scholarly journals Development of a High-Resolution Wind Forecast System Based on the WRF Model and a Hybrid Kalman-Bayesian Filter

Energies ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 3050 ◽  
Author(s):  
Carlos Otero-Casal ◽  
Platon Patlakas ◽  
Miguel A. Prósper ◽  
George Galanis ◽  
Gonzalo Miguez-Macho
Keyword(s):  
Wind Speed ◽  
Wind Farm ◽  
Wrf Model ◽  
Statistical Error ◽  
Atmospheric Model ◽  
Horizontal Resolution ◽  
Integrated System ◽  
Combined System ◽  
Local Flow ◽  
Bayesian Filter

Regional microscale meteorological models have become a critical tool for wind farm production forecasting due to their capacity for resolving local flow dynamics. The high demand for reliable forecasting tools in the energy industry is the motivation for the development of an integrated system that combines the Weather Research and Forecasting (WRF) atmospheric model with an optimization obtained by the conjunction of a Kalman filter and a Bayesian model. This study focuses on the development and validation of this combined system in a very dense wind farm cluster located in Galicia (Northwest of Spain). A period of one year is simulated at 333 m horizontal resolution, with a daily operational forecasting set-up. The Kalman-Bayesian filter was tested both directly on wind speed and on the U-V (zonal and meridional) components for nowcasting periods from 10 min to 6 h periods, all of them with important applications in the wind industry. The results are quite promising, as the main statistical error indices are significantly improved in a 6 h forecasting horizon and even more in shorter horizon cases. The Mean Annual Error (MAE) for 1 h nowcasting horizon is 1.03 m/s for wind speed and 12.16 ° for wind direction. Moreover, the successful utilization of the integrated system in test cases with different characteristics demonstrates the potential utility that this tool may have for a variety of applications in wind farm operations and energy markets.

scholarly journals Idealized WRF model sensitivity simulations of sea breeze types and their effects on offshore windfields

2012 ◽  
Vol 12 (6) ◽  
pp. 15837-15881 ◽  
Author(s):  
C. J. Steele ◽  
S. R. Dorling ◽  
R. von Glasow ◽  
J. Bacon
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Farm ◽  
Wrf Model ◽  
Sea Breeze ◽  
Offshore Wind ◽  
Eastern Coast ◽  
State University ◽  
Sea Breezes ◽  
Gradient Wind

Abstract. The behaviour and characteristics of the marine component of sea breeze cells have received little attention relative to their onshore counterparts. Yet there is a growing interest and dependence on the offshore wind climate from, for example, a wind energy perspective. Using idealized model experiments, we investigate the sea breeze circulation at scales which approximate to those of the Southern North Sea, a region of major ongoing offshore wind farm development. We also contrast the scales and characteristics of the pure and the little known corkscrew and backdoor sea breeze types, where the type is pre-defined by the orientation of the synoptic scale flow relative to the shoreline. We find, crucially, that pure sea breezes, in contrast to corkscrew and backdoor types, can lead to substantial wind speed reductions offshore and that the addition of a second eastern coastline emphasises this effect through generation of offshore "calm zones". The offshore extent of all sea breeze types is found to be sensitive to both the influence of Coriolis acceleration and to the boundary layer scheme selected. These extents range, for example for a pure sea breeze produced in a 2 m s−1 offshore gradient wind, from 10 km to 40 km between the Mellor-Yamada-Nakanishi-Niino and the Yonsei State University schemes, respectively. The corkscrew type restricts the development of a backdoor sea breeze on the eastern coast and is also capable of traversing a 100 km offshore domain even under high gradient wind speed (>15 m s−1) conditions. Realistic variations in sea surface skin temperature during the sea breeze season do not significantly affect the circulation, suggesting that a thermal contrast is only needed as a precondition to the development of the sea breeze. We highlight how sea breeze impacts on circulation need to be considered in order to improve the accuracy of assessments of the offshore wind energy climate.

