The is a set of design requirements made to ensure that wind turbines are appropriately engineered against damage from hazards within the planned lifetime. The standard concerns most aspects of the turbine life from site conditions before construction, to turbine components being tested,  assembled and operated. Wind turbines are capital intensive, and are usually purchased before they are being erected and commissioned. Some of these standards provide technical conditions verifiable by an independent, third party , and as such are necessary in order to make business agreements so wind turbines can be financed and erected. IEC started standardizing international certification on the subject in , and the first standard appeared in The common set of standards sometimes replace the various national standards, forming a basis for global certification.
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Samuel P. Bradney 1 , Tania P. Urmee 2 , Jonathan Whale 2 and Philip D. Clausen 1. Detailed wind measurements were acquired at two built environment sites: from the rooftop of a Bunnings Ltd. For both sites, IEC underestimates the turbulence intensity for the majority of the measured wind speeds. A detailed aeroelastic model was built in FAST using the assumed wind field from IEC and the measured wind fields from PK and Callaghan as an input to predict key turbine performance parameters.
The results of this analysis show a modest increase in the predicted mean power for the higher turbulence regimes of PK and Callaghan as well as higher variation in output power. Predicted mean rotor thrust and blade flapwise loading showed a minor increase due to higher turbulence, with mean predicted torque almost identical but with increased variations due to higher turbulence.
Time series plots for blade flapwise moments and power spectral density plots in the frequency domain show consistently higher blade flapwise bending moments for the Callaghan site with both the sites showing a once-per-revolution response. The standard describes a wind field model, based on open terrain wind conditions to determine wind fluctuations and extreme wind events that can be used as input into aeroelastic codes to allow engineers to predict the performance and structural loading on the turbine for a given site wind condition.
Urban wind regimes are characterized as having low wind speeds with increased turbulent flow due to high surface roughness, atmospheric instability, interaction of the oncoming wind profile with surrounding obstructions, sudden changes in wind speed and direction, etc. Such environments induce stochastic variation in wind speed and turbulence intensity that is difficult to estimate. The existing wind field model in IEC appears to be inadequate when applied to turbines sited in the built environment since it does not incorporate all the design models and wind dynamics related to such highly turbulent sites.
For rooftop based small horizontal axis wind turbines, the rapidly fluctuating gust imposes high dynamic loading on the turbine and can cause resonance. IEC allows for the use of either von Karman or Kaimal spectral density functions to simulate the flow fields, calculate design loads and predict loadings on the turbine. Both of these turbulence models are based on the wind conditions pertaining to open terrain.
Moreover, IEC designates small wind turbine operation into four classes that cover most operating sites. Researchers at Murdoch University have studied the characteristics of the urban wind on a 1.
Part of their work was to investigate if the von Karman and Kaimal models are appropriate for use in the design of SWTs installed in the built environment, and to compare the assumed turbulent spectra with those of the actual flow conditions. The authors observed that both the standard models underestimated he magnitude of the measured values for all wind components and proposed a corrected Kaimal model for rooftop sites in the built environment.
Both groups have collected a significant amount of wind data at their respective sites. The aims of this study are to compare the measured turbulent inflow wind conditions at two sites in the built environment with the modelled wind conditions from IEC This process is considered analogous to using aeroelastic codes to determine small wind turbine design loads from measured wind field conditions, compared to conditions simulated by the IEC standard.
To characterize the turbulent velocity field and estimate dynamic loads, the probability density function of wind fluctuations is often expressed as a Gaussian distribution. The characteristic longitudinal turbulence intensity is expressed as the 90th percentile of longitudinal turbulence intensity measurements binned with respect to wind speed, assuming a Gaussian distribution.
From IEC , I 15 and a are 0. These values are specified for all small wind turbine classes despite the fact they are site dependant. This simplification allows designers to use typical values instead of undertaking expensive monitoring campaigns at specific sites. Equation 1 thereby reduces to: 2 Equation 2 can be rearranged in terms of longitudinal turbulence intensity, I u , as follows: 3. Equation 3 was proposed by Stork et al.
Figure 2 shows the average min wind speed and its longitudinal standard deviation at both PK and UoN. Figure 2 also shows a number of extreme events with large standard deviation at both sites. The low turbulence at low wind speed evident in Figure 2a is likely due to inertial effects of the cup anemometer at low wind speeds. Figure 2 is produced from min averaged data, i. Key to the development of this aeroelastic model is the input of aerofoil properties that govern rotor performance, turbine dynamics, and output power.
Typical operational Reynolds numbers range from 66, at the blade root during rotor start-up to , at the blade tip at rated wind speed conditions. In a similar manner to the blade aerofoil data, the lift and drag data for the delta wing tailfin was input into the model using data presented in [ 25 ]; the tail fin is used as a means of passive yaw control to align the rotor plane to the direction of the inlet wind. Structural parameters of the wind turbine blades and tower need to be inputted into the model.
Both the blade and tower are considered to behave as cantilevered beams which are rigidly attached to the rotor hub and ground respectively. Inputs for these structural elements consist of sectional stiffness, linear density, and beam mode shapes which are used to deduce deflections and dynamic structural response.
Stiffness properties of the tower were also imported into FAST. The changed natural frequency of vibrations and mode shapes were incorporated into the model. Other parameters used for model input include the inertia of the rotor, drive train inertia, and inertia of the generator. Furthermore, the net mass and inertia of the nacelle about the tower axis were also a model input to determine yaw behaviour due to the tailfin aerodynamic response.
