scholarly journals Forecast of Icing Events at a Wind Farm in Sweden

2014 ◽  
Vol 53 (2) ◽  
pp. 262-281 ◽  
Author(s):  
Neil Davis ◽  
Andrea N. Hahmann ◽  
Niels-Erik Clausen ◽  
Mark Žagar
Keyword(s):  
Wind Farm ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Static Structure ◽  
Model Driven ◽  
Accretion Model ◽  
Pbl Scheme ◽  
Wind Park ◽  
The Times ◽  
Persistence Model

AbstractThis paper introduces a method for identifying icing events using a physical icing model, driven by atmospheric data from the Weather Research and Forecasting (WRF) model, and applies it to a wind park in Sweden. Observed wind park icing events were identified by deviation from an idealized power curve and observed temperature. The events were modeled using a physical icing model with equations for both accretion and ablation mechanisms (iceBlade). The accretion model is based on the Makkonen model but was modified to make it applicable to the blades of a wind turbine rather than a static structure, and the ablation model is newly developed. The results from iceBlade are shown to outperform a 1-day persistence model and standard cylinder model in determining the times when any turbine in the wind park is being impacted by icing. The icing model was evaluated using inputs from simulations using nine different WRF physics parameterization combinations. The combination of the Thompson microphysics parameterization and version 2 of the Mellor–Yamada–Nakanishi–Niino PBL scheme was shown to perform best at this location. The distribution of cloud mass into the appropriate hydrometeor classes was found to be very important for forecasting the correct icing period. One concern with the iceBlade approach was the relatively high false alarm rates at the end of icing events due to the ice not being removed rapidly enough.

scholarly journals Simulation of Severe Thunderstorms in Conjugation of Westerly and Easterly on 31 March 2019 in Bangladesh

2022 ◽  
Vol 12 (3) ◽  
pp. 29-43
Author(s):  
Samarendra Karmakar ◽  
Mohan Kumar Das ◽  
Md Quamrul Hassam ◽  
Md Abdul Mannan
Keyword(s):  
South Asian ◽  
Wrf Model ◽  
Horizontal Resolution ◽  
Weather Research And Forecasting ◽  
Atmospheric Conditions ◽  
Microphysics Scheme ◽  
Severe Thunderstorms ◽  
Synoptic Conditions ◽  
Pbl Scheme ◽  
Single Moment

The diagnostic and prognostic studies of thunderstorms/squalls are very important to save live and loss of properties. The present study aims at diagnose the different tropospheric parameters, instability and synoptic conditions associated the severe thunderstorms with squalls, which occurred at different places in Bangladesh on 31 March 2019. For prognostic purposes, the severe thunderstorms occurred on 31 March 2019 have been numerically simulated. In this regard, the Weather Research and Forecasting (WRF) model is used to predict different atmospheric conditions associated with the severe storms. The study domain is selected for 9 km horizontal resolution, which almost covers the south Asian region. Numerical experiments have been conducted with the combination of WRF single-moment 6 class (WSM6) microphysics scheme with Yonsei University (YSU) PBL scheme in simulation of the squall events. Model simulated results are compared with the available observations. The observed values of CAPE at Kolkata both at 0000 and 1200 UTC were 2680.4 and 3039.9 J kg-1 respectively on 31 March 2019 and are found to be comparable with the simulated values. The area averaged actual rainfall for 24 hrs is found is 22.4 mm, which complies with the simulated rainfall of 20-25 mm for 24 hrs. Journal of Engineering Science 12(3), 2021, 29-43

scholarly journals Mountain Waves Analysis in the Vicinity of the Madrid-Barajas Airport Using the WRF Model

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Javier Díaz-Fernández ◽  
Lara Quitián-Hernández ◽  
Pedro Bolgiani ◽  
Daniel Santos-Muñoz ◽  
Ángel García Gago ◽  
...  
Keyword(s):  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Mountain Range ◽  
Aircraft Icing ◽  
Microphysics Scheme ◽  
Mountain Waves ◽  
Skill Scores ◽  
Stable Conditions ◽  
Pbl Scheme ◽  
Wind Velocities

