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Weihao Hu
Researcher at University of Electronic Science and Technology of China
Publications - 383
Citations - 5660
Weihao Hu is an academic researcher from University of Electronic Science and Technology of China. The author has contributed to research in topics: Wind power & Electric power system. The author has an hindex of 28, co-authored 312 publications receiving 3213 citations. Previous affiliations of Weihao Hu include Aalborg University & Southeast University.
Papers
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Reinforcement Learning and Its Applications in Modern Power and Energy Systems: A Review
TL;DR: This paper provides a comprehensive literature review of RL in terms of basic ideas, various types of algorithms, and their applications in power and energy systems.
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Optimized sizing of a standalone PV-wind-hydropower station with pumped-storage installation hybrid energy system
TL;DR: In this article, a photovoltaics (PV)-wind-hydropower station with pumped-storage installation (HSPSI) hybrid energy system in Xiaojin, Sichuan, China was designed and investigated.
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A Heuristic Planning Reinforcement Learning-Based Energy Management for Power-Split Plug-in Hybrid Electric Vehicles
TL;DR: This paper proposes a heuristic planning energy management controller, based on a Dyna agent of reinforcement learning approach, for real-time fuel saving optimization of a plug-in hybrid electric vehicle (PHEV).
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Optimized Placement of Wind Turbines in Large-Scale Offshore Wind Farm Using Particle Swarm Optimization Algorithm
TL;DR: In this paper, a particle swarm optimization (PSO) algorithm was used to find the optimized layout, which minimizes the levelized production cost (LPC) objective function.
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Optimal Operation of Plug-In Electric Vehicles in Power Systems With High Wind Power Penetrations
TL;DR: In this article, the integration of plug-in electric vehicles in the power systems with high wind power penetrations is proposed and discussed, and the optimal operation strategies of PEVs in the spot market are proposed in order to decrease the energy cost for PEV owners.