A study of the impact of very large wind farms on regional weather using the WRF model in high resolution

2020 ◽  
Author(s):  
Simon Jacobsen ◽  
Aksel Walløe Hansen
Keyword(s):  
Wind Speed ◽  
Wind Turbines ◽  
Wind Farm ◽  
Wrf Model ◽  
Wind Farms ◽  
Real Data ◽  
Power Production ◽  
Wake Effects ◽  
The Impact ◽  
Large Wind

<p>The Weather Research and Forecasting (WRF) model fitted with the Fitch et al. (2012) scheme for parameterization of the effect of wind energy extraction is used to study the effects of very large wind farms on regional weather. Two real data cases have been run in a high spatial resolution (grid size 500 m). Both cases are characterized by a convective westerly flow. The inner model domain covers the North Sea and Denmark. The largest windfarm consists of 200.000 wind turbines each with a capacity of 8MW. The model is run for up to 12 hours with and without the wind farm. The impact on the regional weather of these very large wind farms are studied and presented. Furthermore, the effect of horizontal spacing between wind turbines is investigated. Significant impact on the regional weather from the very large wind farms was found. Horizontal wind speed changes occur up to 3500m above the surface. The precipitation pattern is greatly affected by the very large wind farms due to the enhanced mixing in the boundary layer. Increased precipitation occurs at the front? within the wind farm, thus leaving the airmass relatively dry downstream when it reaches the Danish coast, resulting in a decrease in precipitation here compared to the control run. The formation of a small low level jet is found above the very large wind farm. Furthermore, wake effects from individual wind turbines decrease the total power production. The wind speed in the real data cases are well above the speed of maximum power production of the wind turbines. Yet most of the 200.000 wind turbines are producing only 1MW due the wake effects. A simulation run with a wind farm of 50.000 8MW wind turbines was also run. This windfarm covers the same area as the previous one, but horizontal distance between wind turbines are 1000m instead of 500m. This configuration was found to produce a similar amount of power as the 200.000 configuration. However, the atmospheric impact on regional weather is smaller but still large with 50.000 wind turbines.</p>

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.

Optimization of Large Wind Farms Using a Genetic Algorithm

2012 ◽  
Author(s):  
Anshul Mittal ◽  
Lafayette K. Taylor
Keyword(s):  
Genetic Algorithm ◽  
Wind Speed ◽  
Wind Turbines ◽  
Wind Direction ◽  
Wind Farm ◽  
Wind Farms ◽  
Unit Power ◽  
Wake Model ◽  
Variable Wind ◽  
Large Wind

Optimizing the placement of the wind turbines in a wind farm to achieve optimal performance is an active area of research, with numerous research studies being published every year. Typically, the area available for the wind farm is divided into cells (a cell may/may not contain a wind turbine) and an optimization algorithm is used. In this study, the effect of the cell size on the optimal layout is being investigated by reducing it from five rotor diameter (previous studies) to 1/40 rotor diameter (present study). A code is developed for optimizing the placement of wind turbines in large wind farms. The objective is to minimize the cost per unit power produced from the wind farm. A genetic algorithm is employed for the optimization. The velocity deficits in the wake of the wind turbines are estimated using a simple wake model. The code is verified using the results from the previous studies. Results are obtained for three different wind regimes: (1) Constant wind speed and fixed wind direction, (2) constant wind speed and variable wind direction, and (3) variable wind speed and variable wind direction. Cost per unit power is reduced by 11.7% for Case 1, 11.8% for Case 2, and 15.9% for Case 3 for results obtained in this study. The advantages/benefits of a refined grid spacing of 1/40 rotor diameter (1 m) are evident and are discussed. To get an understanding of the sensitivity of the power produced to the wake model, optimized layout is obtained for the Case 1 using a different wake model.

scholarly journals On the Robustness of Active Wake Control to Wind Turbine Downtime

Energies ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 3152
Author(s):  
Stoyan Kanev
Keyword(s):  
Wind Turbines ◽  
Wind Farm ◽  
Wind Farms ◽  
Power Production ◽  
Offshore Wind ◽  
Negative Effects ◽  
Collaborative Control ◽  
Potential Benefits ◽  
Production Increase ◽  
The Impact

Active wake control (AWC) is an operational strategy for wind farms that aims at reducing the negative effects of wakes behind wind turbines on the power production and mechanical loads at the wind turbines’ downstream. For a given wind direction, the strategy relies on collaborative control of the machines within each row of turbines that affect each other through their wakes. The vast amount of research performed during the last decade indicates that the potential upside of this technology on the annual energy production of a wind farm can be as high as a few percentage points. Although these predictions on the potential benefits are quite significant, they typically assume full availability of all turbines within a row operating under AWC. However, even though the availability of offshore wind turbines is nowadays quite high (as high as 95%, or even higher), the availability of a whole row of turbines is shown to be much lower (lower than 60% for a row of ten turbines). This paper studies the impact of turbine downtime on the power production increase from AWC, and concludes that the AWC is robust enough to be kept operational in the presence of turbines standing still.

