Bad data correction in harmonic state estimation for power distribution systems: an approach based on generalised pattern search algorithm

Melo, Igor D.; Antunes, Matheus P.

doi:10.1016/j.epsr.2021.107684

Cited by 12 publications

(4 citation statements)

References 25 publications

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“…The center of circles O t of the designed face gears is zero point, while the center of circles O p of the point cloud is set roughly. Hence, they are aligned by the pattern search technique [ 37 , 38 ]. The maximum and the minimum radius in the point cloud on the xoy plane are respectively R r max and R r min , and their coordinates are respectively ( x r max , y r max , z r max ) and ( x r min , y r min , z r min ).…”

Section: The Measurement Solutionmentioning

confidence: 99%

A Measurement Solution of Face Gears with 3D Optical Scanning

Zhao

et al. 2022

Materials

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Gears are usually measured by the contact metrology method in gear measuring centers or coordinate measuring machines. Recently, three-dimensional (3D) optical scanning, a non-contact metrology method, has been applied in the industry as an advanced measurement technology mainly due to its high efficiency. However, its applications to gears with complicated geometry, such as face gears, are still limited due to its relatively low accuracy and the void of related measurement solutions. In this work, an accurate measurement solution with 3D optical scanning is proposed for the tooth surface deviations of orthogonal face gears. First, point cloud collection is carried out by the 3D scanner. Furthermore, the measurement solution is implemented with a three-stage algorithm by aligning point clouds with the design model. Subsequently, 3D modeling is studied by numbering the points and reconstructing the real tooth surfaces. An example with a measurement experiment and loaded tooth contact analysis is given to show the validity of the proposed method.

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Section: The Measurement Solutionmentioning

confidence: 99%

A Measurement Solution of Face Gears with 3D Optical Scanning

Zhao

et al. 2022

Materials

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“…Therefore, research is being conducted on both detection and repair technology for synchronous phasor data, and disturbance identification methods for extracting the temporal characteristics of bad data in PMU multivariate measurements. Additionally, recent state estimation algorithms can aid in removing the influence of bad data in both input and output, ensuring accurate state estimation of the power system 24–27 …”

Section: Introductionmentioning

confidence: 99%

“…Additionally, recent state estimation algorithms can aid in removing the influence of bad data in both input and output, ensuring accurate state estimation of the power system. [24][25][26][27] As mentioned above, numerous studies have examined state estimation methods of power systems with different operating conditions, including bad data injection, short-time disturbance, power source side or grid-side fault, and so on. However, there is a lack of research on accurately predicting the state of a power system with a significant proportion of renewable energy in the face of source-side uncertainties.…”

mentioning

confidence: 99%

Enhanced dynamic state estimation of regional new energy power system under different abnormal scenarios

Li,

Jiang,

Cui

et al. 2024

Int J Numerical Modelling

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The high proportion of renewable energy sources in the power grid increases the failure probability of the system, which becomes a new challenge for the safe and stable operation of the regional power grid. To ensure stable control of the power network with substantial renewable energy integration, this article proposes a new method that combines the long short‐term memory (LSTM) neural networks and adaptive cubature Kalman filter (ACKF) to improve the prediction accuracy of mutation data inherited from the renewable generation. Four abnormal scenarios, including low voltage ride‐through (LVRT), high voltage ride‐through (HVRT), continuous fault ride‐through and bad data injection of the regional power grid are investigated through extensive case studies. The proposed method is implemented on the IEEE 30‐node system for performance verification. The simulation results demonstrate that the proposed method has considerably higher robustness than the traditional Kalman filter algorithm and can effectively improve the overall state estimation accuracy of the renewable energy power system under different scenarios.

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“…For example, [19] uses a linearized error analysis to identify GE, while [2], [20] propose innovative approaches for GE detection, identification, and correction. A new method based on a generalized pattern search algorithm for data correction in harmonic SE is presented in [21]. In the SE field, M-estimators have also been proposed in the literature, such as L1 loss (often cited as Charbonnier loss in [22]), pseudo-Huber loss [23], L1-L2 loss [24], German-McClure [25], Cauchy method [26], and Welsch loss [27].…”

Section: Introductionmentioning

confidence: 99%

Robust State Estimation Model for Low Voltage Distribution Networks in the Presence of Multiple Gross Errors

et al. 2023

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One of the primary challenges in solving the State Estimation (SE) problem in low voltage networks is the presence of Gross Errors (GE). If the SE model fails to accurately estimate state variables in the presence of GE, the system operator may receive a distorted image of the power network, potentially leading to unforeseen disruptions, blackouts, and significant economic losses. The classical weighted least squares method, which is commonly used in such problems, exhibits low accuracy when simultaneous GE occurs. This paper provides a comprehensive analysis comparing robust M-estimators designed to handle GE, such as Hachtel and the largest normalized residual test, and presents a novel SE method called the Adaptive Maximum Correntropy Criterion (AMCC). The AMCC employs the maximum correntropy criterion for the loss function and an interior point methodology. Additionally, an adaptive scheme is employed to automatically adjust a high parameter associated with the shape of the related gamma function. We show that, in a real low voltage network, the AMCC exhibits superior accuracy with smaller root-meansquare errors compared to the other estimators studied.

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Bad data correction in harmonic state estimation for power distribution systems: an approach based on generalised pattern search algorithm

Cited by 12 publications

References 25 publications

A Measurement Solution of Face Gears with 3D Optical Scanning

A Measurement Solution of Face Gears with 3D Optical Scanning

Enhanced dynamic state estimation of regional new energy power system under different abnormal scenarios

Robust State Estimation Model for Low Voltage Distribution Networks in the Presence of Multiple Gross Errors

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