World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
64
Citations
12338
World Ranking
1695
National Ranking
336

Overview

Weihao Hu is affiliated with the University of Electronic Science and Technology of China, located in China. Their research primarily focuses on the field of Engineering, with substantial contributions to Electrical and Electronic Engineering, Control and Systems Engineering, and Energy Engineering and Power Technology.

The scientist's work spans several subfields, including Electrical and Electronic Engineering, Control and Systems Engineering, Energy Engineering and Power Technology, Mechanical Engineering, and Automotive Engineering. Their research addresses a variety of topics such as Smart Grid Energy Management, Microgrid Control and Optimization, Optimal Power Flow Distribution, Integrated Energy Systems Optimization, Energy Load and Power Forecasting, Hybrid Renewable Energy Systems, and Electric Vehicles and Infrastructure.

Weihao Hu has contributed numerous publications across a variety of respected venues in the energy and power domain. Frequent publication venues include:

  • Renewable Energy
  • Applied Energy
  • IEEE Transactions on Power Systems
  • Energy Reports
  • SSRN Electronic Journal

Their recent papers feature collaborations with co-authors such as Zhe Chen, Qi Huang, Di Cao, Frede Blaabjerg, and Zhenyuan Zhang. Notable recent publications include:

  • Reinforcement Learning and Its Applications in Modern Power and Energy Systems: A Review, 2020, Journal of Modern Power Systems and Clean Energy
  • A Novel Hybrid Short-Term Load Forecasting Method of Smart Grid Using MLR and LSTM Neural Network, 2020, IEEE Transactions on Industrial Informatics
  • A Multi-Agent Deep Reinforcement Learning Based Voltage Regulation Using Coordinated PV Inverters, 2020, IEEE Transactions on Power Systems
  • Data-Driven Multi-Agent Deep Reinforcement Learning for Distribution System Decentralized Voltage Control With High Penetration of PVs, 2021, IEEE Transactions on Smart Grid
  • Deep Reinforcement Learning Enabled Physical-Model-Free Two-Timescale Voltage Control Method for Active Distribution Systems, 2021, IEEE Transactions on Smart Grid

In addition to journal articles, Weihao Hu has published work in book form. One of the books listed is Planning and Operation of Hybrid Renewable Energy Systems, published by Frontiers Media in 2022.

Best Publications

  • Reinforcement Learning and Its Applications in Modern Power and Energy Systems: A Review

    Di Cao;Weihao Hu;Junbo Zhao;Guozhou Zhang

  • Optimized sizing of a standalone PV-wind-hydropower station with pumped-storage installation hybrid energy system

    Xiao Xu;Weihao Hu;Di Cao;Qi Huang

  • A Novel Hybrid Short-Term Load Forecasting Method of Smart Grid Using MLR and LSTM Neural Network

    Jian Li;Daiyu Deng;Junbo Zhao;Dongsheng Cai

  • A Multi-Agent Deep Reinforcement Learning Based Voltage Regulation Using Coordinated PV Inverters

    Di Cao;Weihao Hu;Junbo Zhao;Qi Huang

  • Optimizing investments in coupled offshore wind -electrolytic hydrogen storage systems in Denmark

    Peng Hou;Peter Enevoldsen;Joshua Eichman;Weihao Hu

  • A Heuristic Planning Reinforcement Learning-Based Energy Management for Power-Split Plug-in Hybrid Electric Vehicles

    Teng Liu;Xiaosong Hu;Weihao Hu;Yuan Zou

  • Optimized Placement of Wind Turbines in Large-Scale Offshore Wind Farm Using Particle Swarm Optimization Algorithm

    Peng Hou;Weihao Hu;Mohsen Soltani;Zhe Chen

  • Investigation of wind speed cooling effect on PV panels in windy locations

    Nuri Gökmen;Weihao Hu;Peng Hou;Zhe Chen

  • Flicker Mitigation by Active Power Control of Variable-Speed Wind Turbines With Full-Scale Back-to-Back Power Converters