Turbulence and aircraft icing associated with mountain waves are weather phenomena potentially affecting aviation safety. In this paper, these weather phenomena are analysed in the vicinity of the Adolfo Suárez Madrid-Barajas Airport (Spain). Mountain waves are formed in this area due to the proximity of the Guadarrama mountain range. Twenty different weather research and forecasting (WRF) model configurations are evaluated in an initial analysis. This shows the incompetence of some experiments to capture the phenomenon. The two experiments showing the best results are used to simulate thirteen episodes with observed mountain waves. Simulated pseudosatellite images are validated using satellite observations, and an analysis is performed through several skill scores applied to brightness temperature. Few differences are found among the different skill scores. Nevertheless, the Thompson microphysics scheme combined with the Yonsei university PBL scheme shows the best results. The simulations produced by this scheme are used to evaluate the characteristic variables of the mountain wave episodes at windward and leeward and over the mountain. The results show that north-northwest wind directions, moderate wind velocities, and neutral or slightly stable conditions are the main features for the episodes evaluated. In addition, a case study is analysed to evidence the WRF ability to properly detect turbulence and icing associated with mountain waves, even when there is no visual evidence available.

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 A case study of wind farm effects using two wake parameterizations in WRF (V3.7) in the presence of low level jets

2020 ◽  
Author(s):  
Xiaoli G. Larsén ◽  
Jana Fischereit
Keyword(s):  
Wind Farm ◽  
Wrf Model ◽  
Wind Farms ◽  
Weather Research And Forecasting ◽  
Flow Acceleration ◽  
Low Level ◽  
Low Level Jets ◽  
Flight Measurements

Abstract. While the wind farm parameterization by Fitch et al. (2012) in Weather Research and Forecasting (WRF) model has been used and evaluated frequently, the Explicit Wake Parameterization (EWP) by Volker et al. (2015) is less well explored. The openly available high frequency flight measurements from Bärfuss et al. (2019) provide an opportunity to directly compare the simulation results from the EWP and Fitch scheme with in situ measurements. In doing so, this study aims to compliment the recent study by Siedersleben et al. (2020) by (1) comparing the EWP and Fitch schemes in terms of turbulent kinetic energy (TKE) and velocity deficit, together with FINO 1 measurements and Synthetic Aperture Radar (SAR) data and (2) exploring the interactions of the wind farm with Low Level Jets. Both the Fitch and the EWP schemes can capture the mean wind field in the presence of the wind farm consistently and well. However, their skill is limited in capturing the flow acceleration along the farm edge. TKE in the EWP scheme is significantly underestimated, suggesting that an explicit turbine-induced TKE source should be included in addition to the implicit source from shear. The position of the LLJ nose and the shear beneath the jet nose are modified by the presence of wind farms.

scholarly journals Avaliação da esteira de turbulência gerada por um parque eólico teórico na região do Pampa Gaúcho utilizando o modelo WRF

2020 ◽  
Vol 42 ◽  
pp. e27
Author(s):  
Eduardo Stüker ◽  
Franciano Scremin Puhales ◽  
Luiz Eduardo Medeiros ◽  
Felipe Denardin Costa
Keyword(s):  
Boundary Layer ◽  
Wind Farm ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Atmospheric Flow ◽  
Near Surface ◽  
Control Simulation ◽  
Wind Generators ◽  
Farm Model ◽  
Runoff Decrease

