scholarly journals Comparative LCA of technology improvement opportunities for a 1.5-MW wind turbine in the context of an onshore wind farm

2017 ◽  
Vol 20 (1) ◽  
pp. 173-190 ◽  
Author(s):  
Matthew Ozoemena ◽  
Wai M. Cheung ◽  
Reaz Hasan
Keyword(s):  
Wind Turbine ◽  
Wind Farm ◽  
Onshore Wind ◽  
Comparative Lca ◽  
Technology Improvement ◽  
Technology Improvement Opportunities

Flow Simulation Around a Rim-Driven Wind Turbine and in Its Wake

2013 ◽  
Author(s):  
Bryan E. Kaiser ◽  
Svetlana V. Poroseva ◽  
Michael A. Snider ◽  
Rob O. Hovsapian ◽  
Erick Johnson
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Farm ◽  
Flow Simulation ◽  
Wind Farms ◽  
Sensitivity Study ◽  
Onshore Wind ◽  
Flow Simulations ◽  
Turbine Design ◽  
The Impact

A relatively high free stream wind velocity is required for conventional horizontal axis wind turbines (HAWTs) to generate power. This requirement significantly limits the area of land for viable onshore wind farm locations. To expand a potential for wind power generation and an area suitable for onshore wind farms, new wind turbine designs capable of wind energy harvesting at low wind speeds are currently in development. The aerodynamic characteristics of such wind turbines are notably different from industrial standards. The optimal wind farm layout for such turbines is also unknown. Accurate and reliable simulations of a flow around and behind a new wind turbine design should be conducted prior constructing a wind farm to determine optimal spacing of turbines on the farm. However, computations are expensive even for a flow around a single turbine. The goal of the current study is to determine a set of simulation parameters that allows one to conduct accurate and reliable simulations at a reasonable cost of computations. For this purpose, a sensitivity study on how the parameters variation influences the results of simulations is conducted. Specifically, the impact of a grid refinement, grid stretching, grid cell shape, and a choice of a turbulent model on the results of simulation of a flow around a mid-sized Rim Driven Wind Turbine (U.S. Patent 7399162) and in its near wake is analyzed. This wind turbine design was developed by Keuka Energy LLC. Since industry relies on commercial software for conducting flow simulations, STAR-CCM+ software [1] was used in our study. A choice of a turbulence model was made based on the results from our previous sensitivity study of flow simulations over a rotating disk [2].

scholarly journals Local turbulence parameterization improves the Jensen wake model and its implementation for power optimization of an operating wind farm

2018 ◽  
Author(s):  
Thomas Duc ◽  
Olivier Coupiac ◽  
Nicolas Girard ◽  
Gregor Giebel ◽  
Tuhfe Göçmen
Keyword(s):  
Wind Turbine ◽  
Wind Farm ◽  
Decay Constant ◽  
Wind Farms ◽  
Power Production ◽  
Original Model ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Onshore Wind ◽  
Wake Model

Abstract. In this paper, a new calculation procedure to improve the accuracy of the Jensen wake model for operating wind farms is proposed. In this procedure the wake decay constant is updated locally at each wind turbine based on the turbulence intensity measurement provided by the nacelle anemometer. This procedure was tested against experimental data at onshore wind farm La Sole du Moulin Vieux (SMV) in France and the offshore wind farm Horns Rev-I in Denmark. Results indicate that the wake deficit at each wind turbine is described more accurately than when using the original model, reducing the error from 15–20 % to approximately 5 %. Furthermore, this new model properly calibrated for the SMV wind farm is then used for coordinated control purposes. Assuming an axial induction control strategy, and following a model predictive approach, new power settings leading to an increased overall power production of the farm are derived. Power gains found are in the order of 2.5 % for a two wind turbine case with close spacing and 1 to 1.5 % for a row of five wind turbines with a larger spacing. Finally, the uncertainty of the updated Jensen model is quantified considering the model inputs. When checked against the predicted power gain, the uncertainty of the model estimations is seen to be excessive, reaching approximately 4 %, which indicates the difficulty of field observations for such a gain. Nevertheless, the optimized settings are to be implemented during a field test campaign at SMV wind farm in scope of the national project SMARTEOLE.

Analysis of Wind Turbine Wakes Through Time-Resolved and SCADA Data of an Onshore Wind Farm

2018 ◽  
Vol 140 (4) ◽  
Author(s):  
Francesco Castellani ◽  
Paolo Sdringola ◽  
Davide Astolfi
Keyword(s):  
Wind Turbine ◽  
Complex Terrain ◽  
Spectral Properties ◽  
Wind Farm ◽  
Point Of View ◽  
Test Case ◽  
Time Resolved ◽  
Onshore Wind ◽  
Yaw Control ◽  
Different Levels

An experimental study is conducted on wind turbine wakes and their effects on wind turbine performances and operation. The test case is a wind farm located on a moderately complex terrain, featuring four turbines with 2 MW of rated power each. Two interturbine distances characterize the layout: 4 and 7.5 rotor diameters. Therefore, it is possible to study different levels of wake recovery. The processed data are twofold: time-resolved series, whose frequency is in the order of the hertz, and supervisory control and data acquisition (SCADA) data with 10 min of sampling time. The wake fluctuations are investigated adopting a “slow” point of view (SCADA), on a catalog of wake events spanned over a long period, and a “fast” point of view of selected time-resolved series of wake events. The power ratios between downstream and upstream wind turbines show that the time-resolved data are characterized by a wider range of fluctuations with respect to the SCADA. Moreover, spectral properties are assessed on the basis of time-resolved data. The combination of meandering wind and yaw control is observed to be associated with different spectral properties depending on the level of wake recovery.