Two Corrections for Turbulent Kinetic Energy Generated by Wind Farms in the WRF Model

2020 ◽  
Vol 148 (12) ◽  
pp. 4823-4835
Author(s):  
Cristina L. Archer ◽  
Sicheng Wu ◽  
Yulong Ma ◽  
Pedro A. Jiménez
Keyword(s):  
Wind Speed ◽  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Wind Farm ◽  
Atmospheric Stability ◽  
Wrf Model ◽  
Wind Farms ◽  
Near Surface ◽  
Large Eddy ◽  
The Way

AbstractAs wind farms grow in number and size worldwide, it is important that their potential impacts on the environment are studied and understood. The Fitch parameterization implemented in the Weather Research and Forecasting (WRF) Model since version 3.3 is a widely used tool today to study such impacts. We identified two important issues related to the way the added turbulent kinetic energy (TKE) generated by a wind farm is treated in the WRF Model with the Fitch parameterization. The first issue is a simple “bug” in the WRF code, and the second issue is the excessive value of a coefficient, called CTKE, that relates TKE to the turbine electromechanical losses. These two issues directly affect the way that a wind farm wake evolves, and they impact properties like near-surface temperature and wind speed at the wind farm as well as behind it in the wake. We provide a bug fix and a revised value of CTKE that is one-quarter of the original value. This 0.25 correction factor is empirical; future studies should examine its dependence on parameters such as atmospheric stability, grid resolution, and wind farm layout. We present the results obtained with the Fitch parameterization in the WRF Model for a single turbine with and without the bug fix and the corrected CTKE and compare them with high-fidelity large-eddy simulations. These two issues have not been discovered before because they interact with one another in such a way that their combined effect is a somewhat realistic vertical TKE profile at the wind farm and a realistic wind speed deficit in the wake. All WRF simulations that used the Fitch wind farm parameterization are affected, and their conclusions may need to be revisited.

scholarly journals Evaluation of the wind farm parameterization in the Weather Research and Forecasting model (version 3.8.1) with meteorological and turbine power data

2017 ◽  
Vol 10 (11) ◽  
pp. 4229-4244 ◽  
Author(s):  
Joseph C. Y. Lee ◽  
Julie K. Lundquist
Keyword(s):  
Wind Speed ◽  
Wind Farm ◽  
Statistical Significance ◽  
Wrf Model ◽  
Grid Cell ◽  
Power Production ◽  
Weather Research And Forecasting ◽  
Model Version ◽  
The Impact ◽  
Weather Research

Abstract. Forecasts of wind-power production are necessary to facilitate the integration of wind energy into power grids, and these forecasts should incorporate the impact of wind-turbine wakes. This paper focuses on a case study of four diurnal cycles with significant power production, and assesses the skill of the wind farm parameterization (WFP) distributed with the Weather Research and Forecasting (WRF) model version 3.8.1, as well as its sensitivity to model configuration. After validating the simulated ambient flow with observations, we quantify the value of the WFP as it accounts for wake impacts on power production of downwind turbines. We also illustrate with statistical significance that a vertical grid with approximately 12 m vertical resolution is necessary for reproducing the observed power production. Further, the WFP overestimates wake effects and hence underestimates downwind power production during high wind speed, highly stable, and low turbulence conditions. We also find the WFP performance is independent of the number of wind turbines per model grid cell and the upwind–downwind position of turbines. Rather, the ability of the WFP to predict power production is most dependent on the skill of the WRF model in simulating the ambient wind speed.

scholarly journals Evaluation of the wind farm parameterization in the Weather Research and Forecasting model (version 3.8.1) with meteorological and turbine power data

2017 ◽  
Author(s):  
Joseph C. Y. Lee ◽  
Julie K. Lundquist
Keyword(s):  
Wind Speed ◽  
Wind Farm ◽  
Statistical Significance ◽  
Atmospheric Stability ◽  
Wrf Model ◽  
Power Production ◽  
Weather Research And Forecasting ◽  
Model Version ◽  
The Impact ◽  
Weather Research

