Analytical Model for the Wind Farm Capacity Factor Based on Local Wind Characteristics

2021 ◽  
Author(s):  
Vinicius de Lira Teixeira ◽  
Annibal Hetem ◽  
Gabriel Rodrigues Bruzinga ◽  
Ahda Pionkoski Grilo Pavani ◽  
Julio Carlos Teixeira
Keyword(s):  
Analytical Model ◽  
Wind Farm ◽  
Capacity Factor ◽  
Local Wind ◽  
Wind Characteristics

Does wind speed effects performance and cost of energy? A case study of wind farm

2020 ◽  
Vol 14 (5) ◽  
pp. 953-974
Author(s):  
Zahid Hussain Hulio ◽  
Wei Jiang
Keyword(s):  
Renewable Energy ◽  
Wind Speed ◽  
Wind Farm ◽  
Power Coefficient ◽  
Local Wind ◽  
Content Type ◽  
Wind Speeds ◽  
Cost Of Energy ◽  
Wind Characteristics ◽  
The Cost

Purpose The rapid rising of renewable energy sources particularly wind energy cannot be ignored. The numerical increase in wind energy farms throughout the world is the best example. The purpose of this paper is to assess the basic question of whether wind characteristics affect the performance and cost of energy. The importance of this question cannot be ruled out while comparing renewable energy to a conventional form of energy more specifically especially for the developing country where the cost of energy is very high. Design/methodology/approach The research design of this paper is consists of an assessment of local wind characteristics of the wind farm site using Weibull k and c parameters. The performance model is used to assess the performance of the wind turbine (WT) corresponding to local wind characteristics. The wind correlation with WT in terms of changing wind speed has been assessed to quantify the effects of wind speed on the WT behavior and failure of WT components. Similarly, the power curve of WT is assessed and compared with the International Electrotechnical Commission standards 61400-12-2. The WT power coefficient and tip speed ratio corresponding to wind speed is also investigated. The energy volume and cost of energy lost model is used to determine the cost and volume loss of energy/kWh of the wind farm. Findings The findings of practical wind farms showed that the wind conditions of the site are showing a strong tendency that can be determined from the results of Weibull k and c parameters. The k and c parameters are observed to be 3.44 and 9.16 m/s, respectively, for a period of a year. The standard deviation is observed to be 2.56 for a period of a year. WT shows the efficient behavior can be obtained from the power coefficient and tip speed of WT at different wind speeds. Also, wind farm observation showed that to be some increasing wind speed cause of based WT component failures. The results of energy volume and cost/kWh assessment showed that the major portion of energy volume and cost of energy is lost owing to network, voltage dip and frequency surge, electrical and mechanical components failures. Originality/value Generally, it can be concluded that the WTs are now able to cope with variable wind speeds. However, the results of this paper are showing that WT performance and availability decreased due to increased wind speeds. It can also be a reason to decreased volume and increase the cost of energy/kWh.

scholarly journals Experimental Study on Wake Evolution of a 1.5 MW Wind Turbine in a Complex Terrain Wind Farm Based on LiDAR Measurements

2020 ◽  
Vol 12 (6) ◽  
pp. 2467 ◽  
Author(s):  
Fei Zhao ◽  
Yihan Gao ◽  
Tengyuan Wang ◽  
Jinsha Yuan ◽  
Xiaoxia Gao
Keyword(s):  
Wind Speed ◽  
Wind Shear ◽  
Wind Farm ◽  
Wind Farms ◽  
Field Measurements ◽  
Development Trend ◽  
Asymmetric Distribution ◽  
Lidar Measurements ◽  
Wind Characteristics ◽  
The Development Trend

To study the wake development characteristics of wind farms in complex terrains, two different types of Light Detection and Ranging (LiDAR) were used to conduct the field measurements in a mountain wind farm in Hebei Province, China. Under two different incoming wake conditions, the influence of wind shear, terrain and incoming wind characteristics on the development trend of wake was analyzed. The results showed that the existence of wind shear effect causes asymmetric distribution of wind speed in the wake region. The relief of the terrain behind the turbine indicated a subsidence of the wake centerline, which had a linear relationship with the topography altitudes. The wake recovery rates were calculated, which comprehensively validated the conclusion that the wake recovery rate is determined by both the incoming wind turbulence intensity in the wake and the magnitude of the wind speed.

scholarly journals An Analytical Model for the Regeneration of Wind after Exiting a Wind Farm

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2071
Author(s):  
Brian Fiedler
Keyword(s):  
Boundary Layer ◽  
Pressure Gradient ◽  
Atmospheric Boundary Layer ◽  
Linear Model ◽  
Analytical Model ◽  
Environmental Conditions ◽  
Wind Farm ◽  
Length Scale ◽  
Equilibrium Calculation ◽  
Friction Pressure

The simplest model for an atmospheric boundary layer assumes a uniform steady wind over a certain depth, of order 1 km, with the forces of friction, pressure gradient and Coriolis in balance. A linear model is here employed for the adjustment of wind to this equilibrium, as the wake of a very wide wind farm. A length scale is predicted for the exponential adjustment to equilibrium. Calculation of this length scale is aided by knowledge of the angle for which the wind would normally cross the isobars in environmental conditions in the wake.

scholarly journals Assessment of Wind Characteristics and Wind Power Potential of Gharo, Pakistan

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Zahid Hussain Hulio
Keyword(s):  
Wind Turbine ◽  
Wind Power ◽  
Frequency Distribution ◽  
Cost Estimation ◽  
Wind Farm ◽  
Research Work ◽  
Economic Assessment ◽  
High Energy ◽  
Energy Yield ◽  
Wind Characteristics