Aerodynamic Rotor Performance of a 3300-kW Modern Commercial Large-Scale Wind Turbine Installed in a Wind Farm

2020 ◽  
Vol 143 (3) ◽  
Author(s):  
Mehmet Bilgili ◽  
Mehmet Tontu ◽  
Besir Sahin
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Large Scale ◽  
Wind Farm ◽  
Thrust Force ◽  
Speed Ratio ◽  
Flow Angle ◽  
Onshore Wind ◽  
Turbine Performance

Abstract Wind turbine technology in the world has been developed by continuously improving turbine performance, design, and efficiency. Over the last 40 years, the rated capacity and dimension of the commercial wind turbines have increased dramatically, so the energy cost has declined significantly, and the industry has moved from an idealistic position to an acknowledged component of the power generation industry. For this reason, a thorough examination of the aerodynamic rotor performance of a modern large-scale wind turbine working on existing onshore wind farms is critically important to monitor and control the turbine performance and also for forecasting turbine power. This study focuses on the aerodynamic rotor performance of a 3300-kW modern commercial large-scale wind turbine operating on an existing onshore wind farm based on the measurement data. First, frequency distributions of wind speeds and directions were obtained using measurements over one year. Then, wind turbine parameters such as free-stream wind speed (U∞), far wake wind speed (UW), axial flow induction factor (a), wind turbine power coefficient (CP), tangential flow induction factor (a′), thrust force coefficient (CT), thrust force (T), tip-speed ratio (λ), and flow angle (ϕ) were calculated using the measured rotor disc wind speed (UD), atmospheric air temperature (Tatm), turbine rotational speed (Ω), and turbine power output (P) parameters. According to the results obtained, the maximum P, CP, CT, T, and Ω were calculated as approximately 3.3 MW, 0.45, 0.6, 330 kN, and 12.9 rpm, respectively, while the optimum λ, ϕ, U∞, and Ω for the maximum CP were determined as 7.5–8.5, 6–6.3°, 5–10 m/s, and 6–10 rpm, respectively. These calculated results can contribute to assessing the economic and technical feasibility of modern commercial large-scale wind turbines and supporting future developments in wind energy and turbine technology.

scholarly journals Wind Turbine Yaw Control Optimization and Its Impact on Performance

Machines ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 41 ◽  
Author(s):  
Davide Astolfi ◽  
Francesco Castellani ◽  
Francesco Natili
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Farm ◽  
Principal Component Regression ◽  
Principal Component ◽  
Energy Conversion Efficiency ◽  
Test Case ◽  
Yaw Control ◽  
Control Optimization ◽  
Technology Improvement

The optimization of wind energy conversion efficiency has been recently boosting the technology improvement and the scientific comprehension of wind turbines. In this context, the yawing behavior of wind turbines has become a key topic: the yaw control can actually be exploited for optimization at the level of single wind turbine and of wind farm (for example, through active control of wakes). On these grounds, this work is devoted to the study of the yaw control optimization on a 2 MW wind turbine. The upgrade is estimated by analysing the difference between the measured post-upgrade power and a data driven model of the power according to the pre-upgrade behavior. Particular attention has therefore been devoted to the formulation of a reliable model for the pre-upgrade power of the wind turbine of interest, as a function of the operation variables of all the nearby wind turbines in the wind farm: the high correlation between the possible covariates of the model indicates that Principal Component Regression (PCR) is an adequate choice. Using this method, the obtained result for the selected test case is that the yaw control optimization provides a 1% of annual energy production improvement. This result indicates that wind turbine control optimization can non-negligibly improve the efficiency of wind turbine technology.

scholarly journals Local turbulence parameterization improves the Jensen wake model and its implementation for power optimization of an operating wind farm

2019 ◽  
Vol 4 (2) ◽  
pp. 287-302 ◽  
Author(s):  
Thomas Duc ◽  
Olivier Coupiac ◽  
Nicolas Girard ◽  
Gregor Giebel ◽  
Tuhfe Göçmen
Keyword(s):  
Wind Turbine ◽  
Wind Farm ◽  
Decay Constant ◽  
Wind Farms ◽  
Power Production ◽  
Original Model ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Onshore Wind ◽  
Wake Model

Abstract. In this paper, a new calculation procedure to improve the accuracy of the Jensen wake model for operating wind farms is proposed. In this procedure, the wake decay constant is updated locally at each wind turbine based on the turbulence intensity measurement provided by the nacelle anemometer. This procedure was tested against experimental data at the Sole du Moulin Vieux (SMV) onshore wind farm in France and the Horns Rev-I offshore wind farm in Denmark. Results indicate that the wake deficit at each wind turbine is described more accurately than when using the original model, reducing the error from 15 % to 20 % to approximately 5 %. Furthermore, this new model properly calibrated for the SMV wind farm is then used for coordinated control purposes. Assuming an axial induction control strategy, and following a model predictive approach, new power settings leading to an increased overall power production of the farm are derived. Power gains found are on the order of 2.5 % for a two-wind-turbine case with close spacing and 1 % to 1.5 % for a row of five wind turbines with a larger spacing. Finally, the uncertainty of the updated Jensen model is quantified considering the model inputs. When checked against the predicted power gain, the uncertainty of the model estimations is seen to be excessive, reaching approximately 4 %, which indicates the difficulty of field observations for such a gain. Nevertheless, the optimized settings are to be implemented during a field test campaign at SMV wind farm in the scope of the national project SMARTEOLE.

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