Abstract. Forecasts of wind power production are necessary to facilitate the integration of wind energy into power grids, and these forecasts should incorporate the impact of wind turbine wakes. This paper focuses on a case study of four diurnal cycles with significant power production, and assesses the skill of the wind farm parameterization (WFP) distributed with the Weather Research and Forecasting (WRF) model version 3.8.1, as well as its sensitivity to model configuration. After validating the simulated ambient flow with observations, we quantify the value of the WFP as it accounts for wake impacts on power production of downwind turbines. We also illustrate that a vertical grid with nominally 12-m vertical resolution is necessary for reproducing the observed power production, with statistical significance. Further, the WFP overestimates wake effects and hence underestimates downwind power production during high wind speed and low turbulence conditions. We also find the WFP performance is independent of atmospheric stability, the number of wind turbines per model grid cell, and the upwind-downwind position of turbines. Rather, the ability of the WFP to predict power production is most dependent on the skill of the WRF model in simulating the ambient wind speed.

scholarly journals On the Ability of the WRF Model to Reproduce the Surface Wind Direction over Complex Terrain

2013 ◽  
Vol 52 (7) ◽  
pp. 1610-1617 ◽  
Author(s):  
Pedro A. Jiménez ◽  
Jimy Dudhia
Keyword(s):  
Wind Speed ◽  
Wind Direction ◽  
Complex Terrain ◽  
Grid Point ◽  
Surface Wind ◽  
Winter Season ◽  
Wrf Model ◽  
Horizontal Resolution ◽  
Surface Flow ◽  
High Horizontal Resolution

AbstractThe ability of the Weather Research and Forecasting (WRF) model to reproduce the surface wind direction over complex terrain is examined. A simulation spanning a winter season at a high horizontal resolution of 2 km is compared with wind direction records from a surface observational network located in the northeastern Iberian Peninsula. A previous evaluation has shown the ability of WRF to reproduce the wind speed over the region once the effects of the subgrid-scale topography are parameterized. Hence, the current investigation complements the previous findings, providing information about the model's ability to reproduce the direction of the surface flow. The differences between the observations and the model are quantified in terms of scores explicitly designed to handle the circular nature of the wind direction. Results show that the differences depend on the wind speed. The larger the wind speed is, the smaller are the wind direction differences. Areas with more complex terrain show larger systematic differences between model and observations; in these areas, a statistical correction is shown to help. The importance of the grid point selected for the comparison with observations is also analyzed. A careful selection is relevant to reducing comparative problems over complex terrain.

scholarly journals Idealized WRF model sensitivity simulations of sea breeze types and their effects on offshore windfields

2013 ◽  
Vol 13 (1) ◽  
pp. 443-461 ◽  
Author(s):  
C. J. Steele ◽  
S. R. Dorling ◽  
R. von Glasow ◽  
J. Bacon
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Farm ◽  
Wrf Model ◽  
Sea Breeze ◽  
Offshore Wind ◽  
Energy Output ◽  
State University ◽  
Sea Breezes ◽  
Gradient Wind

Abstract. The behaviour and characteristics of the marine component of sea breeze cells have received little attention relative to their onshore counterparts. Yet there is a growing interest and dependence on the offshore wind climate from, for example, a wind energy perspective. Using idealized model experiments, we investigate the sea breeze circulation at scales which approximate to those of the southern North Sea, a region of major ongoing offshore wind farm development. We also contrast the scales and characteristics of the pure and the little known corkscrew and backdoor sea breeze types, where the type is pre-defined by the orientation of the synoptic scale flow relative to the shoreline. We find, crucially, that pure sea breezes, in contrast to corkscrew and backdoor types, can lead to substantial wind speed reductions offshore and that the addition of a second eastern coastline emphasises this effect through generation of offshore "calm zones". The offshore extent of all sea breeze types is found to be sensitive to both the influence of Coriolis acceleration and to the boundary layer scheme selected. These extents range, for example for a pure sea breeze produced in a 2 m s−1 offshore gradient wind, from 0 km to 21 km between the Mellor-Yamada-Nakanishi-Niino and the Yonsei State University schemes respectively. The corkscrew type restricts the development of a backdoor sea breeze on the opposite coast and is also capable of traversing a 100 km offshore domain even under high along-shore gradient wind speed (>15 m s−1) conditions. Realistic variations in sea surface skin temperature and initializing vertical thermodynamic profile do not significantly alter the resulting circulation, though the strengths of the simulated sea breezes are modulated if the effective land-sea thermal contrast is altered. We highlight how sea breeze impacts on circulation need to be considered in order to improve the accuracy of both assessments of the offshore wind energy climate and forecasts of wind energy output.