The objective of this research work is to assess the wind characteristics and wind power potential of Gharo site. The wind parameters of the site have been used to calculate the wind power density, annual energy yield, and capacity factors at 10, 30, and 50 m. The wind frequency distribution including seasonal as well as percentage of seasonal frequency distribution has been investigated to determine accurately the wind power of the site. The coefficient of variation is calculated at three different heights. Also, economic assessment per kWh of energy has been carried out. The site-specific annual mean wind speeds were 6.89, 5.85, and 3.85 m/s at 50, 30, and 10 m heights with corresponding standard deviations of 2.946, 2.489, and 2.040. The mean values of the Weibull k parameter are estimated as 2.946, 2.489, and 2.040 while those of scale parameter are estimated as 7.634, 6.465, and 4.180 m/s at 50, 30, and 10 m, respectively. The respective mean wind power and energy density values are found to be 118.3, 92.20, and 46.10 W/m2 and 1036.6, 807.90, and 402.60 kWh/m2. As per cost estimation of wind turbines, the wind turbine WT-C has the lowest cost of US$ Cents 0.0346/kWh and highest capacity factors of 0.3278 (32.78%). Wind turbine WT-C is recommended for this site for the wind farm deployment due to high energy generation and minimum price of energy. The results show the appropriateness of the methodology for assessing the wind speed and economic assessment at the lowest price of energy.

scholarly journals Selecting and testing of wind turbine blades of the local-wood growing fastly on local wind characteristics

2018 ◽  
Vol 105 ◽  
pp. 012095 ◽  
Author(s):  
Adi Surjosatyo ◽  
Bagus Rizky Dewantoro ◽  
Budiman R Saragih ◽  
Filbert Nainggolan ◽  
Wahyu Dwianto ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Turbine Blades ◽  
Local Wind ◽  
Wind Turbine Blades ◽  
Wind Characteristics

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.

Wind energy resource assessment of Kütahya, Turkey using WAsP and layout optimization

2020 ◽  
pp. 095765092093603
Author(s):  
Onur Koşar ◽  
Mustafa Arif Özgür
Keyword(s):  
Wind Speed ◽  
Wind Turbines ◽  
Wind Farm ◽  
Real Life ◽  
Energy Resource ◽  
Resource Assessment ◽  
Capacity Factor ◽  
Strong Wind ◽  
Wind Potential ◽  
Shear Turbulence

Kütahya is considered as a candidate region for a wind farm investment due to Turkey's 2023 energy targets and its proximity to other wind farm investments. In this study, two years of wind data collected from a hill near the Evliya Çelebi Campus of Kütahya Dumlupınar University was used to evaluate the wind farm potential of Kütahya. First, the wind speed, wind direction, wind shear, turbulence intensity and wind speed ramp characteristics were determined. Second, the WAsP software was used to create a wind atlas for the region. Three sites with strong wind potential were evaluated. A techno-economic analysis was conducted using five types of wind turbines selected from the WAsP database. Third, optimization of a wind farm layout was conducted by considering different hub height options for 14 commercial wind turbines using MATLAB software. It was shown theoretically that a wind farm with a power capacity of 25 MW can operate with a capacity factor of 35%. However, due to the relatively high topographical ruggedness index on the wind farm site, the calculated value for the capacity factor could not be reached in a real-life application.

scholarly journals Field Measurements of Wind Characteristics Using LiDAR on a Wind Farm with Downwind Turbines Installed in a Complex Terrain Region

Energies ◽  
2020 ◽  
Vol 13 (19) ◽  
pp. 5135
Author(s):  
Tetsuya Kogaki ◽  
Kenichi Sakurai ◽  
Susumu Shimada ◽  
Hirokazu Kawabata ◽  
Yusuke Otake ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Farm ◽  
Field Experiments ◽  
Wind Farms ◽  
Field Measurements ◽  
Horizontal Wind ◽  
Flow Distortion ◽  
Horizontal Wind Speed ◽  
Vertical Profiling ◽  
Wind Characteristics

Downwind turbines have favorable characteristics such as effective energy capture in up-flow wind conditions over complex terrains. They also have reduced risk of severe accidents in the event of disruptions to electrical networks during strong storms due to the free-yaw effect of downwind turbines. These favorable characteristics have been confirmed by wind-towing tank experiments and computational fluid dynamics (CFD) simulations. However, these advantages have not been fully demonstrated in field experiments on actual wind farms. In this study—although the final objective was to demonstrate the potential advantages of downwind turbines through field experiments—field measurements were performed using a vertical-profiling light detection and ranging (LiDAR) system on a wind farm with downwind turbines installed in complex terrains. To deduce the horizontal wind speed, vertical-profiling LiDARs assume that the flow of air is uniform in space and time. However, in complex terrains and/or in wind farms where terrain and/or wind turbines cause flow distortion or disturbances in time and space, this assumption is not valid, resulting in erroneous wind speed estimates. The magnitude of this error was evaluated by comparing LiDAR measurements with those obtained using a cup anemometer mounted on a meteorological mast and detailed analysis of line-of-sight wind speeds. A factor that expresses the nonuniformity of wind speed in the horizontal measurement plane of vertical-profiling LiDAR is proposed to estimate the errors in wind speed. The possibility of measuring and evaluating various wind characteristics such as flow inclination angles, turbulence intensities, wind shear and wind veer, which are important for wind turbine design and for wind farm operation is demonstrated. However, additional evidence of actual field measurements on wind farms in areas with complex terrains is required in order to obtain more universal and objective evaluations.

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