Wind Farm Layout Optimization Using a Viral Systems Algorithm

2013 ◽  
Vol 4 (4) ◽  
pp. 27-40 ◽  
Author(s):  
Jose F. Espiritu ◽  
Carlos M. Ituarte-Villarreal
Keyword(s):  
Wind Speed ◽  
Wind Turbines ◽  
Wind Farm ◽  
Wind Farms ◽  
Optimal Number ◽  
Wind Park ◽  
Variable Direction ◽  
The Cost ◽  
Variable Wind ◽  
Large Wind

In the present research a new viral systems optimization algorithm is developed to find the optimal number and position of wind turbines in large wind farms with the main objective of minimizing the cost per unit power produced from the wind park. The developed algorithm is applied to three well known problems in literature which are: 1) constant wind speed and unidirectional uniform wind, 2) constant wind speed with variable direction, and 3) non-uniform variable wind speed with variable direction. In the final results, the distance between two wind turbines is reduced to one meter, compared to 5 rotor diameters in previous studies.

scholarly journals Performance Enhancement of Proposed Namaacha Wind Farm by Minimising Losses Due to the Wake Effect: A Mozambican Case Study

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4291
Author(s):  
Paxis Marques João Roque ◽  
Shyama Pada Chowdhury ◽  
Zhongjie Huan
Keyword(s):  
Wind Speed ◽  
Wind Power ◽  
Wind Turbines ◽  
Power Output ◽  
Wind Farm ◽  
Wind Farms ◽  
Operating Conditions ◽  
Wake Effect ◽  
Wind Generators ◽  
Wind Potential

District of Namaacha in Maputo Province of Mozambique presents a high wind potential, with an average wind speed of around 7.5 m/s and huge open fields that are favourable to the installation of wind farms. However, in order to make better use of the wind potential, it is necessary to evaluate the operating conditions of the turbines and guide the independent power producers (IPPs) on how to efficiently use wind power. The investigation of the wind farm operating conditions is justified by the fact that the implementation of wind power systems is quite expensive, and therefore, it is imperative to find alternatives to reduce power losses and improve energy production. Taking into account the power needs in Mozambique, this project applied hybrid optimisation of multiple energy resources (HOMER) to size the capacity of the wind farm and the number of turbines that guarantee an adequate supply of power. Moreover, considering the topographic conditions of the site and the operational parameters of the turbines, the system advisor model (SAM) was applied to evaluate the performance of the Vestas V82-1.65 horizontal axis turbines and the system’s power output as a result of the wake effect. For any wind farm, it is evident that wind turbines’ wake effects significantly reduce the performance of wind farms. The paper seeks to design and examine the proper layout for practical placements of wind generators. Firstly, a survey on the Namaacha’s electricity demand was carried out in order to obtain the district’s daily load profile required to size the wind farm’s capacity. Secondly, with the previous knowledge that the operation of wind farms is affected by wake losses, different wake effect models applied by SAM were examined and the Eddy–Viscosity model was selected to perform the analysis. Three distinct layouts result from SAM optimisation, and the best one is recommended for wind turbines installation for maximising wind to energy generation. Although it is understood that the wake effect occurs on any wind farm, it is observed that wake losses can be minimised through the proper design of the wind generators’ placement layout. Therefore, any wind farm project should, from its layout, examine the optimal wind farm arrangement, which will depend on the wind speed, wind direction, turbine hub height, and other topographical characteristics of the area. In that context, considering the topographic and climate features of Mozambique, the study brings novelty in the way wind farms should be placed in the district and wake losses minimised. The study is based on a real assumption that the project can be implemented in the district, and thus, considering the wind farm’s capacity, the district’s energy needs could be met. The optimal transversal and longitudinal distances between turbines recommended are 8Do and 10Do, respectively, arranged according to layout 1, with wake losses of about 1.7%, land utilisation of about 6.46 Km2, and power output estimated at 71.844 GWh per year.

Wind farm cooperative control for optimal power generation

2018 ◽  
Vol 42 (6) ◽  
pp. 547-560 ◽  
Author(s):  
Fa Wang ◽  
Mario Garcia-Sanz
Keyword(s):  
Power Generation ◽  
Wind Turbines ◽  
Cooperative Control ◽  
Wind Farm ◽  
Wind Farms ◽  
Practical Method ◽  
Individual Case ◽  
Power Coefficient ◽  
The Individual ◽  
Large Wind

The power generation of a wind farm depends on the efficiency of the individual wind turbines of the farm. In large wind farms, wind turbines usually affect each other aerodynamically at some specific wind directions. Previous studies suggest that a way to maximize the power generation of these wind farms is to reduce the generation of the first rows wind turbines to allow the next rows to generate more power (coordinated case). Yet, other studies indicate that the maximum generation of the wind farm is reached when every wind turbine works at its individual maximum power coefficient CPmax (individual case). This article studies this paradigm and proposes a practical method to evaluate when the wind farm needs to be controlled according to the individual or the coordinated case. The discussion is based on basic principles, numerical computations, and wind tunnel experiments.

