Comprehensive Review of Edge Computing for Power Systems: State of the Art, Architecture, and Applications

The increasing complexity of conventional energy distribution systems, combined with the growing demand for efficient data processing, has necessitated the implementation of smart grid technologies and the integration of advanced computing paradigms such as edge computing. Traditional cloud-based solutions face significant challenges, including high latency, limited bandwidth, and cybersecurity vulnerabilities, rendering them less effective for real-time smart grid applications. Edge computing enables localized data processing, which significantly reduces latency and optimizes bandwidth usage. These capabilities enhance the resilience and intelligence of modern energy systems. This paper presents a systematic review of edge computing in energy distribution systems, examining its architectures, methodologies, and real-world applications. Key application areas consist of real-time data transmission, smart metering, microgrid management, anomaly and fault detection, state estimation, and energy management. The analysis shows how edge computing improves secure communication, supports decentralized intelligence, and facilitates scalable energy optimization. Beyond these advantages, the review also identifies critical challenges such as interoperability issues, resource constraints, and security vulnerabilities. By categorizing edge computing applications, the findings provide a comprehensive reference for both researchers and industry professionals working on the development of next-generation energy management systems.

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Publication Details

Journal
Applied Sciences
Published
2025-04-21
DOI
https://doi.org/10.3390/app15084592
Citations
22
Primary Topic
Smart Grid and Power Systems
Type
article
Field-Weighted Citation Impact
16.07
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article

Comprehensive Review of Edge Computing for Power Systems: State of the Art, Architecture, and Applications

Erman Terciyanlı, Kamil Çağatay Bayındır, Yunus Yalman, Fatma Yıldırım
22 citations
Applied Sciences
Smart Grid and Power Systems
16.07
article

Comprehensive Review of Edge Computing for Power Systems: State of the Art, Architecture, and Applications

Erman Terciyanlı, Kamil Çağatay Bayındır, Yunus Yalman, Fatma Yıldırım
article en
22 citations

Abstract

The increasing complexity of conventional energy distribution systems, combined with the growing demand for efficient data processing, has necessitated the implementation of smart grid technologies and the integration of advanced computing paradigms such as edge computing. Traditional cloud-based solutions face significant challenges, including high latency, limited bandwidth, and cybersecurity vulnerabilities, rendering them less effective for real-time smart grid applications. Edge computing enables localized data processing, which significantly reduces latency and optimizes bandwidth usage. These capabilities enhance the resilience and intelligence of modern energy systems. This paper presents a systematic review of edge computing in energy distribution systems, examining its architectures, methodologies, and real-world applications. Key application areas consist of real-time data transmission, smart metering, microgrid management, anomaly and fault detection, state estimation, and energy management. The analysis shows how edge computing improves secure communication, supports decentralized intelligence, and facilitates scalable energy optimization. Beyond these advantages, the review also identifies critical challenges such as interoperability issues, resource constraints, and security vulnerabilities. By categorizing edge computing applications, the findings provide a comprehensive reference for both researchers and industry professionals working on the development of next-generation energy management systems.

Applied SciencesVol. 15(8)
Ankara Yıldırım Beyazıt University (TR)
Openalex Percentile: Top 1%
Smart Grid and Power Systems
16.07
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Comprehensive Review of Edge Computing for Power Systems: State of the Art, Architecture, and Applications — Erman Terciyanlı, Kamil Çağatay Bayındır, et al. · Applied Sciences (2025) | TGRS Research Map | TGRS