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Computer Science

D-Index
39
Citations
5326
World Ranking
9876
National Ranking
1241

Overview

Can Wan is affiliated with Zhejiang University in China and specializes in the field of Engineering, with a focus on Electrical and Electronic Engineering, Control and Systems Engineering, and Artificial Intelligence. Their research predominantly revolves around energy systems, smart grids, and power forecasting.

They have contributed extensively to topics such as:

  • Energy Load and Power Forecasting
  • Electric Power System Optimization
  • Optimal Power Flow Distribution
  • Smart Grid Energy Management
  • Microgrid Control and Optimization
  • Integrated Energy Systems Optimization
  • Machine Learning and ELM

Can Wan's publication record includes impactful papers addressing various aspects of power systems and sustainable energy. Selected recent publications include:

  • "Electric Load Clustering in Smart Grid: Methodologies, Applications, and Future Trends," 2021, Journal of Modern Power Systems and Clean Energy
  • "Probabilistic Forecasting Based Sizing and Control of Hybrid Energy Storage for Wind Power Smoothing," 2021, IEEE Transactions on Sustainable Energy
  • "Operating Reserve Quantification Using Prediction Intervals of Wind Power: An Integrated Probabilistic Forecasting and Decision Methodology," 2021, IEEE Transactions on Power Systems
  • "Ensemble Deep Learning-Based Non-Crossing Quantile Regression for Nonparametric Probabilistic Forecasting of Wind Power Generation," 2022, IEEE Transactions on Power Systems
  • "Cost-Oriented Prediction Intervals: On Bridging the Gap Between Forecasting and Decision," 2021, IEEE Transactions on Power Systems

Their work is mostly published in venues such as:

  • IEEE Transactions on Power Systems
  • IEEE Transactions on Smart Grid
  • IEEE Transactions on Sustainable Energy
  • 2022 IEEE Power & Energy Society General Meeting (PESGM)
  • arXiv (Cornell University)

Frequent collaborators include:

  • Yonghua Song
  • Ping Ju
  • Changfei Zhao
  • Peng Yu
  • Hui Liu

Through their research, Can Wan contributes to methodologies and applications related to smart grids, hybrid energy storage, probabilistic forecasting, and power system optimization, intersecting energy engineering with computational intelligence techniques.

Best Publications

  • Probabilistic Forecasting of Wind Power Generation Using Extreme Learning Machine

    Can Wan;Zhao Xu;Pierre Pinson;Zhao Yang Dong

  • Optimal Prediction Intervals of Wind Power Generation

    Can Wan;Zhao Xu;Pierre Pinson;Zhao Yang Dong

  • Direct Quantile Regression for Nonparametric Probabilistic Forecasting of Wind Power Generation

    Can Wan;Jin Lin;Jianhui Wang;Yonghua Song

  • A Hybrid Approach for Probabilistic Forecasting of Electricity Price

    Can Wan;Zhao Xu;Yelei Wang;Zhao Yang Dong

  • Probabilistic Forecasting of Photovoltaic Generation: An Efficient Statistical Approach

    Can Wan;Jin Lin;Yonghua Song;Zhao Xu

  • Optimal Cloud Computing Resource Allocation for Demand Side Management in Smart Grid

    Zijian Cao;Jin Lin;Can Wan;Yonghua Song

  • A Multi-Model Combination Approach for Probabilistic Wind Power Forecasting

    You Lin;Ming Yang;Can Wan;Jianhui Wang

  • A Multistage Home Energy Management System With Residential Photovoltaic Penetration

    Fengji Luo;Gianluca Ranzi;Can Wan;Zhao Xu

  • Risk-Based Day-Ahead Scheduling of Electric Vehicle Aggregator Using Information Gap Decision Theory

    Jian Zhao;Can Wan;Zhao Xu;Jianhui Wang

  • Direct Interval Forecasting of Wind Power

    Can Wan;Zhao Xu;Pierre Pinson

  • A review on applications of heuristic optimization algorithms for optimal power flow in modern power systems

    Ming Niu;Can Wan;Zhao Xu

  • Distribution Network Electric Vehicle Hosting Capacity Maximization: A Chargeable Region Optimization Model

    Jian Zhao;Jianhui Wang;Zhao Xu;Cheng Wang

  • Hybrid Ensemble Deep Learning for Deterministic and Probabilistic Low-Voltage Load Forecasting

    Zhaojing Cao;Can Wan;Zijun Zhang;Furong Li

  • Battery ESS Planning for Wind Smoothing via Variable-Interval Reference Modulation and Self-Adaptive SOC Control Strategy

    Feng Zhang;Ke Meng;Zhao Xu;Zhaoyang Dong

  • Electric Load Clustering in Smart Grid: Methodologies, Applications, and Future Trends

    Caomingzhe Si;Shenglan Xu;Can Wan;Dawei Chen

  • Probabilistic Forecasting Based Sizing and Control of Hybrid Energy Storage for Wind Power Smoothing

    Can Wan;Weiting Qian;Changfei Zhao;Yonghua Song

  • Stochastic Receding Horizon Control of Active Distribution Networks With Distributed Renewables

    Yibao Jiang;Can Wan;Jianhui Wang;Yonghua Song

  • A Fully Distributed Hierarchical Control Framework for Coordinated Operation of DERs in Active Distribution Power Networks

    Shiwei Xia;Siqi Bu;Can Wan;Xi Lu

  • Operating Reserve Quantification Using Prediction Intervals of Wind Power: An Integrated Probabilistic Forecasting and Decision Methodology

    Changfei Zhao;Can Wan;Yonghua Song

  • A Hybrid Stochastic-Interval Operation Strategy for Multi-Energy Microgrids

    Yibao Jiang;Can Wan;Chen Chen;Mohammad Shahidehpour

  • Pareto Optimal Prediction Intervals of Electricity Price

    Can Wan;Ming Niu;Yonghua Song;Zhao Xu

  • Nonparametric Prediction Intervals of Wind Power via Linear Programming

    Can Wan;Jianhui Wang;Jin Lin;Yonghua Song

Frequent Co-Authors

Yonghua Song
Yonghua Song University of Macau
Zhao Xu
Zhao Xu Hong Kong Polytechnic University
Zhao Yang Dong
Zhao Yang Dong City University of Hong Kong
Kit Po Wong
Kit Po Wong University of Western Australia
Fengji Luo
Fengji Luo University of Sydney
Mohammad Shahidehpour
Mohammad Shahidehpour Illinois Institute of Technology
Jianhui Wang
Jianhui Wang Southern Methodist University
Guangya Yang
Guangya Yang Technical University of Denmark
Ke Meng
Ke Meng University of New South Wales

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