scholarly journals Modeling of power curves for industrial wind turbines of specified unit size

2021 ◽  
Vol 1 (65) ◽  
Author(s):  
В. Є. Терехов ◽  
В. С. Подгуренко
Keyword(s):  
Author(s):  
Sandip Kale ◽  
S. N. Sapali

Micro wind turbines installed in various applications, experience average wind speed for most of the time during operations. Power produced by the wind turbine is proportional to the cubic power of the wind velocity and a small increase in wind velocity results increases power output significantly. The approach wind velocity can be increased by covering traditional wind turbine with a diffuser. Researchers are continuously working to develop a compact, lightweight, cost effective and feasible diffuser for wind turbines. The present work carried out to develop a diffuser with these stated objectives. A compact, lightweight inclined flanged diffuser developed for a micro wind turbine. Bare micro wind turbine and wind turbine covered with developed efficient inclined flanged diffuser tested in the field as per International Electrotechnical Commission (IEC) standards and results presented in the form of power curves. The prediction of annual energy production for both wind turbines determined as per IEC standards.


Resources ◽  
2016 ◽  
Vol 5 (4) ◽  
pp. 44
Author(s):  
Masaō Ashtine ◽  
Richard Bello ◽  
Kaz Higuchi

2017 ◽  
Vol 2 (2) ◽  
pp. 547-567 ◽  
Author(s):  
Mads M. Pedersen ◽  
Torben J. Larsen ◽  
Helge Aa. Madsen ◽  
Gunner Chr. Larsen

Abstract. In this paper an alternative method to evaluate power performance and loads on wind turbines using a blade-mounted flow sensor is investigated. The hypothesis is that the wind speed measured at the blades has a high correlation with the power and loads such that a power or load assessment can be performed from a few hours or days of measurements.In the present study a blade-mounted five-hole pitot tube is used as the flow sensor as an alternative to the conventional approach, where the reference wind speed is either measured at a nearby met mast or on the nacelle using lidar technology or cup anemometers. From the flow sensor measurements, an accurate estimate of the wind speed at the rotor plane can be obtained. This wind speed is disturbed by the presence of the wind turbine, and it is therefore different from the free-flow wind speed. However, the recorded wind speed has a high correlation with the actual power production as well as the flap-wise loads as it is measured close to the blade where the aerodynamic forces are acting.Conventional power curves are based on at least 180 h of 10 min mean values, but using the blade-mounted flow sensor both the observation average time and the overall assessment time can potentially be shortened. The basis for this hypothesis is that the sensor is able to provide more observations with higher accuracy, as the sensor follows the rotation of the rotor and because of the high correlation between the flow at the blades and the power production. This is the research question addressed in this paper.The method is first tested using aeroelastic simulations where the dependence of the radial position and effect of multiple blade-mounted flow sensors are also investigated. Next the method is evaluated on the basis of full-scale measurements on a pitch-regulated, variable-speed 3.6 MW wind turbine.It is concluded that the wind speed derived from the blade-mounted flow sensor is highly correlated with the power and flap-wise bending moment and that the method has advantages over the traditional approach where the met-mast wind speed is used as reference, e.g. the capability of measuring the shear, veer and turbulence. The aeroelastic simulations show that the assessment time can be reduced, but this reduction cannot be confirmed from the current measurement database due to sensor problems and practical circumstances. Measuring the wind speed at the rotor plane comes with a price as the wind speed is affected by the induction which may be sensitive to the changes you want to evaluate, e.g. different vortex generator configurations. Furthermore it is concluded that a robust instrument and measurement system is required to obtain accurate and reliable wind speed recordings from pitot-tube measurements.


Author(s):  
Al‐Motasem Aldaoudeyeh ◽  
Khaled Alzaareer ◽  
Salman Harasis ◽  
Zeyad Al‐Odat ◽  
Mohammad Obeidat ◽  
...  

2014 ◽  
Vol 555 ◽  
pp. 012029 ◽  
Author(s):  
M Dörenkämper ◽  
J Tambke ◽  
G Steinfeld ◽  
D Heinemann ◽  
M Kühn

Energies ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 891 ◽  
Author(s):  
Mohsen Vahidzadeh ◽  
Corey D. Markfort

Power generation from wind farms is traditionally modeled using power curves. These models are used for assessment of wind resources or for forecasting energy production from existing wind farms. However, prediction of power using power curves is not accurate since power curves are based on ideal uniform inflow wind, which do not apply to wind turbines installed in complex and heterogeneous terrains and in wind farms. Therefore, there is a need for new models that account for the effect of non-ideal operating conditions. In this work, we propose a model for effective axial induction factor of wind turbines that can be used for power prediction. The proposed model is tested and compared to traditional power curve for a 2.5 MW horizontal axis wind turbine. Data from supervisory control and data acquisition (SCADA) system along with wind speed measurements from a nacelle-mounted sonic anemometer and turbulence measurements from a nearby meteorological tower are used in the models. The results for a period of four months showed an improvement of 51% in power prediction accuracy, compared to the standard power curve.


2014 ◽  
Vol 51 (4) ◽  
pp. 15-24
Author(s):  
A. Mutule ◽  
O. Kochukov

Abstract An approach is proposed to the modelling of wind farms in the electric power system long-term planning. It allows a specialist to perform calculations based on scanty information and offers a set of ready-to-use data for easy, fast, and precise modelling. The authors exemplify the calculations of wind speed probability density and power curves and give an idea for relevant corrections. They also show how to pass from a single wind turbine model to the unified model of multiple wind turbines which would meet the requirements of long-term planning tasks. The paper presents the data on wind farms that are operating in UK and Oceania


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