World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
93
Citations
31533
World Ranking
263
National Ranking
13

Yan Xu publication distribution in Electronics and Electrical Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Electronics and Electrical Engineering in 2026. The highlighted bar marks where Yan Xu sits on this spectrum.

34–53 publications: 24 scientists 54–73 publications: 52 scientists 74–93 publications: 114 scientists 94–113 publications: 203 scientists 114–133 publications: 269 scientists 134–153 publications: 355 scientists 154–173 publications: 403 scientists 174–193 publications: 446 scientists 194–213 publications: 430 scientists 214–233 publications: 431 scientists 234–253 publications: 399 scientists 254–273 publications: 366 scientists 274–293 publications: 335 scientists 294–313 publications: 300 scientists 314–333 publications: 276 scientists 334–353 publications: 250 scientists 354–373 publications: 214 scientists 374–393 publications: 187 scientists 394–413 publications: 152 scientists 414–433 publications: 169 scientists 434–453 publications: 147 scientists 454–473 publications: 111 scientists 474–493 publications: 117 scientists 494–513 publications: 103 scientists 514–533 publications: 99 scientists 534–553 publications: 92 scientists 554–573 publications: 75 scientists 574–593 publications: 58 scientists 594–613 publications: 69 scientists 614–633 publications: 50 scientists 634–653 publications: 62 scientists 654–673 publications: 54 scientists 674–693 publications: 44 scientists 694–713 publications: 37 scientists 714–733 publications: 28 scientists 734–753 publications: 26 scientists 754–773 publications: 26 scientists 774–793 publications: 19 scientists 794–813 publications: 23 scientists 814–833 publications: 20 scientists 834–853 publications: 16 scientists 854–873 publications: 20 scientists 874–893 publications: 11 scientists 894–913 publications: 11 scientists 914–933 publications: 16 scientists 934–953 publications: 13 scientists 954–973 publications: 10 scientists 974–993 publications: 11 scientists 994–1,013 publications: 9 scientists 1,014–1,033 publications: 9 scientists 1,034–1,053 publications: 10 scientists 1,054–1,064 publications: 6 scientists 1,065+ publications: 99 scientists
34 publications 1,065+

This scientist: 664 publications — 93rd percentile

93% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,065 publications or more.

Yan Xu D-index placement in Electronics and Electrical Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Electronics and Electrical Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Yan Xu sits on this spectrum.

30 D-Index: 178 scientists 31 D-Index: 257 scientists 32 D-Index: 263 scientists 33 D-Index: 263 scientists 34 D-Index: 244 scientists 35 D-Index: 236 scientists 36 D-Index: 211 scientists 37 D-Index: 220 scientists 38 D-Index: 214 scientists 39 D-Index: 214 scientists 40 D-Index: 205 scientists 41 D-Index: 187 scientists 42 D-Index: 194 scientists 43 D-Index: 201 scientists 44 D-Index: 155 scientists 45 D-Index: 189 scientists 46 D-Index: 148 scientists 47 D-Index: 160 scientists 48 D-Index: 134 scientists 49 D-Index: 130 scientists 50 D-Index: 141 scientists 51 D-Index: 156 scientists 52 D-Index: 108 scientists 53 D-Index: 130 scientists 54 D-Index: 112 scientists 55 D-Index: 97 scientists 56 D-Index: 111 scientists 57 D-Index: 102 scientists 58 D-Index: 108 scientists 59 D-Index: 120 scientists 60 D-Index: 103 scientists 61 D-Index: 93 scientists 62 D-Index: 92 scientists 63 D-Index: 74 scientists 64 D-Index: 77 scientists 65 D-Index: 73 scientists 66 D-Index: 64 scientists 67 D-Index: 69 scientists 68 D-Index: 60 scientists 69 D-Index: 39 scientists 70 D-Index: 57 scientists 71 D-Index: 59 scientists 72 D-Index: 46 scientists 73 D-Index: 49 scientists 74 D-Index: 38 scientists 75 D-Index: 35 scientists 76 D-Index: 32 scientists 77 D-Index: 35 scientists 78 D-Index: 31 scientists 79 D-Index: 22 scientists 80 D-Index: 34 scientists 81 D-Index: 31 scientists 82 D-Index: 34 scientists 83 D-Index: 23 scientists 84 D-Index: 18 scientists 85 D-Index: 30 scientists 86 D-Index: 19 scientists 87 D-Index: 19 scientists 88 D-Index: 20 scientists 89 D-Index: 8 scientists 90 D-Index: 17 scientists 91 D-Index: 7 scientists 92 D-Index: 14 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 12 scientists 97 D-Index: 10 scientists 98 D-Index: 10 scientists 99 D-Index: 12 scientists 100 D-Index: 16 scientists 101 D-Index: 5 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 8 scientists 105 D-Index: 9 scientists 106 D-Index: 13 scientists 107 D-Index: 4 scientists 108 D-Index: 5 scientists 109 D-Index: 10 scientists 110 D-Index: 8 scientists 111+ D-Index: 96 scientists
30 D-Index 111+

This scientist: 93 D-Index — 96th percentile

96% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 111 D-Index or more.

Overview

Yan Xu is affiliated with Nanyang Technological University in Singapore and specializes in engineering with a focus on electrical and electronic engineering, control and systems engineering, automotive engineering, artificial intelligence, and safety, risk, reliability, and quality.

Their recent research publishes extensively in several key venues, contributing to topics such as microgrid control and optimization, smart grid energy management, optimal power flow distribution, advanced battery technologies research, power system optimization and stability, power system reliability and maintenance, and electric vehicles and infrastructure.

