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 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.

Evaluating Community Engagement and Benefit-Sharing Practices in Australian Wind Farm Development

2017 ◽  
Vol 1 (1) ◽  
pp. 1-6 ◽  
Author(s):  
Nina Lansbury Hall ◽  
Jarra Hicks ◽  
Taryn Lane ◽  
Emily Wood
Keyword(s):  
Community Engagement ◽  
Community Involvement ◽  
Wind Farm ◽  
Social Acceptance ◽  
Wind Farms ◽  
Clean Energy ◽  
Benefit Sharing ◽  
Delphi Panel ◽  
Government Organizations

The wind industry is positioned to contribute significantly to a clean energy future, yet the level of community opposition has at times led to unviable projects. Social acceptance is crucial and can be improved in part through better practice community engagement and benefit-sharing. This case study provides a “snapshot” of current community engagement and benefit-sharing practices for Australian wind farms, with a particular emphasis on practices found to be enhancing positive social outcomes in communities. Five methods were used to gather views on effective engagement and benefit-sharing: a literature review, interviews and a survey of the wind industry, a Delphi panel, and a review of community engagement plans. The overarching finding was that each community engagement and benefit-sharing initiative should be tailored to a community’s context, needs and expectations as informed by community involvement. This requires moving away from a “one size fits all” approach. This case study is relevant to wind developers, energy regulators, local communities and renewable energy-focused non-government organizations. It is applicable beyond Australia to all contexts where wind farm development has encountered conflicted societal acceptance responses.

scholarly journals Evaluation of the WRF Model to Simulate a High-Intensity Rainfall Event over Kampala, Uganda

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 873
Author(s):  
Yakob Umer ◽  
Janneke Ettema ◽  
Victor Jetten ◽  
Gert-Jan Steeneveld ◽  
Reinder Ronda
Keyword(s):  
High Intensity ◽  
Flood Hazard ◽  
Weather Prediction ◽  
Wrf Model ◽  
Numerical Weather Prediction Model ◽  
Rainfall Event ◽  
Weather Research And Forecasting ◽  
Event Triggering ◽  
Rain Events

Simulating high-intensity rainfall events that trigger local floods using a Numerical Weather Prediction model is challenging as rain-bearing systems are highly complex and localized. In this study, we analyze the performance of the Weather Research and Forecasting (WRF) model’s capability in simulating a high-intensity rainfall event using a variety of parameterization combinations over the Kampala catchment, Uganda. The study uses the high-intensity rainfall event that caused the local flood hazard on 25 June 2012 as a case study. The model capability to simulate the high-intensity rainfall event is performed for 24 simulations with a different combination of eight microphysics (MP), four cumulus (CP), and three planetary boundary layer (PBL) schemes. The model results are evaluated in terms of the total 24-h rainfall amount and its temporal and spatial distributions over the Kampala catchment using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) analysis. Rainfall observations from two gauging stations and the CHIRPS satellite product served as benchmark. Based on the TOPSIS analysis, we find that the most successful combination consists of complex microphysics such as the Morrison 2-moment scheme combined with Grell-Freitas (GF) and ACM2 PBL with a good TOPSIS score. However, the WRF performance to simulate a high-intensity rainfall event that has triggered the local flood in parts of the catchment seems weak (i.e., 0.5, where the ideal score is 1). Although there is high spatial variability of the event with the high-intensity rainfall event triggering the localized floods simulated only in a few pockets of the catchment, it is remarkable to see that WRF is capable of producing this kind of event in the neighborhood of Kampala. This study confirms that the capability of the WRF model in producing high-intensity tropical rain events depends on the proper choice of parametrization combinations.

scholarly journals Use of Analytic Hierarchy Process for Wind Farm Installation Region Prioritization–Case Study

Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2284 ◽  
Author(s):  
Rômulo Lemos Bulhões ◽  
Eudemário Souza de Santana ◽  
Alex Álisson Bandeira Santos
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy Process ◽  
Wind Farm ◽  
Greenhouse Gas Emission ◽  
Wind Farms ◽  
Clean Energy ◽  
Poor Quality ◽  
Analytic Hierarchy ◽  
Hierarchy Process

Electricity generation via renewable sources is emerging as a possible solution to meet the growing demand for electricity worldwide. Additionally, the need to produce clean energy, with little or no pollutants or greenhouse gas emission is paramount. Due to these factors, wind farms are noticeably increasing in number, especially in Brazil. However, the vast size of the country and the poor quality of its infrastructure are among several factors that make it difficult for effective decision-making to accelerate the growth of this segment in Brazil. With the purpose of assisting government agencies, regulatory agencies and other institutions in this area, the use of a multi-criteria selection method called the analytic hierarchy process is proposed here to assist in decision-making and to select priority regions for implementing wind farms. This work focuses on a case study of the state of Bahia, in which 27 territories were selected for an installation priority evaluation. Computational tools were used to hierarchize these chosen territories, including Matlab, for the construction of the computational algorithm. The results indicate the priority pf the regions according to the established criteria, which allows installation locations to be mapped—these could serve as a basis for regional investment.