Configuration of Statistical Postprocessing Techniques for Improved Low-Level Wind Speed Forecasts in West Texas

2020 ◽  
Vol 35 (1) ◽  
pp. 129-147
Author(s):  
Meghan J. Mitchell ◽  
Brian Ancell ◽  
Jared A. Lee ◽  
Nicholas H. Smith
Keyword(s):  
Wind Speed ◽  
Wind Farm ◽  
Weather Prediction ◽  
Wrf Model ◽  
Turbine Rotor ◽  
Low Level ◽  
Wind Speeds ◽  
West Texas ◽  
Model Output Statistics ◽  
Sonic Detection

Abstract The wind energy industry needs accurate forecasts of wind speeds at turbine hub height and in the rotor layer to accurately predict power output from a wind farm. Current numerical weather prediction (NWP) models struggle to accurately predict low-level winds, partially due to systematic errors within the models due to deficiencies in physics parameterization schemes. These types of errors are addressed in this study with two statistical postprocessing techniques—model output statistics (MOS) and the analog ensemble (AnEn)—to understand the value of each technique in improving rotor-layer wind forecasts. This study is unique in that it compares the techniques using a sonic detection and ranging (SODAR) wind speed dataset that spans the entire turbine rotor layer. This study uses reforecasts from the Weather Research and Forecasting (WRF) Model and observations in west Texas over periods of up to two years to examine the skill added to forecasts when applying both MOS and the AnEn. Different aspects of the techniques are tested, including model horizontal and vertical resolution, number of predictors, and training set length. Both MOS and the AnEn are applied to several levels representing heights in the turbine rotor layer (40, 60, 80, 100, and 120 m). This study demonstrates the degree of improvement that different configurations of each technique provides to raw WRF forecasts, to help guide their use for low-level wind speed forecasts. It was found that both AnEn and MOS show significant improvement over the raw WRF forecasts, but the two methods do not differ significantly from each other.

scholarly journals Observed and simulated turbulent kinetic energy (WRF 3.8.1) overlarge offshore wind farms

2019 ◽  
Author(s):  
Simon K. Siedersleben ◽  
Andreas Platis ◽  
Julie K. Lundquist ◽  
Bughsin Djath ◽  
Astrid Lampert ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Wind Farm ◽  
Wind Farms ◽  
Horizontal Resolution ◽  
Offshore Wind ◽  
Vertical Resolution ◽  
Offshore Wind Farms ◽  
The Impact ◽  
Simulated Wind

Abstract. Because wind farms affect local weather and microclimates, parameterizations of their effects have been developed for numerical weather prediction models. While most wind farm parameterizations (WFP) include drag effects of wind farms, models differ on whether or not an additional turbulent kinetic energy (TKE) source should be included in these parameterizations to simulate the impact of wind farms on the boundary layer. Therefore, we use aircraft measurements above large offshore wind farms in stable conditions to evaluate WFP choices. Of the three case studies we examine, we find the simulated ambient background flow to agree with observations of temperature stratification and winds. This agreement allowing us to explore the sensitivity of simulated wind farm effects with respect to modeling choices such as whether or not to include a TKE source, horizontal resolution, vertical resolution, and advection of TKE. For a stably stratified marine atmospheric boundary layer (MABL), a TKE source and a horizontal resolution in the order of 5 km or finer are necessary to represent the impact of offshore wind farms on the MABL. Additionally, TKE advection results in excessively reduced TKE over the wind farms, which in turn causes an underestimation of the wind speed above the wind farm. Furthermore, using fine vertical resolution increases the agreement of the simulated wind speed with satellite observations of surface wind speed.

scholarly journals Sensitivity of the WRF model to PBL parametrizations and nesting techniques: evaluation of surface wind over complex terrain

