World's Best Scientists 2026 revealed!
Ricardo J. Bessa

Ricardo J. Bessa

D-Index & Metrics

Engineering and Technology

D-Index
44
Citations
8480
World Ranking
5757
National Ranking
30

Ricardo J. Bessa publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Ricardo J. Bessa sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 157 publications — 30th percentile

30% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Ricardo J. Bessa D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Ricardo J. Bessa sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 44 D-Index — 42nd percentile

42% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Ricardo J. Bessa is a researcher affiliated with the University of Porto in Portugal, with a specialization in engineering and a focus on electrical and electronic engineering. Their research encompasses areas such as control and systems engineering, artificial intelligence, safety, risk, reliability and quality, and renewable energy, sustainability and the environment.

Their work prominently addresses topics related to smart grid energy management, energy load and power forecasting, electric power system optimization, smart grid security and resilience, optimal power flow distribution, power system reliability and maintenance, and anomaly detection techniques and applications.

Recent publications by Ricardo J. Bessa include:

  • Forecasting: theory and practice, 2022, BOA (University of Milano-Bicocca)
  • Big data analytics for future electricity grids, 2020, Electric Power Systems Research
  • Towards Data Markets in Renewable Energy Forecasting, 2020, IEEE Transactions on Sustainable Energy
  • Privacy-Preserving Distributed Learning for Renewable Energy Forecasting, 2021, IEEE Transactions on Sustainable Energy
  • A review on the decarbonization of high-performance computing centers, 2023, Renewable and Sustainable Energy Reviews

Frequent co-authors collaborating with Bessa include:

  • Clara Gouveia
  • Pierre Pinson
  • Georges Kariniotakis
  • Gil Sampaio
  • Carla Gonçalves

The researcher has contributed extensively to publications in venues such as:

  • IET conference proceedings.
  • arXiv (Cornell University)
  • Electric Power Systems Research
  • IEEE Transactions on Sustainable Energy
  • Zenodo (CERN European Organization for Nuclear Research)

Their main areas of study include engineering with a significant number of publications in electrical and electronic engineering, reflecting a broad engagement with multiple subfields and interdisciplinary topics relating to energy systems and sustainability.

Best Publications

  • Wind power forecasting : state-of-the-art 2009.

    C. Monteiro;R. Bessa;V. Miranda;A. Botterud

  • Wind power forecasting uncertainty and unit commitment

    J. Wang;A. Botterud;R. Bessa;H. Keko

  • Methodologies to Determine Operating Reserves Due to Increased Wind Power

    H. Holttinen;M. Milligan;E. Ela;N. Menemenlis

  • Setting the Operating Reserve Using Probabilistic Wind Power Forecasts

    M A Matos;R J Bessa

  • Flexibility products and markets: Literature review

    José Villar;Ricardo Jorge Bessa;Manuel Matos

  • Optimized Bidding of a EV Aggregation Agent in the Electricity Market

    R. J. Bessa;M. A. Matos;F. J. Soares;J. A. P. Lopes

  • Economic and technical management of an aggregation agent for electric vehicles: a literature survey

    Ricardo J. Bessa;Manuel A. Matos

  • Improving Renewable Energy Forecasting With a Grid of Numerical Weather Predictions

    Jose R. Andrade;Ricardo J. Bessa

  • Estimating the Active and Reactive Power Flexibility Area at the TSO-DSO Interface

    Joao Silva;Jean Sumaili;Ricardo J. Bessa;Luis Seca

  • The future of forecasting for renewable energy

    Conor Sweeney;Ricardo J. Bessa;Jethro Browell;Pierre Pinson

  • Entropy and Correntropy Against Minimum Square Error in Offline and Online Three-Day Ahead Wind Power Forecasting

    R.J. Bessa;V. Miranda;J. Gama

  • Wind Power Trading Under Uncertainty in LMP Markets

    A. Botterud;Zhi Zhou;Jianhui Wang;R. J. Bessa

  • Time-adaptive quantile-copula for wind power probabilistic forecasting

    Ricardo J. Bessa;V. Miranda;A. Botterud;Z. Zhou

  • Methodologies to determine operating reserves due to increased wind power

    Hannele Holttinen;Michael Milligan;Erik Ela;Nickie Menemenlis

  • Comparison of two new short-term wind-power forecasting systems

    Ignacio J. Ramirez-Rosado;L. Alfredo Fernandez-Jimenez;Cláudio Monteiro;João Sousa

  • Time Adaptive Conditional Kernel Density Estimation for Wind Power Forecasting

    R. J. Bessa;V. Miranda;A. Botterud;Jianhui Wang

  • Demand Dispatch and Probabilistic Wind Power Forecasting in Unit Commitment and Economic Dispatch: A Case Study of Illinois

    A. Botterud;Zhi Zhou;Jianhui Wang;J. Sumaili

  • Spatial-Temporal Solar Power Forecasting for Smart Grids

    Ricardo J. Bessa;Artur Trindade;Vladimiro Miranda

  • Probabilistic solar power forecasting in smart grids using distributed information

    R.J. Bessa;A. Trindade;Cátia S.P. Silva;V. Miranda

  • Optimization Models for EV Aggregator Participation in a Manual Reserve Market

    Ricardo J. Bessa;Manuel A. Matos

Frequent Co-Authors

Manuel A. Matos
Manuel A. Matos University of Porto
Vladimiro Miranda
Vladimiro Miranda University of Porto
Pierre Pinson
Pierre Pinson Technical University of Denmark
Georges Kariniotakis
Georges Kariniotakis Mines ParisTech
João Gama
João Gama University of Porto
William J. Shaw
William J. Shaw Pacific Northwest National Laboratory
João Peças Lopes
João Peças Lopes University of Porto
Michael Milligan
Michael Milligan National Renewable Energy Laboratory

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