scholarly journals Looking for an Offshore Low-Level Jet Champion among Recent Reanalyses: A Tight Race over the Baltic Sea

Energies ◽  
2020 ◽  
Vol 13 (14) ◽  
pp. 3670
Author(s):  
Christoffer Hallgren ◽  
Johan Arnqvist ◽  
Stefan Ivanell ◽  
Heiner Körnich ◽  
Ville Vakkari ◽  
...  
Keyword(s):  
Baltic Sea ◽  
Wind Farms ◽  
Resource Assessment ◽  
Offshore Wind ◽  
The Baltic Sea ◽  
Average Wind Speed ◽  
Low Level ◽  
Wide Range ◽  
Low Level Jets ◽  
The Baltic

With an increasing interest in offshore wind energy, focus has been directed towards large semi-enclosed basins such as the Baltic Sea as potential sites to set up wind turbines. The meteorology of this inland sea in particular is strongly affected by the surrounding land, creating mesoscale conditions that are important to take into consideration when planning for new wind farms. This paper presents a comparison between data from four state-of-the-art reanalyses (MERRA2, ERA5, UERRA, NEWA) and observations from LiDAR. The comparison is made for four sites in the Baltic Sea with wind profiles up to 300 m. The findings provide insight into the accuracy of reanalyses for wind resource assessment. In general, the reanalyses underestimate the average wind speed. The average shear is too low in NEWA, while ERA5 and UERRA predominantly overestimate the shear. MERRA2 suffers from insufficient vertical resolution, which limits its usefulness in evaluating the wind profile. It is also shown that low-level jets, a very frequent mesoscale phenomenon in the Baltic Sea during late spring, can appear in a wide range of wind speeds. The observed frequency of low-level jets is best captured by UERRA. In terms of general wind characteristics, ERA5, UERRA, and NEWA are similar, and the best choice depends on the application.

Modeling of Flow Acceleration Around Wind Farms

2007 ◽  
Author(s):  
Patrick Moriarty ◽  
Tetsuya Kogaki
Keyword(s):  
Wind Farm ◽  
Computational Models ◽  
Three Dimensional ◽  
Wind Farms ◽  
Navier Stokes ◽  
Local Wind ◽  
Flow Acceleration ◽  
Wind Speeds ◽  
Optimum Spacing ◽  
Future Work

Recent measurements from operating wind farms demonstrate that the layout of the farm and interactions between turbine wakes strongly affects the overall efficiency of the wind farm. In some wind farms arranged in rectangular layouts, winds coming from the direction of the rectangular corner create a potential acceleration around the wind farm. This acceleration inherently leads to stronger local wind speeds at wind turbines downstream of the corner turbine, thereby increasing the power output of the downstream turbines. In this study, computational models are developed to predict this complex behavior seen in wind farms. The model used to examine these effects is a fully three-dimensional unsteady incompressible Navier-Stokes code, with the turbulence model turned off. Preliminary results show an optimum spacing configuration is possible. However, the results have yet to be verified at higher Reynolds number, which will be the effort of future work. Ultimately, these tools may lead to more optimal wind farm layouts.

scholarly journals Noise assessment of the small-scale wind farm

2019 ◽  
Vol 112 ◽  
pp. 02011
Author(s):  
Cristian-Gabriel Alionte ◽  
Daniel-Constantin Comeaga
Keyword(s):  
Power Systems ◽  
Large Scale ◽  
Wind Farm ◽  
Wind Farms ◽  
Small Scale ◽  
Large Power ◽  
Small Power ◽  
Noise Assessment ◽  
The Impact

The importance of renewable energy and especially of eolian systems is growing. For this reason, we propose the investigation of an important pollutant - the noise, which has become so important that European Commission and European Parliament introduced Directive 2002/49/CE relating to the assessment and management of environmental noise. So far, priority has been given to very large-scale systems connected to national energy systems, wind farms whose highly variable output power could be regulated by large power systems. Nowadays, with the development of small storage capacities, it is feasible to install small power wind turbines in cities of up to 10,000 inhabitants too. As a case study, we propose a simulation for a rural locality where individual wind units could be used. This specific case study is interesting because it provides a new perspective of the impact of noise on the quality of life when the use of this type of system is implemented on a large scale. This option, of distributed and small power wind turbine, can be implemented in the future as an alternative or an adding to the common systems.

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