LSTM-Based Fault Direction Estimation and Protection Coordination for Networked Distribution System

Kim, Woo-Hyun; Kim, Ju–Yong; Chae, Woo-Kyu; Kim, Geonho; Lee, Chun-Kwon

doi:10.1109/access.2022.3166836

Cited by 19 publications

(4 citation statements)

References 43 publications

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“…In other words, if a protective device fails to detect the direction of a fault, it can lead to the failure of protection coordination. To solve this problem, [12] proposes a direction detection method using a communication-based protection coordination scheme and a long short-term memory (LSTM) neural network. In particular, the issue of malfunctioning protective devices becomes more severe in NDS with DGs [13].…”

Section: Literature Survey 121 Protection Coordination In Networked D...mentioning

confidence: 99%

A Study on a Communication-Based Algorithm to Improve Protection Coordination under High-Impedance Fault in Networked Distribution Systems

Noh,

Gham,

Yoon

et al. 2023

Sustainability

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The rising demand for stable power supply in distribution systems has increased the importance of reliable supply. Thus, a networked distribution system (NDS) linked with individual lines is being adopted, gradually replacing the radial distribution system (RDS) currently applied to most distribution systems. Implementing the NDS can lead to various improvements in factors such as line utilization rate, acceptance rates of distributed power, and terminal voltages, while mitigating line losses. However, compared with the RDS, the NDS can experience bidirectional fault currents owing to its interconnected lines, thereby hindering protection coordination, which must be addressed before the NDS can be implemented in real-world power systems. Due to the characteristics of NDS, the reverse fault current is relatively small. However, this phenomenon becomes more severe when the high impedance fault (HIF) occurs. In this paper, the malfunction of protective devices during the HIF is directly verified and analyzed in the NDS. As a result, when the HIF occurs, the issue of the reverse protective device malfunctioning worsens because of a reduction in fault current and a failure in direction detection. To solve this issue, this work proposes a communication-based protection algorithm. Through the comparative verification of the proposed algorithm and the conventional protection method, protection coordination can be secured in the case of an HIF without new devices. It must be highlighted that the proposed method does not affect the settings of the protective device and provides a cost-effective and efficient solution since this algorithm is added independently to the existing relay.

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Section: Literature Survey 121 Protection Coordination In Networked D...mentioning

confidence: 99%

A Study on a Communication-Based Algorithm to Improve Protection Coordination under High-Impedance Fault in Networked Distribution Systems

Noh,

Gham,

Yoon

et al. 2023

Sustainability

View full text Add to dashboard Cite

show abstract

“…Its units solve the vanishing gradient problem partially, since LSTM units allow the gradients to flow unchanged [ 12 ]. Based on the advantages of the wavelet transform and the promising capabilities of LSTM [ 13 , 14 , 15 , 16 ], this work proposes using a combination of those techniques in a method named wavelet LSTM. For this purpose, a study will be conducted using the alarm data obtained from a recloser of a power utility company in the Serrana region of Santa Catarina, Brazil.…”

Section: Introductionmentioning

confidence: 99%

Wavelet LSTM for Fault Forecasting in Electrical Power Grids

Branco

Cavalca

Stefenon

et al. 2022

Sensors

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An electric power distribution utility is responsible for providing energy to consumers in a continuous and stable way. Failures in the electrical power system reduce the reliability indexes of the grid, directly harming its performance. For this reason, there is a need for failure prediction to reestablish power in the shortest possible time. Considering an evaluation of the number of failures over time, this paper proposes performing failure prediction during the first year of the pandemic in Brazil (2020) to verify the feasibility of using time series forecasting models for fault prediction. The long short-term memory (LSTM) model will be evaluated to obtain a forecast result that an electric power utility can use to organize maintenance teams. The wavelet transform has shown itself to be promising in improving the predictive ability of LSTM, making the wavelet LSTM model suitable for the study at hand. The assessments show that the proposed approach has better results regarding the error in prediction and has robustness when statistical analysis is performed.

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“…Long Short-Term Memory (LSTM) is a model applied in deep learning that has been widely used by researchers for time series forecasting [9][10][11], its units solve the vanishing gradient problem partially since the LSTM units allow the gradients to flow unchanged [12]. Based on the advantages of the Wavelet transform and the promising capabilities of LSTM [13][14][15][16], this work proposes to use a combination of those techniques in a method named Wavelet LSTM. For this purpose, a study will be conducted using the alarm data obtained from a re-closer of a power utility company in the Serrana region of Santa Catarina, Brazil.…”

Section: Introductionmentioning

confidence: 99%

Wavelet Long Short-Term Memory to Fault Forecasting in Electrical Power Grids

Branco¹,

Cavalca²,

Stefenon³

et al. 2022

Preprint

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The electric power distribution utility is responsible for providing energy to consumers in a continuous and stable way, failures in the electrical power system reduce the reliability indexes of the grid, directly harming its performance. For this reason, there is a need for failure prediction to reestablish power in the shortest possible time. Considering an evaluation of the number of failures over time, this paper proposes to perform a failure prediction during the first year of the pandemic in Brazil (2020) to verify the feasibility of using time series forecasting models for fault prediction. The Long Short-Term Memory (LSTM) model will be evaluated to obtain a forecast result that can be used by the electric power utility to organize the maintenance teams. The Wavelet transform shows to be promising in improving the predictive ability of the LSTM, making the Wavelet LSTM model suitable for the study at hand. The results show that the proposed approach has better results regarding the evaluation of the error in prediction and has robustness when a statistical analysis is performed.

show abstract

LSTM-Based Fault Direction Estimation and Protection Coordination for Networked Distribution System

Cited by 19 publications

References 43 publications

A Study on a Communication-Based Algorithm to Improve Protection Coordination under High-Impedance Fault in Networked Distribution Systems

A Study on a Communication-Based Algorithm to Improve Protection Coordination under High-Impedance Fault in Networked Distribution Systems

Wavelet LSTM for Fault Forecasting in Electrical Power Grids

Wavelet Long Short-Term Memory to Fault Forecasting in Electrical Power Grids

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