Wind Flow Over a Complex Terrain in Nygårdsfjell, Norway

2015 ◽  
Author(s):  
Muhammad Bilal ◽  
Narendran Sridhar ◽  
Guillermo Araya ◽  
Sivapathas Parameswaran ◽  
Yngve Birkelund
Keyword(s):  
Wind Energy ◽  
Wind Turbine ◽  
Complex Terrain ◽  
Wind Farm ◽  
Turbulence Models ◽  
Future Research ◽  
Wind Flow ◽  
Governing Equations ◽  
The North ◽  
Numerical Predictions

The understanding of atmospheric flows is crucial in the analysis of dispersion of a contaminant or pollutant, wind energy and air-quality assessment to name a few. Additionally, the effects of complex terrain and associated orographic forcing are crucial in wind energy production. Furthermore, the use of the Reynolds-averaged Navier-Stokes (RANS) equations in the analysis of complex terrain is still considered the “workhorse” since millions of mesh points are required to accurately capture the details of the surface. On the other hand, solving the same problem by means of the instantaneous governing equations of the flow (i.e., in a suite of DNS or LES) would imply almost prohibitive computational resources. In this study, numerical predictions of atmospheric boundary layers are performed over a complex topography located in Nygårdsfjell, Norway. The Nygårdsfjell wind farm is located in a valley at approximately 420 meters above sea level surrounded by mountains in the north and south near the Swedish border. Majority of the winds are believed to be originated from Torneträsk lake in the east which is covered with ice during the winter time. The air closest to the surface on surrounding mountains gets colder and denser. The air then slides down the hill and accumulates over the lake. Later, the air spills out westward towards Ofotfjord through the broader channel that directs and transforms it into highly accelerated winds. Consequently, one of the objectives of the present article is to study the influence of local terrain on shaping these winds over the wind farm. It is worth mentioning that we are not considering any wind turbine model in the present investigation, being the main purpose to understand the influence of the local surface topography and roughness on the wind flow. Nevertheless, future research will include modeling the presence of a wind turbine and will be published elsewhere. The governing equations of the flow are solved by using a RANS approach and by considering three different two-equation turbulence models: k-omega (k–ω), k-epsilon (k–ε) and shear stress transport (SST). Furthermore, the real topographical characteristics of the terrain have been modeled by extracting the required area from the larger digital elevation model (DEM) spanning over 100 km square. The geometry is then extruded using Rhino and meshed in ANSYS Fluent. The terrain dimensions are approximately 2000×1000 meter square.

Overview of Subsynchronous Oscillation in Grid-connected Wind Farm

2020 ◽  
Vol 13 (7) ◽  
pp. 969-979
Author(s):  
Xu Pei-Zhen ◽  
Lu Yong-Geng ◽  
Cao Xi-Min
Keyword(s):  
Power Systems ◽  
Wind Turbine ◽  
Large Scale ◽  
Wind Farm ◽  
Wind Farms ◽  
Induction Generator ◽  
Future Research ◽  
Stable Operation ◽  
Subsynchronous Oscillation ◽  
Different Types

Background: Over the past few years, the subsynchronous oscillation (SSO) caused by the grid-connected wind farm had a bad influence on the stable operation of the system and has now become a bottleneck factor restricting the efficient utilization of wind power. How to mitigate and suppress the phenomenon of SSO of wind farms has become the focus of power system research. Methods: This paper first analyzes the SSO of different types of wind turbines, including squirrelcage induction generator based wind turbine (SCIG-WT), permanent magnet synchronous generator- based wind turbine (PMSG-WT), and doubly-fed induction generator based wind turbine (DFIG-WT). Then, the mechanisms of different types of SSO are proposed with the aim to better understand SSO in large-scale wind integrated power systems, and the main analytical methods suitable for studying the SSO of wind farms are summarized. Results: On the basis of results, using additional damping control suppression methods to solve SSO caused by the flexible power transmission devices and the wind turbine converter is recommended. Conclusion: The current development direction of the SSO of large-scale wind farm grid-connected systems is summarized and the current challenges and recommendations for future research and development are discussed.

scholarly journals Inter-annual variability of wind climates and wind turbine annual energy production

2018 ◽  
Author(s):  
Sara C. Pryor ◽  
Tristan J. Shepherd ◽  
Rebecca J. Barthelmie
Keyword(s):  
Standard Deviation ◽  
Wind Energy ◽  
Wind Turbine ◽  
Energy Production ◽  
Wind Farm ◽  
Wind Farms ◽  
Wind Speeds ◽  
Annual Variability ◽  
Eastern Usa

