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Latest Scientific Developments in Wind Power

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A3: Wind, Wave and Tidal Energy".

Deadline for manuscript submissions: closed (25 March 2026) | Viewed by 1705

Special Issue Editors

School of Renewable Energy, Hohai University, Changzhou 213200, China
Interests: wind turbine aerodynamics; wind farm control; marine current energy; turbulent flow; floating wind turbine; wind tunnel experiment; hydropower and pump station

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Guest Editor
College of Energy and Power Engineering, Lanzhou University of Technology, Lanzhou 730050, China
Interests: wind turbine aerodynamics; wind turbine wakes simulation
State Key Laboratory of Clean Energy Utilization, Zhejiang University, Hangzhou 310058, China
Interests: mesoscale and microscale simulations of onshore or offshore wind farms; wind power forecasting; machine learning; climatic and pollutant impacts of wind power

Special Issue Information

Dear Colleagues,

Wind power, as a clean and renewable energy source, has made tremendous strides over the past decades, playing a crucial role in addressing climate change, ensuring energy supply, and fostering social and economic development. The historic global consensus at COP28 reached to triple renewable energy by 2030, aimed at accelerating the transition towards a sustainable energy system, further underscoring the promising future of wind power. However, we are also keenly aware of the multifaceted challenges that lie ahead. These include the complexity and restriction of development scenarios, the stability of new power grids, the safety and reliability of large-scale turbines, severe inflation, shrinking investment benefits, and the pressing need for environmental friendliness. These challenges necessitate innovative solutions and advancements in wind power technology.

In light of this, we are delighted to announce this Special Issue which aims to showcase the latest scientific developments in the field of wind power, covering theory, design, application, modeling, testing, forecasting, monitoring, operations and maintenance, and more. By bringing together researchers, engineers, and policymakers, we aim to provide a holistic view of the current landscape and future directions of wind power.

In this Special Issue, original research articles and reviews are welcome. Topics of interest for publication include, but are not limited to, the following:

  • Wind resource assessment and utilization.
  • Wake evolution, modeling and mitigation.
  • Advances in micro-siting of wind farms and their environmental impacts.
  • Novel control strategies for wind turbines and wind farms.
  • Floating wind turbine.
  • Structural reliability and durability of wind turbines. 
  • Wind power forecasting, testing, and performance evaluation.
  • Innovations in wind turbine design, materials, and manufacturing process.
  • Artificial intelligence and machine learning applications in wind power.
  • “Offshore wind power +”multi-industry integration and synergies.
  • Wind power drive, generator, and transmission systems.
  • Wind farm operations, maintenance, and life-cycle management.
  • Policy frameworks and economic analysis in wind power development.

Dr. Huiwen Liu
Dr. Yan Wang
Dr. Qiang Wang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • wind resource
  • wind turbine
  • wind farm control
  • wind power
  • aerodynamics
  • floating wind turbine
  • artificial intelligence
  • power forecasting
  • structural response
  • operations and maintenance

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Published Papers (1 paper)

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Review

36 pages, 4112 KB  
Review
Review on Dynamic Inflow Sensing Layout Optimization for Large-Scale Wind Farms: Wake Modeling, Data-Driven Prediction, and Multi-Objective Uncertainty Optimization
by Rongzhe Yang, Tenggang Cui, Zhenman Chen, Shijin Ma, Hongrui Ping, Fulong Wei, Zhenbo Gao, Guanlin Lu, Huiwen Liu and Lidong Zhang
Energies 2026, 19(3), 810; https://doi.org/10.3390/en19030810 - 4 Feb 2026
Cited by 1 | Viewed by 855
Abstract
Large-scale wind farms operate under highly unsteady atmospheric inflows, where transient turbulence, dynamic wake interactions, and inflow-wake coupling reduce energy production and exacerbate turbine loads. Over the past five years, advances in high-fidelity computational fluid dynamics (CFDs), large eddy simulation (LES), machine learning [...] Read more.
Large-scale wind farms operate under highly unsteady atmospheric inflows, where transient turbulence, dynamic wake interactions, and inflow-wake coupling reduce energy production and exacerbate turbine loads. Over the past five years, advances in high-fidelity computational fluid dynamics (CFDs), large eddy simulation (LES), machine learning (ML)-based wake modeling, and multi-objective optimization have reshaped wind farm layout optimization under dynamic inflow conditions. This review synthesizes recent progress in five key areas: dynamic inflow and high-fidelity wake modeling (including LES-driven transient wake evolution and turbulence-resolved inflow generation), data-driven wake prediction, multi-objective layout optimization (considering the annual energy production (AEP), fatigue load constraints, and the levelized cost of energy (LCOE)), blockage modeling for complex terrain and yaw misalignment, and real-time optimization addressing inflow, turbine performance, and modeling uncertainties. Coupling transient wake models with surrogate-assisted multi-objective optimization enables a computationally efficient and physically consistent layout design. Key open challenges (dynamic wake controllability, real-time optimization under uncertainty, and integration with next-generation farm-level control systems) and future directions for enhancing large-scale wind farm resilience and cost-competitiveness are also identified. However, despite significant progress, existing models still face fundamental limitations, such as oversimplified treatment of complex turbulence structures, poor generalization under extreme or atypical conditions, and inadequate capture of long-timescale dynamic responses, which constrain their reliability in practical optimization settings. Full article
(This article belongs to the Special Issue Latest Scientific Developments in Wind Power)
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