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IEEE Transactions on Power Systems
H-index 76

IEEE Transactions on Power Systems

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Electronics and Electrical Engineering 20 366 1309 71
Engineering and Technology 65 118 469 54

Additional Metrics

Number of Best Scientists*: 575
Documents by Best Scientists*: 1694
Top 100 Ranked Scientists*: 16
SCIMAGO H-index: 322
SCIMAGO SJR: 3.629
Impact Factor: 7.2

Overview

Top Research Topics at IEEE Transactions on Power Systems?

The journal covers a variety of subjects, including Electric power system, Control theory, Mathematical optimization, Control engineering and AC power. The work on Electric power system tackled in IEEE Transactions on Power Systems brings together disciplines like Electrical network, Reliability engineering and Electronic engineering. The Reliability engineering study tackled is a key component of adjacent topics in the area of Reliability (statistics).

The journal explores topics in Control theory which can be helpful for research in disciplines like Transient (oscillation) and Voltage. The studies on Mathematical optimization discussed can also contribute to research in the domains of Robustness (computer science) and Economic dispatch.

  • Electric power system (45.98%)
  • Control theory (31.34%)
  • Mathematical optimization (25.51%)

What are the most cited papers published in the journal?

  • MATPOWER: Steady-State Operations, Planning, and Analysis Tools for Power Systems Research and Education (4120 citations)
  • Definition and classification of power system stability IEEE/CIGRE joint task force on stability terms and definitions (2589 citations)
  • The IEEE Reliability Test System-1996. A report prepared by the Reliability Test System Task Force of the Application of Probability Methods Subcommittee (2490 citations)

Research areas of the most cited articles at IEEE Transactions on Power Systems:

The main points discussed in the most cited publications deal with Electric power system, Mathematical optimization, Control theory, Power system simulation and Control engineering. The published papers with studies in Electric power system featured incorporate elements of Control system, Wind power, Electrical network, Reliability engineering and Electricity generation. While the primary focus in the most cited articles is Control theory, they also dissect topics surrounding AC power and Voltage regulation as a whole.

What topics the last edition of the journal is best known for?

  • Statistics
  • Artificial intelligence
  • Operating system

The previous edition focused in particular on these issues:

The journal focuses on Electric power system, Control theory, Mathematical optimization, Power (physics) and AC power. Topics in Electric power system explored in it were investigated in conjunction with research in Convergence (routing), Reliability engineering, Grid, Nonlinear system and Renewable energy. IEEE Transactions on Power Systems addresses concerns in Control theory which are intertwined with other disciplines, such as Transient (oscillation), Stability (probability) and Voltage.

Topics in Mathematical optimization were tackled in line with various other fields like Wind power, Power system simulation and Economic dispatch. While AC power is the focus of IEEE Transactions on Power Systems, it also provided insights into the studies of Distributed generation and Photovoltaic system.

The most cited articles from the last journal are:

  • Definition and Classification of Power System Stability – Revisited & Extended (26 citations)
  • DeepOPF: A Deep Neural Network Approach for Security-Constrained DC Optimal Power Flow (18 citations)
  • Roles of Dynamic State Estimation in Power System Modeling, Monitoring and Operation (15 citations)

Papers citation over time

A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

The top authors publishing in IEEE Transactions on Power Systems (based on the number of publications) are:

  • Antonio J. Conejo (126 papers) absent at the last edition,
  • Vijay Vittal (122 papers) published 5 papers at the last edition, 4 more than at the previous edition,
  • Roy Billinton (122 papers) absent at the last edition,
  • Mohammad Shahidehpour (111 papers) published 17 papers at the last edition, 6 more than at the previous edition,
  • Jianhui Wang (104 papers) published 5 papers at the last edition, 1 more than at the previous edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Only papers with recognized affiliations are considered

The top affiliations publishing in IEEE Transactions on Power Systems (based on the number of publications) are:

  • Tsinghua University (334 papers) published 51 papers at the last edition, 25 more than at the previous edition,
  • Iowa State University (241 papers) published 10 papers at the last edition, 3 more than at the previous edition,
  • Arizona State University (194 papers) published 13 papers at the last edition, 10 more than at the previous edition,
  • University of Saskatchewan (180 papers) published 14 papers at the last edition, 6 more than at the previous edition,
  • Illinois Institute of Technology (173 papers) published 23 papers at the last edition, 11 more than at the previous edition.

The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2021 edition, 15.20% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 23.90% were posted by at least one author from the top 10 institutions publishing in the journal. Another 14.78% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 21.70% of all publications and 39.62% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

  • Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
  • Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
  • Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
  • Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
  • Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Top Publications

  • Definition and Classification of Power System Stability – Revisited & Extended

    Nikos Hatziargyriou;Jovica Milanovic;Claudia Rahmann;Venkataramana Ajjarapu

    (2021)
    983 Citations
  • Microgrid Stability Definitions, Analysis, and Examples

    Mostafa Farrokhabadi;Dimitris Lagos;Richard W. Wies;Mario Paolone

    (2020)
    706 Citations
  • Revisiting Grid-Forming and Grid-Following Inverters: A Duality Theory

    Unknown

    (2021)
    546 Citations
  • Real-World Subsynchronous Oscillation Events in Power Grids With High Penetrations of Inverter-Based Resources

    Unknown

    (2023)
    446 Citations
  • An Enhanced IEEE 33 Bus Benchmark Test System for Distribution System Studies

    Sarineh Hacopian Dolatabadi;Maedeh Ghorbanian;Pierluigi Siano;Nikos D. Hatziargyriou

    (2021)
    372 Citations
  • A Multi-Agent Deep Reinforcement Learning Method for Cooperative Load Frequency Control of a Multi-Area Power System

    Ziming Yan;Yan Xu

    (2020)
    327 Citations
  • Understanding Small-Signal Stability of Low-Inertia Systems

    Uros Markovic;Ognjen Stanojev;Petros Aristidou;Evangelos Vrettos

    (2021)
    287 Citations
  • Using Bayesian Deep Learning to Capture Uncertainty for Residential Net Load Forecasting

    Mingyang Sun;Tingqi Zhang;Yi Wang;Goran Strbac

    (2020)
    187 Citations

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