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Wind, Volume 5, Issue 3 (September 2025) – 3 articles

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26 pages, 1033 KiB  
Review
Review of Artificial Intelligence-Based Design Optimization of Wind Power Systems
by Zhihong Jiang, Han Li, Hao Yang, Han Wu, Wenzhou Liu and Zhe Chen
Wind 2025, 5(3), 18; https://doi.org/10.3390/wind5030018 - 11 Jul 2025
Abstract
This paper reviews the applications of artificial intelligence (AI) in the design optimization of wind power systems, mainly including (1) wind farm layout optimization; (2) wind turbine design optimization; and (3) wind farm electrical system design optimization. Firstly, this paper introduces the general [...] Read more.
This paper reviews the applications of artificial intelligence (AI) in the design optimization of wind power systems, mainly including (1) wind farm layout optimization; (2) wind turbine design optimization; and (3) wind farm electrical system design optimization. Firstly, this paper introduces the general considerations in the optimal design of wind power systems and the AI methods commonly used for the optimal design of wind power systems. Then the applications of AI in the optimal design of wind farms are reviewed in detail. Finally, further research directions of using AI methods in the optimal design of wind power systems are recommended. Full article
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31 pages, 5327 KiB  
Article
Wind Estimation Methods for Nearshore Wind Resource Assessment Using High-Resolution WRF and Coastal Onshore Measurements
by Taro Maruo and Teruo Ohsawa
Wind 2025, 5(3), 17; https://doi.org/10.3390/wind5030017 - 7 Jul 2025
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Abstract
Accurate wind resource assessment is essential for offshore wind energy development, particularly in nearshore sites where atmospheric stability and internal boundary layers significantly influence the horizontal wind distribution. In this study, we investigated wind estimation methods using a high-resolution, 100 m grid Weather [...] Read more.
Accurate wind resource assessment is essential for offshore wind energy development, particularly in nearshore sites where atmospheric stability and internal boundary layers significantly influence the horizontal wind distribution. In this study, we investigated wind estimation methods using a high-resolution, 100 m grid Weather Research and Forecasting (WRF) model and coastal onshore wind measurement data. Five estimation methods were evaluated, including a control WRF simulation without on-site measurement data (CTRL), observation nudging (NDG), two offline methods—temporal correction (TC) and the directional extrapolation method (DE)—and direct application of onshore measurement data (DA). Wind speed and direction data from four nearshore sites in Japan were used for validation. The results indicated that TC provided the most accurate wind speed estimate results with minimal bias and relatively high reproducibility of temporal variations. NDG exhibited a smaller standard deviation of bias and a slightly higher correlation with the measured time series than CTRL. DE could not reproduce temporal variations in the horizontal wind speed differences between points. These findings suggest that TC is the most effective method for assessing nearshore wind resources and is thus recommended for practical use. Full article
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30 pages, 2575 KiB  
Review
The Potential of Utility-Scale Hybrid Wind–Solar PV Power Plant Deployment: From the Data to the Results
by Luis Arribas, Javier Domínguez, Michael Borsato, Ana M. Martín, Jorge Navarro, Elena García Bustamante, Luis F. Zarzalejo and Ignacio Cruz
Wind 2025, 5(3), 16; https://doi.org/10.3390/wind5030016 - 7 Jul 2025
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Abstract
The deployment of utility-scale hybrid wind–solar PV power plants is gaining global attention due to their enhanced performance in power systems with high renewable energy penetration. To assess their potential, accurate estimations must be derived from the available data, addressing key challenges such [...] Read more.
The deployment of utility-scale hybrid wind–solar PV power plants is gaining global attention due to their enhanced performance in power systems with high renewable energy penetration. To assess their potential, accurate estimations must be derived from the available data, addressing key challenges such as (1) the spatial and temporal resolution requirements, particularly for renewable resource characterization; (2) energy balances aligned with various business models; (3) regulatory constraints (environmental, technical, etc.); and (4) the cost dependencies of the different components and system characteristics. When conducting such analyses at the regional or national scale, a trade-off must be achieved to balance accuracy with computational efficiency. This study reviews existing experiences in hybrid plant deployment, with a focus on Spain, identifying the lack of national-scale product cost models for HPPs as the main gap and establishing a replicable methodology for hybrid plant mapping. A simplified example is shown using this methodology for a country-level analysis. Full article
(This article belongs to the Topic Solar and Wind Power and Energy Forecasting, 2nd Edition)
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