The main objective of this study is to analyze the influence of a wind farm on the variables that control the flow in the atmospheric boundary layer. The simulated period was the whole year of 2008, using a control simulation performed with the Weather Research and Forecasting model (WRF), and the wind farm model (the WRF model with the module Fitch, which parameters the influence of wind turbines on atmospheric flow). Both simulations using the Yonsei-University (YSU) boundary layer parameterization. From the control simulation is made the validation of the model, using observational data collected in two automatic stations of the National Institute of Meteorology (INMET) in the cities of Alegrete-RS and Quaraí-RS. The wind farm idealized in this work has 100 wind generators of 3 MW of power with 120 m in height and with rotor measuring 125 m in diameter. Although the wind speed responds adequately, the temperature and turbulence of near-surface runoff decrease. Analysis of the dependence of near-surface turbulence with vertical stability indicates that the turbulence being generated by the turbines is not reaching the surface. This problem may be related to the chosen boundary layer parameterization.

scholarly journals A case study of wind farm effects using two wake parameterizations in the Weather Research and Forecasting (WRF) model (V3.7.1) in the presence of low-level jets

2021 ◽  
Vol 14 (6) ◽  
pp. 3141-3158
Author(s):  
Xiaoli G. Larsén ◽  
Jana Fischereit
Keyword(s):  
Wind Farm ◽  
Wrf Model ◽  
Wind Farms ◽  
Weather Research And Forecasting ◽  
Low Level ◽  
Low Level Jets ◽  
Simulation Results ◽  
Weather Research

Abstract. While the wind farm parameterization by Fitch et al. (2012) in the Weather Research and Forecasting (WRF) model has been used and evaluated frequently, the explicit wake parameterization (EWP) by Volker et al. (2015) is less well explored. The openly available high-frequency flight measurements from Bärfuss et al. (2019a) provide an opportunity to directly compare the simulation results from the EWP and Fitch scheme with in situ measurements. In doing so, this study aims to complement the recent study by Siedersleben et al. (2020) by (1) comparing the EWP and Fitch schemes in terms of turbulent kinetic energy (TKE) and velocity deficit, together with FINO 1 measurements and synthetic aperture radar (SAR) data, and (2) exploring the interactions of the wind farm with low-level jets (LLJs). This is done using a bug-fixed WRF version that includes the correct TKE advection, following Archer et al. (2020). Both the Fitch and the EWP schemes can capture the mean wind field in the presence of the wind farm consistently and well. TKE in the EWP scheme is significantly underestimated, suggesting that an explicit turbine-induced TKE source should be included in addition to the implicit source from shear. The value of the correction factor for turbine-induced TKE generation in the Fitch scheme has a significant impact on the simulation results. The position of the LLJ nose and the shear beneath the jet nose are modified by the presence of wind farms.

scholarly journals Assimilating X- and S-Band Radar Data for a Heavy Precipitation Event in Italy

Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1727
Author(s):  
Valerio Capecchi ◽  
Andrea Antonini ◽  
Riccardo Benedetti ◽  
Luca Fibbi ◽  
Samantha Melani ◽  
...  
Keyword(s):  
Extreme Event ◽  
Wrf Model ◽  
Heavy Precipitation ◽  
Radar Data ◽  
Flash Floods ◽  
Precipitation Event ◽  
Weather Research And Forecasting ◽  
Limited Area ◽  
Heavy Precipitation Event ◽  
The Town

During the night between 9 and 10 September 2017, multiple flash floods associated with a heavy-precipitation event affected the town of Livorno, located in Tuscany, Italy. Accumulated precipitation exceeding 200 mm in two hours was recorded. This rainfall intensity is associated with a return period of higher than 200 years. As a consequence, all the largest streams of the Livorno municipality flooded several areas of the town. We used the limited-area weather research and forecasting (WRF) model, in a convection-permitting setup, to reconstruct the extreme event leading to the flash floods. We evaluated possible forecasting improvements emerging from the assimilation of local ground stations and X- and S-band radar data into the WRF, using the configuration operational at the meteorological center of Tuscany region (LaMMA) at the time of the event. Simulations were verified against weather station observations, through an innovative method aimed at disentangling the positioning and intensity errors of precipitation forecasts. A more accurate description of the low-level flows and a better assessment of the atmospheric water vapor field showed how the assimilation of radar data can improve quantitative precipitation forecasts.

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