Determination of harmonic current contributions of plants supplied from PCC based on state estimation

Sezgin, Erhan; Göl, Murat; Salor, Özgül

doi:10.1109/siu.2015.7130274

Cited by 4 publications

(6 citation statements)

References 10 publications

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“…In order to evaluate the proposed method, Monte Carlo simulations are carried out. Mean squared error (MSE) of the estimation is calculated by evaluating 1000 estimations as shown in (12).…”

Section: Verification Of the Proposed Methodsmentioning

confidence: 99%

“…In (12), n being the number of simulations is equal to 1000, (x i ) represents estimated states, and x i represents the true states. The MSE of the real and imaginary parts of V P CC (V 1 ) estimation are presented in Table 2.…”

Section: Verification Of the Proposed Methodsmentioning

confidence: 99%

“…In [10], optimal measurement placement and observability analysis in state estimation are discussed for harmonic state estimation. The methods proposed in [11,12] are based on the weighted least squares (WLS) state estimator, which is not robust against bad data, such that even in the presence of a single bad data harmonic state estimates may be biased. In order to filter out the bad measurements, a postestimation bad data identification process should be employed, which increases the solution time significantly.…”

Section: Introductionmentioning

confidence: 99%

“…In the literature, there are state estimation-based techniques applied to the harmonic contribution determination problem [8][9][10][11][12]. In [8], a circuit theory-based harmonic state estimation method is implemented and compared with the singular value decomposition (SVD) technique.…”

Section: Introductionmentioning

confidence: 99%

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Determination of harmonic current contributions based on robust state estimation

Sezgin¹,

Göl²,

Salor³

2018

Turk J Elec Eng & Comp Sci

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Abstract:In this paper, a state estimation based method is proposed to determine harmonic current contributions of plants supplied from a point of common coupling (PCC). This work mainly aims to reduce gross error of capacitive voltage transformer (CVT) measurements at harmonic frequencies using robust weighted least absolute value (WLAV) state estimation method, which provides the optimum state estimates for harmonic voltages in the presence of a redundant enough measurement set. Estimated harmonic voltages are then used to solve the harmonic current contribution problem based on superposition theorem. It has been shown that the proposed method can provide optimum harmonic estimates when CVTs are used. The use of the proposed method with proper measurement placement makes resistive-capacitive voltage transformers (RCVTs) redundant. Results of the proposed method are comparable with measurements of RCVTs, which have the disadvantages of having high costs and being cumbersome to install.

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Section: Verification Of the Proposed Methodsmentioning

confidence: 99%

Section: Verification Of the Proposed Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Determination of harmonic current contributions based on robust state estimation

Sezgin¹,

Göl²,

Salor³

2018

Turk J Elec Eng & Comp Sci

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“…Today, two main approaches can be found in the technical literature to treat this problem. The first one seeks to determine, at the point of common coupling (PCC), the harmonic distortion contribution due to customers and utilities using circuit analysis theorems (Norton, Thévenin, and Superposition Theorems) [4][5][6][7][8][9][10][11][12][13]. In reference [5], for example, the electrical utility grid and the customer's load installation at the PCC are modeled through a Norton equivalent circuit and the superposition theorem is used to identify the contribution of each side on the voltage harmonic distortion.…”

Section: Introductionmentioning

confidence: 99%

Evaluating Harmonic Distortions on Grid Voltages Due to Multiple Nonlinear Loads Using Artificial Neural Networks

et al. 2018

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This paper presents a procedure to estimate the impacts on voltage harmonic distortion at a point of interest due to multiple nonlinear loads in the electrical network. Despite artificial neural networks (ANN) being a widely used technique for the solution of a large amount and variety of issues in electric power systems, including harmonics modeling, its utilization to establish relationships among the harmonic voltage at a point of interest in the electric grid and the corresponding harmonic currents generated by nonlinear loads was not found in the literature, thus this innovative procedure is considered in this article. A simultaneous measurement campaign must be carried out in all nonlinear loads and at the point of interest for data acquisition to train and test the ANN model. A sensitivity analysis is proposed to establish the percent contribution of load currents on the observed voltage distortion, which constitutes an original definition presented in this paper. Initially, alternative transient program (ATP) simulations are used to calculate harmonic voltages at points of interest in an industrial test system due to nonlinear loads whose harmonic currents are known. The resulting impacts on voltage harmonic distortions obtained by the ATP simulations are taken as reference values to compare with those obtained by using the proposed procedure based on ANN. By comparing ATP results with those obtained by the ANN model, it is observed that the proposed methodology is able to classify correctly the impact degree of nonlinear load currents on voltage harmonic distortions at points of interest, as proposed in this paper.

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Harmonic source modeling based on the linear cluster-weighted model

Xiang

Shao

Zhang

et al. 2022

2022 7th Asia Conference on Power and Electrical Engineering (ACPEE)

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Determination of harmonic current contributions of plants supplied from PCC based on state estimation

Cited by 4 publications

References 10 publications

Determination of harmonic current contributions based on robust state estimation

Determination of harmonic current contributions based on robust state estimation

Evaluating Harmonic Distortions on Grid Voltages Due to Multiple Nonlinear Loads Using Artificial Neural Networks

Harmonic source modeling based on the linear cluster-weighted model

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