Adaptive current harmonic estimation under fault conditions for smart grid systems

Rivas, Angel Esteban Labrador; Silva, Newton da; Abrão, Taufik

doi:10.1016/j.epsr.2020.106276

Cited by 21 publications

(6 citation statements)

References 26 publications

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“…In future, the proposed EFDLMS can be used for smart grid applications. 46,47 New fractional derivatives [48][49][50] can also be explored to design novel gradient based algorithms.…”

Section: Discussionmentioning

confidence: 99%

Enhanced fractional adaptive processing paradigm for power signal estimation

Chaudhary

Khan

Raja

et al. 2022

Math Methods in App Sciences

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Fractional calculus tools have been exploited to effectively model variety of engineering, physics and applied sciences problems. The concept of fractional derivative has been incorporated in the optimization process of least mean square (LMS) iterative adaptive method. This study exploits the recently introduced enhanced fractional derivative based LMS (EFDLMS) for parameter estimation of power signal formed by the combination of different sinusoids. The EFDLMS addresses the issue of fractional extreme points and provides faster convergence speed. The performance of EFDLMS is evaluated in detail by taking different levels of noise in the composite sinusoidal signal as well as considering various fractional orders in the EFDLMS. Simulation results reveal that the EDFLMS is faster in convergence speed than the conventional LMS (i.e., EFDLMS for unity fractional order).

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“…In future, the proposed EFDLMS can be used for smart grid applications. 46,47 New fractional derivatives [48][49][50] can also be explored to design novel gradient based algorithms.…”

Section: Discussionmentioning

confidence: 99%

Enhanced fractional adaptive processing paradigm for power signal estimation

Chaudhary

Khan

Raja

et al. 2022

Math Methods in App Sciences

View full text Add to dashboard Cite

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“…There-fore, PQ estimation is realized by using non-stationary approaches, such as time-frequency or time-scale representation [88][89][90][91][92]. These methods include Hilbert-Huang transform (HHT), continuous wavelet transform (CWT) and Kalman filters (KF) [8,88,[93][94][95].…”

Section: Extension To Non-stationary Conditionsmentioning

confidence: 99%

Power Quality Disturbances Characterization Using Signal Processing and Pattern Recognition Techniques: A Comprehensive Review

2023

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Several factors affect existing electric power systems and negatively impact power quality (PQ): the high penetration of renewable and distributed sources that are based on power converters with or without energy storage, non-linear and unbalanced loads, and the deployment of electric vehicles. In addition, the power grid needs more improvement in the performances of real-time PQ monitoring, fault diagnosis, information technology, and advanced control and communication techniques. To overcome these challenges, it is imperative to re-evaluate power quality and requirements to build a smart, self-healing power grid. This will enable early detection of power system disturbances, maximize productivity, and minimize power system downtime. This paper provides an overview of the state-of-the-art signal processing- (SP) and pattern recognition-based power quality disturbances (PQDs) characterization techniques for monitoring purposes.

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“…New technologies of smart grid, such as dynamic line rating [4] and situation awareness [5], require wide-area line operation data based on widely distributed OCMS. In the OCMS for power transmission lines, line current measurement can directly reflect the operation status of transmission lines and different line faults [6]. Therefore, line current measurement is an intuitive way of OCMS for power transmission lines [7].…”

Section: Introductionmentioning

confidence: 99%

Time-Multiplexed Self-Powered Wireless Current Sensor for Power Transmission Lines

et al. 2021

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Current measurement is a key part of the monitoring system for power transmission lines. Compared with the conventional current sensor, the distributed, self-powered and contactless current sensor has great advantages of safety and reliability. By integrating the current sensing function and the energy harvesting function of current transformer (CT), a time-multiplexed self-powered wireless sensor that can measure the power transmission line current is presented in this paper. Two operating modes of CT, including current sensing mode and energy harvesting mode, are analyzed in detail. Through the design of mode-switching circuit, harvesting circuit and measurement circuit are isolated using only one CT secondary coil, which eliminates the interference between energy harvesting and current measurement. Thus, the accurate measurement in the current sensing mode and the maximum energy collection in the energy harvesting mode are both realized, all of which simplify the online power transmission line monitoring. The designed time-multiplexed working mode allows the sensor to work at a lower transmission line current, at the expense of a lower working frequency. Finally, the proposed sensor is verified by experiments.

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Adaptive current harmonic estimation under fault conditions for smart grid systems

Cited by 21 publications

References 26 publications

Enhanced fractional adaptive processing paradigm for power signal estimation

Enhanced fractional adaptive processing paradigm for power signal estimation

Power Quality Disturbances Characterization Using Signal Processing and Pattern Recognition Techniques: A Comprehensive Review

Time-Multiplexed Self-Powered Wireless Current Sensor for Power Transmission Lines

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