    Weihao Hu;Zhe Chen;Yue Wang;Zhaoan Wang

  • A Meta-Learning Method for Electric Machine Bearing Fault Diagnosis Under Varying Working Conditions With Limited Data

    Unknown

  • Optimal Operation of Plug-In Electric Vehicles in Power Systems With High Wind Power Penetrations

    Weihao Hu;Chi Su;Zhe Chen;Birgitte Bak-Jensen

  • Data-Driven Multi-Agent Deep Reinforcement Learning for Distribution System Decentralized Voltage Control With High Penetration of PVs

    Di Cao;Junbo Zhao;Weihao Hu;Fei Ding

  • A review of offshore wind farm layout optimization and electrical system design methods

    Peng Hou;Jiangsheng Zhu;Kuichao Ma;Guangya Yang

  • Optimal operation strategy of battery energy storage system to real-time electricity price in Denmark

    Weihao Hu;Zhe Chen;Birgitte Bak-Jensen

  • Deep Reinforcement Learning Enabled Physical-Model-Free Two-Timescale Voltage Control Method for Active Distribution Systems

    Di Cao;Junbo Zhao;Weihao Hu;Nanpeng Yu

  • Attention Enabled Multi-Agent DRL for Decentralized Volt-VAR Control of Active Distribution System Using PV Inverters and SVCs

    Di Cao;Junbo Zhao;Weihao Hu;Fei Ding

  • Deep reinforcement learning–based approach for optimizing energy conversion in integrated electrical and heating system with renewable energy

    Bin Zhang;Weihao Hu;Di Cao;Qi Huang

  • Soft actor-critic –based multi-objective optimized energy conversion and management strategy for integrated energy systems with renewable energy

    Bin Zhang;Weihao Hu;Di Cao;Tao Li

  • Reinforcement Learning Based Efficiency Optimization Scheme for the DAB DC–DC Converter With Triple-Phase-Shift Modulation

    Yuanhong Tang;Weihao Hu;Jian Xiao;Zhangyong Chen

  • Dynamic energy conversion and management strategy for an integrated electricity and natural gas system with renewable energy: Deep reinforcement learning approach

    Bin Zhang;Weihao Hu;Jinghua Li;Di Cao

  • Electric vehicles and large-scale integration of wind power – The case of Inner Mongolia in China

    Wen Liu;Weihao Hu;Henrik Lund;Zhe Chen

  • Combined optimization for offshore wind turbine micro siting

    Peng Hou;Weihao Hu;Mohsen N. Soltani;Cong Chen

  • A Reactive Power Dispatch Strategy With Loss Minimization for a DFIG-Based Wind Farm

    Baohua Zhang;Peng Hou;Weihao Hu;Mohsen Soltani

  • Comprehensive Cost Minimization in Distribution Networks Using Segmented-Time Feeder Reconfiguration and Reactive Power Control of Distributed Generators

    Shuheng Chen;Weihao Hu;Zhe Chen

  • Flicker Mitigation by Individual Pitch Control of Variable Speed Wind Turbines With DFIG

    Yunqian Zhang;Zhe Chen;Weihao Hu;Ming Cheng

  • Data-driven optimal energy management for a wind-solar-diesel-battery-reverse osmosis hybrid energy system using a deep reinforcement learning approach

    Guozhou Zhang;Weihao Hu;Di Cao;Wen Liu

Frequent Co-Authors

Zhe Chen
Zhe Chen Aalborg University
Junbo Zhao
Junbo Zhao University of Connecticut
Birgitte Bak-Jensen
Birgitte Bak-Jensen Aalborg University
Frede Blaabjerg
Frede Blaabjerg Aalborg University
Jiakun Fang
Jiakun Fang Huazhong University of Science and Technology
Henrik Lund
Henrik Lund Aalborg University
Ming Cheng
Ming Cheng Southeast University
Mark Z. Jacobson
Mark Z. Jacobson Stanford University
Guangya Yang
Guangya Yang Technical University of Denmark
Weirong Chen
Weirong Chen Southwest Jiaotong University

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