Abstract. Inter-annual variability (IAV) of expected annual energy production (AEP) from proposed wind farms plays a key role in dictating project financing. IAV in pre-construction projected AEP and the difference in 50th and 90th percentile (P50 and P90) AEP derives in part from variability in wind climates. However, the magnitude of IAV in wind speeds at/close to wind turbine hub-heights is poorly constrained and maybe overestimated by the 6 % standard deviation of annual mean wind speeds that is widely applied within the wind energy industry. Thus there is a need for improved understanding of the long-term wind resource and the inter-annual variability therein in order to generate more robust predictions of the financial value of a wind energy project. Long-term simulations of wind speeds near typical wind turbine hub-heights over the eastern USA indicate median gross capacity factors (computed using 10-minute wind speeds close to wind turbine hub-heights and the power curve of the most common wind turbine deployed in the region) that are in good agreement with values derived from operational wind farms. The IAV of annual mean wind speeds at/near to typical wind turbine hub-heights in these simulations is lower than is implied by assuming a standard deviation of 6 %. Indeed, rather than in 9 in 10 years exhibiting AEP within 0.9 and 1.1 times the long-term mean AEP, results presented herein indicate that over 90 % of the area in the eastern USA that currently has operating wind turbines simulated AEP lies within 0.94 and 1.06 of the long-term average. Further, IAV of estimated AEP is not substantially larger than IAV in mean wind speeds. These results indicate it may be appropriate to reduce the IAV applied to pre-construction AEP estimates to account for variability in wind climates, which would decrease the cost of capital for wind farm developments.

scholarly journals Optimization of Wind Turbine Interconnections in an Offshore Wind Farm Using Metaheuristic Algorithms

2020 ◽  
Vol 12 (14) ◽  
pp. 5761 ◽  
Author(s):  
Chakib El Mokhi ◽  
Adnane Addaim
Keyword(s):  
Wind Energy ◽  
Wind Turbine ◽  
Wind Farm ◽  
Renewable Energy Sources ◽  
Wind Farms ◽  
Optimization Methods ◽  
Network Routing ◽  
Metaheuristic Algorithms ◽  
Offshore Wind ◽  
Offshore Wind Farms

Wind energy is currently one of the fastest-growing renewable energy sources in the world. For this reason, research on methods to render wind farms more energy efficient is reasonable. The optimization of wind turbine positions within wind farms makes the exploitation of wind energy more efficient and the wind farms more competitive with other energy resources. The investment costs alone for substation and electrical infrastructure for offshore wind farms run around 15–30% of the total investment costs of the project, which are considered high. Optimizing the substation location can reduce these costs, which also minimizes the overall cable length within the wind farm. In parallel, optimizing the cable routing can provide an additional benefit by finding the optimal grid network routing. In this article, the authors show the procedure on how to create an optimized wind farm already in the design phase using metaheuristic algorithms. Besides the optimization of wind turbine positions for more energy efficiency, the optimization methods of the substation location and the cable routing for the collector system to avoid cable losses are also presented.

Wind resource assessment and wind farm modeling in Mossobo-Harena area, North Ethiopia

2020 ◽  
pp. 0309524X2092540
Author(s):  
Addisu Dagne Zegeye
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Turbine ◽  
Power Density ◽  
Energy Production ◽  
Wind Farm ◽  
Ground Level ◽  
Energy Potential ◽  
Mean Power ◽  
Wind Energy Potential

