Age of Information-Optimized Differential Protection Strategy for Smart Grids

Differential protection is a fundamental mechanism in power systems for detecting and isolating faults. However, traditional protection schemes face significant challenges in modern smart grids due to communication delays and the inability to dynamically adapt to real-time information. These limitat...

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Main Authors: Jiajia Fu, Zhongmiao Kang, Ying Zeng, Zanhong Wu
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10981742/
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author Jiajia Fu
Zhongmiao Kang
Ying Zeng
Zanhong Wu
author_facet Jiajia Fu
Zhongmiao Kang
Ying Zeng
Zanhong Wu
author_sort Jiajia Fu
collection DOAJ
description Differential protection is a fundamental mechanism in power systems for detecting and isolating faults. However, traditional protection schemes face significant challenges in modern smart grids due to communication delays and the inability to dynamically adapt to real-time information. These limitations often result in reduced fault detection accuracy and delayed system response, threatening the reliability and stability of the grid. To address these shortcomings, we propose an Age of Information (AoI)-optimized differential protection strategy tailored for smart grids. By modeling the differential protection problem as a remote Markov Decision Process (MDP), we incorporate AoI as a critical factor to capture the freshness of information in decision-making under stochastic delays. Our analysis reveals that treating AoI as auxiliary side information, rather than a standalone optimization goal, significantly enhances the timeliness of information and indirectly improves fault detection accuracy. By leveraging AoI, we show that it is possible to enhance the timeliness and accuracy of fault detection, even under adverse network conditions, by ensuring that the system relies on the freshest information available. In particular, our results demonstrate a 6.5% improvement in information freshness compared to traditional methods, leading to enhanced system performance. This study provides new insights into leveraging information freshness to overcome the inherent limitations of traditional differential protection schemes, thereby improving the efficiency and resilience of modern power systems.
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spelling doaj-art-730e9445eb6f4e93a1f1208cdbf904b92025-08-20T02:28:19ZengIEEEIEEE Access2169-35362025-01-0113789057891410.1109/ACCESS.2025.356626410981742Age of Information-Optimized Differential Protection Strategy for Smart GridsJiajia Fu0Zhongmiao Kang1Ying Zeng2https://orcid.org/0009-0007-8986-4954Zanhong Wu3Electric Power Dispatching Control Center, Guangdong Power Grid Company Ltd., Guangzhou, ChinaElectric Power Dispatching Control Center, Guangdong Power Grid Company Ltd., Guangzhou, ChinaElectric Power Dispatching Control Center, Guangdong Power Grid Company Ltd., Guangzhou, ChinaElectric Power Dispatching Control Center, Guangdong Power Grid Company Ltd., Guangzhou, ChinaDifferential protection is a fundamental mechanism in power systems for detecting and isolating faults. However, traditional protection schemes face significant challenges in modern smart grids due to communication delays and the inability to dynamically adapt to real-time information. These limitations often result in reduced fault detection accuracy and delayed system response, threatening the reliability and stability of the grid. To address these shortcomings, we propose an Age of Information (AoI)-optimized differential protection strategy tailored for smart grids. By modeling the differential protection problem as a remote Markov Decision Process (MDP), we incorporate AoI as a critical factor to capture the freshness of information in decision-making under stochastic delays. Our analysis reveals that treating AoI as auxiliary side information, rather than a standalone optimization goal, significantly enhances the timeliness of information and indirectly improves fault detection accuracy. By leveraging AoI, we show that it is possible to enhance the timeliness and accuracy of fault detection, even under adverse network conditions, by ensuring that the system relies on the freshest information available. In particular, our results demonstrate a 6.5% improvement in information freshness compared to traditional methods, leading to enhanced system performance. This study provides new insights into leveraging information freshness to overcome the inherent limitations of traditional differential protection schemes, thereby improving the efficiency and resilience of modern power systems.https://ieeexplore.ieee.org/document/10981742/Differential protectionsmart gridsMarkov decision processage of informationremote communication-control co-designfault detection
spellingShingle Jiajia Fu
Zhongmiao Kang
Ying Zeng
Zanhong Wu
Age of Information-Optimized Differential Protection Strategy for Smart Grids
IEEE Access
Differential protection
smart grids
Markov decision process
age of information
remote communication-control co-design
fault detection
title Age of Information-Optimized Differential Protection Strategy for Smart Grids
title_full Age of Information-Optimized Differential Protection Strategy for Smart Grids
title_fullStr Age of Information-Optimized Differential Protection Strategy for Smart Grids
title_full_unstemmed Age of Information-Optimized Differential Protection Strategy for Smart Grids
title_short Age of Information-Optimized Differential Protection Strategy for Smart Grids
title_sort age of information optimized differential protection strategy for smart grids
topic Differential protection
smart grids
Markov decision process
age of information
remote communication-control co-design
fault detection
url https://ieeexplore.ieee.org/document/10981742/
work_keys_str_mv AT jiajiafu ageofinformationoptimizeddifferentialprotectionstrategyforsmartgrids
AT zhongmiaokang ageofinformationoptimizeddifferentialprotectionstrategyforsmartgrids
AT yingzeng ageofinformationoptimizeddifferentialprotectionstrategyforsmartgrids
AT zanhongwu ageofinformationoptimizeddifferentialprotectionstrategyforsmartgrids