Notable recent papers include:

  • A Multi-Agent Reinforcement Learning-Based Data-Driven Method for Home Energy Management (2020), IEEE Transactions on Smart Grid
  • A Multi-Agent Deep Reinforcement Learning Method for Cooperative Load Frequency Control of a Multi-Area Power System (2020), IEEE Transactions on Power Systems
  • State-of-Health Estimation and Remaining-Useful-Life Prediction for Lithium-Ion Battery Using a Hybrid Data-Driven Method (2020), IEEE Transactions on Vehicular Technology
  • Distributed Resilient Control for Energy Storage Systems in Cyber-Physical Microgrids (2020), IEEE Transactions on Industrial Informatics
  • Hierarchically-Coordinated Voltage/VAR Control of Distribution Networks Using PV Inverters (2020), IEEE Transactions on Smart Grid

Yan Xu frequently collaborates with several co-authors, including Yu Wang, Chao Ren, Zhao Yang Dong, Cuo Zhang, and Zhengmao Li.

The scientist's most common publication venues are:

  • IEEE Transactions on Power Systems
  • IEEE Transactions on Smart Grid
  • International Journal of Electrical Power & Energy Systems
  • arXiv (Cornell University)
  • IEEE Transactions on Industrial Informatics

Yan Xu has also contributed to book publications, such as the work published by the Institution of Engineering and Technology titled "Coordination of Distributed Energy Resources in Microgrids: Optimisation, control, and hardware-in-the-loop validation" (2021).

Best Publications

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

    Weicong Kong;Zhao Yang Dong;Youwei Jia;David J. Hill

  • On an output feedback finite-time stabilisation problem

    Y. Hong;J. Huang;Y. Xu

  • Short-Term Residential Load Forecasting Based on Resident Behaviour Learning

    Weicong Kong;Zhao Yang Dong;David J. Hill;Fengji Luo

  • Electric Vehicle Battery Charging/Swap Stations in Distribution Systems: Comparison Study and Optimal Planning

    Yu Zheng;Zhao Yang Dong;Yan Xu;Ke Meng

  • Bidding Strategy for Microgrid in Day-Ahead Market Based on Hybrid Stochastic/Robust Optimization

    Guodong Liu;Yan Xu;Kevin Tomsovic

  • A Two-Layer Energy Management System for Microgrids With Hybrid Energy Storage Considering Degradation Costs

    Chengquan Ju;Peng Wang;Lalit Goel;Yan Xu

  • A Multi-Objective Collaborative Planning Strategy for Integrated Power Distribution and Electric Vehicle Charging Systems

    Weifeng Yao;Junhua Zhao;Fushuan Wen;Zhaoyang Dong

  • A Multi-Agent Reinforcement Learning-Based Data-Driven Method for Home Energy Management

    Xu Xu;Youwei Jia;Yan Xu;Zhao Xu

  • Data-Driven Load Frequency Control for Stochastic Power Systems: A Deep Reinforcement Learning Method With Continuous Action Search

    Ziming Yan;Yan Xu

  • Electricity Price Forecasting With Extreme Learning Machine and Bootstrapping

    Xia Chen;Zhao Yang Dong;Ke Meng;Yan Xu

  • Optimal coordinated energy dispatch of a multi-energy microgrid in grid-connected and islanded modes

    Zhengmao Li;Yan Xu

  • State-of-Health Estimation and Remaining-Useful-Life Prediction for Lithium-Ion Battery Using a Hybrid Data-Driven Method

    Bin Gou;Yan Xu;Xue Feng

  • A Multi-Agent Deep Reinforcement Learning Method for Cooperative Load Frequency Control of a Multi-Area Power System

    Ziming Yan;Yan Xu

  • Multi-Timescale Coordinated Voltage/Var Control of High Renewable-Penetrated Distribution Systems

    Yan Xu;Zhao Yang Dong;Rui Zhang;David J. Hill

  • Adaptive voltage control with distributed energy resources: Algorithm, theoretical analysis, simulation, and field test verification

    Huijuan Li;Fangxing Li;Yan Xu;D. Tom Rizy

  • Toward Future Green Maritime Transportation: An Overview of Seaport Microgrids and All-Electric Ships

    Sidun Fang;Yu Wang;Bin Gou;Yan Xu

  • Robust Operation of Microgrids via Two-Stage Coordinated Energy Storage and Direct Load Control

    Cuo Zhang;Yan Xu;Zhao Yang Dong;Jin Ma

  • A Reliable Intelligent System for Real-Time Dynamic Security Assessment of Power Systems

    Yan Xu;Zhao Yang Dong;Jun Hua Zhao;Pei Zhang

  • Electric Vehicle Route Optimization Considering Time-of-Use Electricity Price by Learnable Partheno-Genetic Algorithm

    Hongming Yang;Songping Yang;Yan Xu;Erbao Cao

  • Robust Coordination of Distributed Generation and Price-Based Demand Response in Microgrids

    Cuo Zhang;Yan Xu;Zhao Yang Dong;Kit Po Wong

  • Short-term load forecasting of Australian National Electricity Market by an ensemble model of extreme learning machine

    Rui Zhang;Zhao Yang Dong;Yan Xu;Ke Meng

Frequent Co-Authors

Zhao Yang Dong
Zhao Yang Dong City University of Hong Kong
Kit Po Wong
Kit Po Wong University of Western Australia
Ke Meng
Ke Meng University of New South Wales
Junhua Zhao
Junhua Zhao Chinese University of Hong Kong, Shenzhen
Rui Zhang
Rui Zhang National University of Singapore
Yi Tang
Yi Tang Nanyang Technological University
Zhao Xu
Zhao Xu Hong Kong Polytechnic University
Aijun Du
Aijun Du Queensland University of Technology
Qiuwei Wu
Qiuwei Wu Technical University of Denmark
Fushuan Wen
Fushuan Wen Zhejiang University

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