Optimizing Fault Detection in Electric Power Load Management Systems: A Reinforcement Learning Approach for Prioritized Test Case Selection-Reference-Cited by-同舟云学术

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Optimizing Fault Detection in Electric Power Load Management Systems: A Reinforcement Learning Approach for Prioritized Test Case Selection

Published:2024-03-16 Issue: Volume:37 Page:502-505
ISSN:
Container-title:2024 10th International Symposium on System Security, Safety, and Reliability (ISSSR)
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Author:

Feng Meiling¹,Chen Ke²,Guo Qiang³,Meng Tao⁴,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 Changyi Electric Power Supply Company,Changyi,China

4. State Grid Lanzhou Power Supply Company

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10562059/10562060/10562078.pdf?arnumber=10562078

Reference12 articles.

1. A smart load management system based on the grasshopper optimization algorithm using the under-frequency load shedding approach

2. A Decentralized Fault Detection Technique for Detecting Single Phase to Ground Faults in Power Distribution Systems With Resonant Grounding

3. Fault Analysis and Handling Research of Power Load Management System;Xiao;Dianzi Shijie [Electronic World],2018

4. Research on Improving Data Integrity of Load Management Terminals for Electric Power Spot Trading Users;Liang;Jidian Xinxi [Mechanical and Electrical Information],2019

5. Quality Assessment of Load Management Terminal Software Based on AHP+Entropy Weight Method;Liang;Neimenggu Dianli Jishu [Inner Mongolia Electric Power Technology],2019

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