This wind turbine utilises a self-excited induction generator SEIG which operates at variable rotational speed due to the implementation of a maximum power point tracking MPPT control algorithm. A total of three min simulations were undertaken to compare the response of the IEC Kaimal wind model to measured wind data from both the UoN and PK sites. A min series was produced using TurbSim with a mean wind speed of 7.
Time series sets were selected from the 90th percentile longitudinal turbulence line-of-best-fit at a mean wind speed of 7. Simulations were executed in FAST using the blade element momentum theory aerodynamic model, with inclusion of the Beddoes—Leishman dynamic stall model, Prandtl correction for tip-loss effects, and skewed wake correction to account for yaw errors.
This lengthy computation time was due to a disparity in solver schemes between the fixed time step solver in FAST and the accelerated variable step solver used for the Simulink SEIG model, where the Simulink solver time step had to be reduced to the same time step as FAST. FAST allows for a wide range of outputs including, but not limited to; rotor aerodynamic power, tip speed ratio, generator electrical power, net rotor thrust and torque, blade and tower loads and deflections.
Table 1 also shows a modest increase in mean power observed for the higher turbulent UoN and PK wind sets when compared to the IEC simulated data. A similar trend is also observed when comparing tip speed ratio, where increases of the mean are likely due to the effects of rapid changes in wind speed in combination with rotor inertia and variable speed control effects.
This indicates that variable speed control schemes for turbines used in complex terrain should be robust enough to contend with operation outside design tip speed ratios. The effects of inlet wind sets on turbine loads were also considered, in particular: the net rotor thrust, net rotor torque, and the first blade flapwise moment considered critical for fatigue loading.
As documented in Table 2 , the net rotor thrust load and blade flapwise load show a minor increase in mean load when comparing the IEC inlet wind to the UoN and PK wind series.
Interestingly, mean rotor torque was practically identical, however higher variations in torque and hence power were experienced for the UoN and PK cases. That is torque deviation beyond the design level was mitigated by the controller via reducing the rotor speed.
This corresponds to a reduction in tip speed ratio, a decrease in aerofoil lift, and an increase in drag forces, which was ultimately manifest as an increase in net rotor thrust. This represents a significant increase in loading which is likely to have consequences for both blade ultimate and fatigue loading.
A time series plot of the blade flapwise bending moment is presented in Figure 3 , illustrating the output signals from FAST. A power spectral density plot, is provided to assess blade response in the frequency domain. Higher power spectral density PSD values at low frequencies were observed for the UoN and PK data sets, suggesting that the wind at UoN and PK has greater turbulent kinetic energy, with this energy passed on to the dynamics of the turbine. The exact cause of this reduction was not apparent and requires further investigation.
No other significant dynamics effects, including natural frequency excitation, were observed. Damage equivalent loads DELs were calculated for the blade flapwise bending moment load to compare potential for fatigue loading.
Methodology was followed as per IEC The work documented in this paper clearly shows the assumed wind field spectral model used in IEC under predicts the level of turbulence for most wind speeds at the PK site and for all wind speeds at the UoN site. The results of this study suggest that the IEC NTM is not applicable for built environment or complex terrain sites. Small wind turbine developers should therefore use caution when using IEC wind conditions for determining design loads.
A critically important point is the effect of these higher turbulence levels on turbine performance and fatigue loading experienced by a turbine throughout its nominal lifespan of 20 years. Results of this modelling clearly show that for the same mean wind speed of 7.
Mean rotor torque was largely unaffected by increased turbulence with both rotor thrust and flapwise moment increased by turbulence. For SWT, the blade flapwise bending moment is the critical loading that determines the blade fatigue life. Further research effort and site measurements are required to fully characterise the urban wind resource at a wider range of small wind turbine sites before a revision can be proposed to the standard.
The influence of inlet wind conditions on small wind turbine operation is non-linear due to complex system dynamics. To fully investigate structural loading and fatigue life effects, aeroelastic simulations encompassing the full turbine operating range of wind speeds and turbulence levels will be required.
This work will form the basis of future research effort. Cite this article as : Samuel P. Bradney, Tania P. Urmee, Jonathan Whale, Philip D. Clausen, The suitability of the IEC wind model for small wind turbines operating in the built environment, Renew.
Energy Environ. Data correspond to usage on the plateform after The current usage metrics is available hours after online publication and is updated daily on week days. All issues Volume 2 Renew. Sustainable energy systems for the future. Issue Renew. Table 1 Ten-min statistics for generator power and tip speed ratio. Table 2 Ten-min statistics for rotor thrust, torque, and blade load.
Table 3 Ten-min maximum rotor loads. IEC Sunderland, T. Woolmington, M. Conlon, J. Blackledge, Urban deployment of small wind turbines: power performance and turbulence, in Proc.
Tabrizi, J. Whale, T.
Do you need a multi-user copy? Our prices are in Swiss francs CHF. We accept all major credit cards American Express, Mastercard and Visa , PayPal and bank transfers as form of payment. Preview Abstract IEC deals with safety philosophy, quality assurance, and engineering integrity and specifies requirements for the safety of small wind turbines SWTs including design, installation, maintenance and operation under specified external conditions.