Although Ethiopia does not have significant fossil fuel resource, it is endowed with a huge amount of renewable energy resources such as hydro, wind, geothermal, and solar power. However, only a small portion of these resources has been utilized so far and less than 30% of the nation’s population has access to electricity. The wind energy potential of the country is estimated to be up to 10 GW. Yet less than 5% of this potential is developed so far. One of the reasons for this low utilization of wind energy in Ethiopia is the absence of a reliable and accurate wind atlas and resource maps. Development of reliable and accurate wind atlas and resource maps helps to identify candidate sites for wind energy applications and facilitates the planning and implementation of wind energy projects. The main purpose of this research is to assess the wind energy potential and model wind farm in the Mossobo-Harena site of North Ethiopia. In this research, wind data collected for 2 years from Mossobo-Harena site meteorological station were analyzed using different statistical software to evaluate the wind energy potential of the area. Average wind speed and power density, distribution of the wind, prevailing direction, turbulence intensity, and wind shear profile of the site were determined. Wind Atlas Analysis and Application Program was used to generate the generalized wind climate of the area and develop resource maps. Wind farm layout and preliminary turbine micro-sitting were done by taking various factors into consideration. The IEC wind turbine class of the site was determined and an appropriate wind turbine for the study area wind climate was selected and the net annual energy production and capacity factor of the wind farm were determined. The measured data analysis conducted indicates that the mean wind speed at 10 and 40 m above the ground level is 5.12 and 6.41 m/s, respectively, at measuring site. The measuring site’s mean power density was determined to be 138.55 and 276.52 W/m2 at 10 and 40 m above the ground level, respectively. The prevailing wind direction in the site is from east to south east where about 60% of the wind was recorded. The resource grid maps developed by Wind Atlas Analysis and Application Program on a 10 km × 10 km area at 50 m above the ground level indicate that the selected study area has a mean wind speed of 5.58 m/s and a mean power density of 146 W/m2. The average turbulence intensity of the site was found to be 0.136 at 40 m which indicates that the site has a moderate turbulence level. According to the resource assessment done, the area is classified as a wind Class IIIB site. A 2-MW rated power ENERCON E-82 E2 wind turbine which is an IEC Class IIB turbine with 82 m rotor diameter and 98 m hub height was selected for estimation of annual energy production on the proposed wind farm. 88 ENERCON E-82 E2 wind turbines were properly sited in the wind farm with recommended spacing between the turbines so as to reduce the wake loss. The rated power of the wind farm is 180.4 MW and the net annual energy production and capacity factor of the proposed wind farm were determined to be 434.315 GWh and 27.48% after considering various losses in the wind farm.

Implementation Issues in 3D Wind Flow Predictions Over Complex Terrain

2006 ◽  
Vol 128 (4) ◽  
pp. 539-553 ◽  
Author(s):  
John Prospathopoulos ◽  
Spyros G. Voutsinas
Keyword(s):  
Wind Energy ◽  
Boundary Conditions ◽  
Complex Terrain ◽  
Flow Direction ◽  
Region Of Interest ◽  
Field Measurements ◽  
Navier Stokes ◽  
Wind Flow ◽  
Computational Domain

Practical aspects concerning the use of 3D Navier-Stokes solvers as prediction tools for micro-siting of wind energy installations are considered. Micro-siting is an important issue for a successful application of wind energy in sites of complex terrain. There is a constantly increasing interest in using mean wind flow predictions based on Reynolds averaged Navier-Stokes (RANS) solvers in order to minimize the number of required field measurements. In this connection, certain numerical aspects, such as the extent of the numerical flow domain, the choice of the appropriate inflow boundary conditions, and the grid resolution, can decisively affect the quality of the predictions. In the present paper, these aspects are analyzed with reference to the Askervein hill data base of full scale measurements. The objective of the work is to provide guidelines with respect to the definition of appropriate boundary conditions and the construction of an adequate and effective computational grid when a RANS solver is implemented. In particular, it is concluded that (a) the ground roughness affects the predictions significantly, (b) the computational domain should have an extent permitting the full development of the flow before entering the region of interest, and (c) the quality of the predictions at the local altitude maxima depends on the grid density in the main flow direction.

scholarly journals Wake and Turbulence Analysis for Wind Turbine Layouts in an Island

2018 ◽  
Vol 64 ◽  
pp. 06010
Author(s):  
Bachhal Amrender Singh ◽  
Vogstad Klaus ◽  
Lal Kolhe Mohan ◽  
Chougule Abhijit ◽  
Beyer Hans George
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Energy Production ◽  
Wind Farm ◽  
Full Length Paper ◽  
Turbulence Analysis ◽  
Wake Model ◽  
Wind Resources

