Progress and Challenges in Wind Farm Optimization
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 (27 January 2026) | Viewed by 3926
Special Issue Editors
Interests: control; wind turbines/farms; condition monitoring; modeling; estimation; prediction; neural network
Interests: wind farm flow analysis; wake modeling and optimization; wind farm layout optimization; wind farm power forecasting; time series data prediction; wind turbine noise propagation analysis; wind noise testing and evaluation; low-frequency noise propagation modeling
Special Issue Information
Dear Colleagues,
During the past few decades, wind energy has emerged as one of the most significant and rapidly growing renewable energy sources. However, optimizing wind farms’ performance and cost-effectiveness remains a critical challenge due to complex factors such as wake interactions, variability in wind resources, and environmental constraints.
This Special Issue will explore cutting-edge advancements in wind farm optimization, focusing on layout design, operational strategies, predictive maintenance, and the integration of emerging technologies such as machine learning and artificial intelligence. Key areas of interest include optimizing wind farm layouts to maximize power output, mitigating wake effects, minimizing operational costs, and enhancing grid integration. Additionally, innovative approaches to environmental impact reduction, such as noise minimization and ecological considerations, will be addressed.
The topics of interest for publication include, but are not limited to, the following:
- Wind farm layout optimization;
- Operational and control strategies;
- Predictive maintenance and cost reduction;
- Wake effect modeling and mitigation;
- Integration of wind energy with hybrid systems;
- Machine learning and AI applications in optimization;
- Environmental impact assessments and mitigation.
Through this Special Issue, we will advance the state-of-the-art in wind farm optimization, providing valuable insights for researchers, industry professionals, and policymakers dedicated to the future of wind energy.
Prof. Dr. Sung-ho Hur
Dr. Eunkuk Son
Guest Editors
Manuscript Submission Information
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Keywords
- wind farm optimization
- wake effect mitigation
- layout design
- predictive maintenance
- machine learning
- artificial intelligence
- operational strategies
- environmental impact
- grid integration
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