IEEE Transactions on Smart Grid

Aims & Scope

The IEEE Transactions on Smart Grid is a cross disciplinary and internationally archival journal aimed at disseminating results of research on smart grid that relates to, arises from, or deliberately influences energy generation, transmission, distribution and delivery.

The journal publishes original research on theories and development on principles of smart grid technologies and systems.

The Transactions also welcomes manuscripts on design, implementation and evaluation of power systems that are affected by smart grid.

Surveys of existing work on smart grid may also be considered for publication when they propose a new viewpoint on history and a challenging perspective on the future of smart grid.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	9.8

Journal Rank

Year	Value
2024	328

Journal Citation Indicator

Year	Value
2024	16366

SJR (SCImago Journal Rank)

Year	Value
2024	4.608

Quartile

Year	Value
2024	Q1

h-index

Year	Value
2024	253

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Trends in Microgrid Control

  Citation: 2595

  Authors: Daniel E., Ali, Amir H., Claudio A., Reza, Mehrdad, Amir H., Oriol, Maryam, Rodrigo, Guillermo A., Nikos D.

• Autonomous Demand-Side Management Based on Game-Theoretic Energy Consumption Scheduling for the Future Smart Grid

  Citation: 2266

  Authors: Amir-Hamed, Vincent W. S., Juri, Robert, Alberto

• Short-Term Residential Load Forecasting Based on LSTM Recurrent Neural Network

  Citation: 1916

  Authors: Weicong, Zhao Yang, Youwei, David J., Yan, Yuan

• Optimal Residential Load Control With Price Prediction in Real-Time Electricity Pricing Environments

  Citation: 1479

  Authors: Amir-Hamed, Alberto

• Hierarchical Structure of Microgrids Control System

  Citation: 1265

  Authors: Ali, Ali

• Demand Side Management in Smart Grid Using Heuristic Optimization

  Citation: 1009

  Authors: Thillainathan, Dipti, Tan Zong

• A Survey of Distributed Optimization and Control Algorithms for Electric Power Systems

  Citation: 1001

  Authors: Daniel K., Florian, Henrik, Steven H., Sambuddha, Ross, Javad

• Review of Smart Meter Data Analytics: Applications, Methodologies, and Challenges

  Citation: 965

  Authors: Yi, Qixin, Tao, Chongqing

• Harmonic Stability in Power Electronic-Based Power Systems: Concept, Modeling, and Analysis

  Citation: 961

  Authors: Xiongfei, Frede

• A Hybrid AC/DC Microgrid and Its Coordination Control

  Citation: 945

  Authors:

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