scholarly journals A Study of the Impact of Pitch Misalignment on Wind Turbine Performance

Machines ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 8 ◽  
Author(s):  
Davide Astolfi
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Power Output ◽  
Wind Farm ◽  
Reactive Power ◽  
Power Production ◽  
Test Case ◽  
Before And After ◽  
Input Variables ◽  
The Impact

Pitch angle control is the most common means of adjusting the torque of wind turbines. The verification of its correct function and the optimization of its control are therefore very important for improving the efficiency of wind kinetic energy conversion. On these grounds, this work is devoted to studying the impact of pitch misalignment on wind turbine power production. A test case wind farm sited onshore, featuring five multi-megawatt wind turbines, was studied. On one wind turbine on the farm, a maximum pitch imbalance between the blades of 4.5 ° was detected; therefore, there was an intervention for recalibration. Operational data were available for assessing production improvement after the intervention. Due to the non-stationary conditions to which wind turbines are subjected, this is generally a non-trivial problem. In this work, a general method was formulated for studying this kind of problem: it is based on the study, before and after the upgrade, of the residuals between the measured power output and a reliable model of the power output itself. A careful formulation of the model is therefore crucial: in this work, an automatic feature selection algorithm based on stepwise multivariate regression was adopted, and it allows identification of the most meaningful input variables for a multivariate linear model whose target is the power of the wind turbine whose pitch has been recalibrated. This method can be useful, in general, for the study of wind turbine power upgrades, which have been recently spreading in the wind energy industry, and for the monitoring of wind turbine performances. For the test case of interest, the power of the recalibrated wind turbine is modeled as a linear function of the active and reactive power of the nearby wind turbines, and it is estimated that, after the intervention, the pitch recalibration provided a 5.5% improvement in the power production below rated power. Wind turbine practitioners, in general, should pay considerable attention to the pitch imbalance, because it increases loads and affects the residue lifetime; in particular, the results of this study indicate that severe pitch misalignment can heavily impact power production.

Design Analysis of Critical Concepts Influence Wind Farm Production and Efficiency

2018 ◽  
Vol 40 ◽  
pp. 136-150
Author(s):  
Naima Charhouni ◽  
Mohammed Sallaou ◽  
Khalifa Mansouri
Keyword(s):  
Wind Turbines ◽  
Wind Farm ◽  
Production Efficiency ◽  
Wind Farms ◽  
Power Production ◽  
Separation Distance ◽  
Design Analysis ◽  
Offshore Wind ◽  
Farm Production ◽  
Wind Farm Design

Wind farm deficiency caused by wake turbine interactions has received an important attention by scientific researchers in recent years. However the quality of power production is strongly depends on wind turbines location from others. In this regard, this paper proposes a comprehensive design analysis of crucial concepts that aid to plan for an efficient wind farm design. Indeed, the wake modeling problem is addressed in this analysis by comparing three models with available measured data gotten from literature. A configuration of wind turbines placement within the offshore wind farm as a function of separation distance is investigated in this study considering four wind farms layout. In addition to these elements, four rotor diameters size are evaluated as critical concept for wind turbine selection and production .The results obtained demonstrate that it is complicated to make a balance between three conflicted objectives related to the power production, efficiency and surface land area required for wind farm as a function of these crucial concepts.

scholarly journals Wind Farm Loads under Wake Redirection Control

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4088
Author(s):  
Stoyan Kanev ◽  
Edwin Bot ◽  
Jack Giles
Keyword(s):  
Large Scale ◽  
Wind Farm ◽  
Wind Farms ◽  
Power Production ◽  
Power Gain ◽  
Main Obstacle ◽  
Depth Analysis ◽  
Wake Effects ◽  
Fatigue Loads ◽  
Positive Effect

Active wake control (AWC) is a strategy for operating wind farms in such a way as to reduce the wake effects on the wind turbines, potentially increasing the overall power production. There are two concepts to AWC: induction control and wake redirection. The former strategy boils down to down-regulating the upstream turbines in order to increase the wind speed in their wakes. This has generally a positive effect on the turbine loading. The wake redirection concept, which relies on intentional yaw misalignment to move wakes away from downstream turbines, has a much more prominent impact and may lead to increased loading. Moreover, the turbines are typically not designed and certified to operate at large yaw misalignments. Even though the potential upsides in terms of power gain are very interesting, the risk for damage or downtime due to increased loading is seen as the main obstacle preventing large scale implementation of this technology. In order to provide good understanding on the impacts of AWC on the turbine loads, this paper presents the results from an in-depth analysis of the fatigue loads on the turbines of an existing wind farm. Even though for some wind turbine components the fatigue loads do increase for some wind conditions under yaw misalignment, it is demonstrated that the wake-induced loading decreases even more so that the lifetime loads under AWC are generally lower.

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