Articles | Volume 6, issue 2
https://doi.org/10.5194/wes-6-311-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-6-311-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
An overview of wind-energy-production prediction bias, losses, and uncertainties
Joseph C. Y. Lee
National Wind Technology Center, National Renewable Energy Laboratory,
Golden, CO 80401, USA
M. Jason Fields
CORRESPONDING AUTHOR
National Wind Technology Center, National Renewable Energy Laboratory,
Golden, CO 80401, USA
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- Experimental investigation of blade tip vortex behavior in the wake of asymmetric rotors A. Abraham & T. Leweke 10.1007/s00348-023-03646-3
- Numerical investigation of rotor asymmetry to promote wake recovery A. Abraham et al. 10.1088/1742-6596/2505/1/012032
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- A New Decision Process for Choosing the Wind Resource Assessment Workflow with the Best Compromise between Accuracy and Costs for a Given Project in Complex Terrain S. Barber et al. 10.3390/en15031110
- Evaluating wind speed and power forecasts for wind energy applications using an open-source and systematic validation framework J. Lee et al. 10.1016/j.renene.2022.09.111
- Characterization of wind turbine flow through nacelle-mounted lidars: a review S. Letizia et al. 10.3389/fmech.2023.1261017
- Multi-fidelity vortex simulations of rotor flows: Validation against detailed wake measurements N. Ramos-García et al. 10.1016/j.compfluid.2023.105790
- Investigating the physical mechanisms that modify wind plant blockage in stable boundary layers M. Sanchez Gomez et al. 10.5194/wes-8-1049-2023
- Numerical investigation of the vortical structures in the near wake of a model wind turbine T. Weislein et al. 10.1088/1742-6596/2767/2/022008
- Exploring cooperation between wind farms: a wake steering optimization study of the Belgian offshore wind farm cluster B. Foloppe et al. 10.1088/1742-6596/2505/1/012055
- Analysis of the systematic errors of energy yield assessment in the context of wind farm repowering P. Mazoyer et al. 10.1088/1742-6596/2507/1/012016
- Evaluation and Comparison of Different Methods for Improving Fault Ride-Through Capability in Grid-Tied Permanent Magnet Synchronous Wind Generators M. Mahmoud et al. 10.1155/2023/7717070
- Machine learning for predicting offshore vertical wind profiles F. Rouholahnejad et al. 10.1088/1742-6596/2626/1/012023
- Effect of pitch on nonlinear dynamics of helical vortex disturbed by long-wave instability Y. Hattori & A. Hirano 10.1017/jfm.2024.529
- Uncovering wind power forecasting uncertainty sources and their propagation through the whole modelling chain J. Yan et al. 10.1016/j.rser.2022.112519
- A three-dimensional, analytical wind turbine wake model: Flow acceleration, empirical correlations, and continuity Z. Sadek et al. 10.1016/j.renene.2023.03.129
- Wind power production from very large offshore wind farms S. Pryor et al. 10.1016/j.joule.2021.09.002
- Materials and systems for polymer-based Metallocene batteries: Status and challenges S. Beladi-Mousavi & L. Walder 10.1016/j.polymer.2022.124658
- The wind farm as a sensor: learning and explaining orographic and plant-induced flow heterogeneities from operational data R. Braunbehrens et al. 10.5194/wes-8-691-2023
- Exploring the Interdependence of Vertical Extrapolation Uncertainties in Repowering Wind Farms P. Mazoyer et al. 10.1088/1742-6596/2767/9/092009
- Offshore wind power system economic evaluation framework under aleatory and epistemic uncertainty A. Caputo et al. 10.1016/j.apenergy.2023.121585
- Can mesoscale models capture the effect from cluster wakes offshore? M. Gomez et al. 10.1088/1742-6596/2767/6/062013
- A Dependability Neural Network Approach for Short-Term Production Estimation of a Wind Power Plant F. Famoso et al. 10.3390/en17071627
- Prediction of hourly wind speed time series at unsampled locations using machine learning F. Houndekindo & T. Ouarda 10.1016/j.energy.2024.131518
- Optimization and control strategy for wind turbine aerodynamic performance under uncertainties H. Tian et al. 10.1063/5.0167442
- Uncertainty Quantification for an Automatised RANS-Based Wind Resource Assessment Approach S. Remmler et al. 10.1088/1742-6596/2767/9/092007
- Sensitivity of multiscale large Eddy simulations for wind power calculations in complex terrain G. De Moliner et al. 10.1016/j.apenergy.2024.123195
- Evaluating Wind Speed and Power Forecasts for Wind Energy Applications Using an Open-Source and Systematic Validation Framework J. Lee et al. 10.2139/ssrn.4064500
- Using Observed and Modelled Heat Fluxes for Improved Extrapolation of Wind Distributions R. Floors et al. 10.1007/s10546-023-00803-3
- Overview of recent observations and simulations from the American WAKE experimeNt (AWAKEN) field campaign P. Moriarty et al. 10.1088/1742-6596/2505/1/012049
- Characterization of atmospheric coherent structures and their impact on a utility-scale wind turbine A. Abraham & J. Hong 10.1017/flo.2021.20
- Seasonal variability of wake impacts on US mid-Atlantic offshore wind plant power production D. Rosencrans et al. 10.5194/wes-9-555-2024
- Overview of preparation for the American WAKE ExperimeNt (AWAKEN) P. Moriarty et al. 10.1063/5.0141683
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- Grand challenges in the design, manufacture, and operation of future wind turbine systems P. Veers et al. 10.5194/wes-8-1071-2023
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Latest update: 22 Nov 2024
Short summary
This review paper evaluates the energy prediction bias in the wind resource assessment process, and the overprediction bias is decreasing over time. We examine the estimated and observed losses and uncertainties in energy production from the literature, according to the proposed framework in the International Electrotechnical Commission 61400-15 standard. The considerable uncertainties call for further improvements in the prediction methodologies and more observations for validation.
This review paper evaluates the energy prediction bias in the wind resource assessment process,...
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