There is a big wind energy potential in supplying the power in an island and most of the islands are off-grid. Due to the limited area in island(s), there is need to find appropriate layout / location for wind turbines suited to the local wind conditions. In this paper, we have considered the wind resources data of an island in Trøndelag region of the Northern Norway, situated on the coastal line. The wind resources data of this island have been analysed for wake losses and turbulence on wind turbines for determining appropriate locations of wind turbines in this island. These analyses are very important for understanding the fatigue and mechanical stress on the wind turbines. In this work, semi empirical wake model has been used for wake losses analysis with wind speed and turbine spacings. The Jensen wake model used for the wake loss analysis due to its high degree of accuracy and the Frandsen model for characterizing the turbulent loading. The variations of the losses in the wind energy production of the down-wind turbine relative to the up-wind turbine and, the down-stream turbulence have been analysed for various turbine distances. The special emphasis has been taken for the case of wind turbine spacing, leading to the turbulence conditions for satisfying the IEC 61400-1 conditions to find the wind turbine layout in this island. The energy production of down-wind turbines has been decreased from 2 to 20% due to the lower wind speeds as they are located behind up-wind turbine, resulting in decreasing the overall energy production of the wind farm. Also, the higher wake losses have contributed to the effective turbulence, which has reduced the overall energy production from the wind farm. In this case study, the required distance for wind turbines have been changed to 6 rotor diameters for increasing the energy gain. From the results, it has been estimated that the marginal change in wake losses by moving the down-stream wind turbine by one rotor diameter distance has been in the range of 0.5 to 1% only and it is insignificant. In the full-length paper, the wake effects with wind speed variations and the wind turbine locations will be reported for reducing the wake losses on the down-stream wind turbine. The Frandsen model has been used for analysing turbulence loading on the down-stream wind turbine as per IEC 61400-1 criteria. In larger wind farms, the high turbulence from the up-stream wind turbines increases the fatigues on the turbines of the wind farm. In this work, we have used the effective turbulence criteria at a certain distance between up-stream and down-stream turbines for minimizing the fatigue load level. The sensitivity analysis on wake and turbulence analysis will be reported in the full-length paper. Results from this work will be useful for finding wind farm layouts in an island for utilizing effectively the wind energy resources and electrification using wind power plants.

scholarly journals Three-Dimensional Wind Field Construction and Wind Turbine Siting in an Urban Environment

Fluids ◽  
2020 ◽  
Vol 5 (3) ◽  
pp. 137 ◽  
Author(s):  
Mingrui Liu ◽  
Xiuling Wang
Keyword(s):  
Wind Turbine ◽  
Urban Environment ◽  
Wind Field ◽  
Three Dimensional ◽  
Turbulence Models ◽  
Reynolds Stress Model ◽  
Urban Environments ◽  
Urban Region ◽  
Wind Flow ◽  
Simulation Results

Three-dimensional urban wind field construction plays an important role not only in the analysis of pedestrian levels of comfort but also in the effectiveness of harnessing wind energy in an urban environment. However, it is challenging to accurately simulate urban wind flow due to the complex land use in urban environments. In this study, a three-dimensional numerical model was developed for urban wind flow construction. To obtain an accurate urban wind field, various turbulence models, including the Reynolds stress model (RSM), k-ω shear stress transport (SST), realizable k-ε, and (Re-Normalisation Group (RNG) k-ε models were tested. Simulation results were compared with experimental data in the literature. The RSM model showed promising potential in simulating urban wind flow. The model was then adopted to simulate urban wind flow for Purdue University Northwest, which is located in the Northwest Indiana urban region. Based on the simulation results, the optimal location was identified for urban wind turbine siting.

scholarly journals Wind Turbine Wake Modeling in Accelerating Wind Field: A Preliminary Study on a Two-Dimensional Hill

Fluids ◽  
2019 ◽  
Vol 4 (3) ◽  
pp. 153 ◽  
Author(s):  
Omar M. A. M. Ibrahim ◽  
Shigeo Yoshida ◽  
Masahiro Hamasaki ◽  
Ao Takada
Keyword(s):  
Wind Speed ◽  
Wind Tunnel ◽  
Wind Turbine ◽  
Wind Field ◽  
Complex Terrain ◽  
Wind Farm ◽  
Wind Tunnel Test ◽  
Two Dimensional ◽  
Preliminary Study ◽  
Wake Model

Complex terrain can influence wind turbine wakes and wind speed profiles in a wind farm. Consequently, predicting the performance of wind turbines and energy production over complex terrain is more difficult than it is over flat terrain. In this preliminary study, an engineering wake model, that considers acceleration on a two-dimensional hill, was developed based on the momentum theory. The model consists of the wake width and wake wind speed. The equation to calculate the rotor thrust, which is calculated by the wake wind speed profiles, was also formulated. Then, a wind-tunnel test was performed in simple flow conditions in order to investigate wake development over a two-dimensional hill. After this the wake model was compared with the wind-tunnel test, and the results obtained by using the new wake model were close to the wind-tunnel test results. Using the new wake model, it was possible to estimate the wake shrinkage in an accelerating two-dimensional wind field.

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