Enhancing Fault Detection in Power Load Management Systems: A Neural Network Approach with Seq2Seq-CNN-LSTM Models-Reference-Cited by-同舟云学术

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Enhancing Fault Detection in Power Load Management Systems: A Neural Network Approach with Seq2Seq-CNN-LSTM Models

Published:2024-03-16 Issue: Volume: Page:490-494
ISSN:
Container-title:2024 10th International Symposium on System Security, Safety, and Reliability (ISSSR)
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Author:

Feng Meiling¹,Wang Shuyang²,Yu Haoyang³,Guo Qiang⁴,Li Bin¹

Affiliation:

1. North China Electric Power University,School of Electric and Electronic Engineering,Beijing,China

2. China Electric Power Research Institute,Beijing,China

3. State Grid Yichun Electric Power Supply Company,Yichun,China

4. State Grid Changyi Electric Power Supply Company,Changyi,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10562059/10562060/10562088.pdf?arnumber=10562088

Reference11 articles.

1. Investigation on Power System Dynamic Monitoring System Using Artificial Neural Networks

2. Machine Learning: A Comprehensive Exploration of Fault Detection and Diagnosis in Smart Grids

3. A Single-Level Rule-Based Model Predictive Control Approach for Energy Management of Grid-Connected Microgrids

4. A Digital Twin Approach for Fault Diagnosis in Unmanned Ships Integrated Power System

5. Distributed Generation Planning and Optimization: Deterministic versus Heuristic Approaches

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