2015 ◽  
Vol 8 (7) ◽  
pp. 5437-5479 ◽  
Author(s):  
J. J. Gómez-Navarro ◽  
C. C. Raible ◽  
S. Dierer
Keyword(s):  
Wind Speed ◽  
Complex Terrain ◽  
Surface Wind ◽  
Wrf Model ◽  
Horizontal Resolution ◽  
Economic Damage ◽  
Climate Modelling ◽  
Spectral Nudging ◽  
Pbl Scheme ◽  
Wind Storms

Abstract. Simulating surface wind over complex terrain is a challenge in regional climate modelling. Therefore, this study aims at identifying a setup of the WRF model that minimizes systematic errors of surface winds in hindcast simulations. Major factors of the model configuration are tested to find a suitable setup: the horizontal resolution, the PBL parameterization scheme and the way WRF is nested to the driving dataset. Hence, a number of sensitivity simulations at a spatial resolution of 2 km are carried out and compared to observations. Given the importance of wind storms, the analysis is based on case studies of 24 historical wind storms that caused great economic damage in Switzerland. Each of these events is downscaled using eight different model setups, but sharing the same driving dataset. The results show that the unresolved topography leads to a general overestimation of wind speed in WRF. However, this bias can be substantially reduced by using a PBL scheme that explicitly considers the effects of non-resolved topography, which also improves the spatial structure of wind speed over Switzerland. The wind direction, although generally well reproduced, is not very sensitive to the PBL scheme. Further sensitivity tests include four types of nesting methods: nesting only at the boundaries of the outermost domain, analysis and spectral nudging, and the so-called re-forecast method, where the simulation is frequently restarted. These simulations show that restricting the freedom of the model to develop large-scale disturbances slightly increases the temporal agreement with the observations, at the same time that it further reduces the overestimation of wind speed, especially for maximum wind peaks. The model skill is also evaluated in the outermost domains, where the resolution is coarser. The results demonstrate the important role of horizontal resolution, where the step from 6 to 2 km significantly improves model performance. In summary, the combination of a grid size of 2 km, the non-local PBL scheme modified to explicitly account for non-resolved orography, as well as analysis or spectral nudging, is a superior combination when dynamical downscaling is aimed at reproducing real wind fields.

scholarly journals Turbulent kinetic energy over large offshore wind farms observed and simulated by the mesoscale model WRF (3.8.1)

2020 ◽  
Vol 13 (1) ◽  
pp. 249-268 ◽  
Author(s):  
Simon K. Siedersleben ◽  
Andreas Platis ◽  
Julie K. Lundquist ◽  
Bughsin Djath ◽  
Astrid Lampert ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Wind Farm ◽  
Wind Farms ◽  
Horizontal Resolution ◽  
Offshore Wind ◽  
Vertical Resolution ◽  
Offshore Wind Farms ◽  
The Impact ◽  
Simulated Wind

Abstract. Wind farms affect local weather and microclimates; hence, parameterizations of their effects have been developed for numerical weather prediction models. While most wind farm parameterizations (WFPs) include drag effects of wind farms, models differ on whether or not an additional turbulent kinetic energy (TKE) source should be included in these parameterizations to simulate the impact of wind farms on the boundary layer. Therefore, we use aircraft measurements above large offshore wind farms in stable conditions to evaluate WFP choices. Of the three case studies we examine, we find the simulated ambient background flow to agree with observations of temperature stratification and winds. This agreement allows us to explore the sensitivity of simulated wind farm effects with respect to modeling choices such as whether or not to include a TKE source, horizontal resolution, vertical resolution and advection of TKE. For a stably stratified marine atmospheric boundary layer (MABL), a TKE source and a horizontal resolution on the order of 5 km or finer are necessary to represent the impact of offshore wind farms on the MABL. Additionally, TKE advection results in excessively reduced TKE over the wind farms, which in turn causes an underestimation of the wind speed deficit above the wind farm. Furthermore, using fine vertical resolution increases the agreement of the simulated wind speed with satellite observations of surface wind speed.

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