power Flow Model for Medium-voltage Distribution Systems Considering Measurement and Structure Characteristics

Lu,

Yan,

Huang

et al. 2024

Journal of Modern Power Systems and Clean Energy

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Medium-voltage distribution systems (MVDSs) mainly consist of a feeder head, lines, distribution transformers, and the equivalent load or power supply interfaced with the distribution transformers. The information of such load or power supply can be measured via the three-wattmeter method (THM) and the two-wattmeter method (TWM). The measurements can be used to perform the control of the power supply and simulate the characteristics of the load, so the models of the load and the power supply need to consider the measurement characteristics. Existing research works on three-phase power flow (PF) just consider the measurement characteristics of THM. Hence, the PF equation of the bus measured via TWM is firstly built. Based on conventional measurements, an accurate and general model of the grounded and ungrounded slack bus is proposed. Furthermore, the influence arising from the connection type and angle shift of distribution transformers on the admittance matrix is considered, and thus a general three-phase transformer model is summarized, which is applicable for all the transformers mentioned herein. Finally, Newton' s method is adopted to solve the PF calculation, and the performance of the proposed PF model is demonstrated through designed tests.

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Section: A Models Of Other Components In Pf Modelmentioning

confidence: 99%

Power Flow Model for Medium-voltage Distribution Systems Considering Measurement and Structure Characteristics

Lu,

Yan,

Huang

et al. 2024

Journal of Modern Power Systems and Clean Energy

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“…The number of measurements was around 1.35 times the number of state variables. Kalman filter (KF) methods have also been applied in HSE [7], [15] and were reported to be fast. An adaptive KF was applied in [7], which did not require explicit knowledge of the noise covariance matrix.…”

Section: B Assessment Of the State-of-the-artmentioning

confidence: 99%

Harmonic Current Estimation of Unmonitored Harmonic Sources With a Novel Oversampling Technique for Limited Datasets

et al. 2022

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In modern power systems, harmonics are amongst the significant issues attributed to renewable energy sources and nonlinear loads. Direct harmonic monitoring of the entire power system may be too costly or impractical, and measured data could be limited. In this paper, a new methodology is proposed to estimate harmonic current rms values of unmonitored harmonic sources, based on harmonic voltage rms magnitudes only, measured at a limited number of monitored buses. A new technique of output curve-normalization is employed in pre-processing. Subsequently, a method is proposed to refine the architecture of the Artificial Neural Networks' (ANNs), after which ANN-based harmonic current estimators are developed for each harmonic order and each harmonic source. Furthermore, a novel Neural Oversampling Consensus Algorithm for Regression (NOCAR) is proposed to improve estimation accuracy. K-Nearest Neighbor (KNN) and ANN are combined in developing NOCAR. A comparison is made with state-of-the-art techniques by using synthetic data, which demonstrates both the proposed method's robustness and its capability to perform when minimal information is available. The implementation for real data demonstrates the efficiency of the ANNbased harmonic current estimators with oversampling. The influence of the number of harmonic meters is investigated, revealing the ability of this data-driven technique to reduce the number of harmonic meters, and hence monitoring costs. Moreover, the correlation between different harmonic orders is studied, with results suggesting that, unlike the widely accepted notion, this correlation should not be ignored in harmonic analysis. This study highlights the advantages of integrating intelligent techniques into harmonic monitoring systems. INDEX TERMSArtificial neural networks, harmonic current estimation, harmonic voltage monitors, oversampling. NOMENCLATURE b k+1 j Bias of node j in Layer k+1. D Dataset for ANN training and testing. d k+1 j

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“…This increases the calculation time and could create error in the model, as the voltage harmonics magnitudes might be affected by noise. In [20,21], Kalman filter and state-space model have been employed for estimating the current harmonics in an unbalanced grid using the measured voltage and current values in the time domain. Although these methods estimate the current harmonics in unbalanced condition, the impact of other conditions, such as weak grid, has not been investigated.…”

Section: Introductionmentioning

confidence: 99%

Modelling and prediction of current harmonics generated by power converters in distribution networks

Moradi

Yaghoobi

Alduraibi

et al. 2021

IET Generation Trans & Dist

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Predicting current harmonics in distribution networks is essential to find harmonic losses and power quality indices. In order to predict the current harmonics, the effect of grid impedance and voltage distortions on grid-connected power converters need to be considered. The effects of these parameters on current harmonics can be nonlinear, which complicates the system analysis. Consequently, this paper investigates the impacts of background voltage harmonics, grid impedance, and multi-parallel grid-connected converters on current harmonics at a point of common coupling. Moreover, a novel method called combined least squares and kriging (CLSK) is proposed to predict the current harmonics after evaluating the level of system nonlinearity. In the proposed CLSK method, the prediction model is developed by measured voltage and current harmonics at the point of common coupling to identify and predict the current harmonics. This analysis shows that using the proposed CLSK method, the accuracy of the current harmonic prediction is increased compared to the existing methods. The accuracy and the efficiency of the proposed CLSK method are verified by lab experimental results and field measurement data.

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Enhanced harmonic state estimation in unbalanced three-phase electrical grids based on the Kalman filter and physical scale-down implementation

Cited by 15 publications

References 30 publications

Power Flow Model for Medium-voltage Distribution Systems Considering Measurement and Structure Characteristics

Power Flow Model for Medium-voltage Distribution Systems Considering Measurement and Structure Characteristics

Harmonic Current Estimation of Unmonitored Harmonic Sources With a Novel Oversampling Technique for Limited Datasets

Modelling and prediction of current harmonics generated by power converters in distribution networks

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