Evaluating the impact of electrical grid connection on the wind turbine performance for Hofa wind farm scheme in Jordan

2008 ◽  
Vol 49 (11) ◽  
pp. 3376-3380 ◽  
Author(s):  
M.H. Abderrazzaq ◽  
O. Aloquili
Keyword(s):  
Wind Turbine ◽  
Wind Farm ◽  
Electrical Grid ◽  
Grid Connection ◽  
Turbine Performance ◽  
The Impact

scholarly journals Mitigating impact of spatial variance of turbulence in wind energy applications

2020 ◽  
Vol 5 (2) ◽  
pp. 439-450
Author(s):  
Jonas Kazda ◽  
Jakob Mann
Keyword(s):  
Wind Turbine ◽  
Random Error ◽  
Wind Farm ◽  
Second Order ◽  
Mitigation Measures ◽  
Order Moment ◽  
Spatial Variance ◽  
Turbine Performance ◽  
The Difference ◽  
The Impact

Abstract. For the first time an analytical solution for the quantification of the spatial variance of the second-order moment of correlated wind speeds was developed in this work. The spatial variance is defined as random differences in the sample variance of wind speed between different points in space. The approach is successfully verified using simulation and field data. The impact of the spatial variance on three selected applications relevant to the wind energy sector is then investigated including mitigation measures. First, the difference of the second-order moment between front-row wind turbines of Lillgrund wind farm is investigated. The variance of the difference ranges between 25 % and 48 % for turbulence intensities ranging from 7 % to 10 % and a sampling period of 10 min. It is thus suggested to use the second-order moment measured at each individual turbine as input to flow models of wind farm controllers in order to mitigate random error. Second, the impact of the spatial variance of the measured second-order moment on the verification of wind turbine performance is investigated. Misalignment between the mean wind direction and the line connecting the meteorological mast and wind turbine is observed to result in an additional random error in the observed second-order moment of wind speed. In the investigated conditions the random error was up to 34 %. Such a random error adds uncertainty to the turbulence intensity-based classification of the fatigue loads and power output of a wind turbine. To mitigate the random error, it is suggested to either filter the measured data for low angles of misalignment or quantify wind turbine performance using the ensemble-averaged measurements of the same wind conditions. Third, the verification of sensors in wind farms was investigated with respect to the impact of distant reference measurements. In the case of a misalignment between the wind direction and the line connecting sensor and reference, an increased random error will hamper the comparison of the measured second-order moments. The suggested mitigation measures are equivalent to those for the verification of turbine performance.

scholarly journals Mitigating Impact of Spatial Variance of Turbulence in Wind Energy Applications

2019 ◽  
Author(s):  
Jonas Kazda ◽  
Jakob Mann
Keyword(s):  
Wind Turbine ◽  
Random Error ◽  
Wind Farm ◽  
Second Order ◽  
Mitigation Measures ◽  
Order Moment ◽  
Spatial Variance ◽  
Turbine Performance ◽  
The Difference ◽  
The Impact

Abstract. The first analytical solution for the quantification of the spatial variance of the second-order moment of correlated wind speeds was developed in this work. The spatial variance is defined as random differences in the sample variance of wind speed between different points in space. The approach is successfully verified using simulation and field data. The impact of the spatial variance on three selected applications relevant to the wind energy sector is then investigated including mitigation measures. First, the difference of the second-order moment between front-row wind turbines of Lillgrund wind farm is investigated. The variance of the difference ranges between 25 % and 48 % for turbulence intensities ranging from 7 % to 10 % and a sampling period of 10 min. It is thus suggested to use the second-order moment measured at each individual turbine as input to flow models of wind farm controllers in order to mitigate random error. Second, the impact of the spatial variance of the measured second-order moment on the verification of wind turbine performance is investigated. Misalignment between the mean wind direction and the line connecting the meteorological mast and wind turbine is observed to result in an additional random error in the observed second-order moment of wind speed. In the investigated conditions the random error was up to 34 %. Such random error adds uncertainty to the turbulence intensity-based classification of the fatigue loads and power output of a wind turbine. To mitigate the random error it is suggested to either filter the measured data for low angles of misalignment, or to quantify wind turbine performance using the ensemble averaged measurements of the same wind conditions. Third, the verification of sensors in wind farms was investigated with respect to the impact of distant reference measurements. In case of a misalignment between the wind direction and the line connecting sensor and reference, an increased random error will hamper the comparison of the measured second-order moments. The suggested mitigation measures are equivalent to those for the verification of turbine performance.

Dynamic Simulation of a Wind Farm With Variable Speed Wind Turbines

2003 ◽  
Author(s):  
E. Muljadi ◽  
C. P. Butterfield
Keyword(s):  
Wind Turbine ◽  
Wind Power ◽  
Wind Turbines ◽  
Wind Farm ◽  
Reactive Power ◽  
Power Network ◽  
Variable Speed ◽  
Power Capacity ◽  
Advantages And Disadvantages ◽  
The Impact

Wind power generation has increased very rapidly in the past few years. The total U.S. wind power capacity by the end of 2001 was 4,260 megawatts. As wind power capacity increases, it becomes increasingly important to study the impact of wind farm output on the surrounding power networks. In this paper, we attempt to simulate a wind farm by including the properties of the wind turbine, the wind speed time series, the characteristics of surrounding power network, and reactive power compensation. Mechanical stress and fatigue load of the wind turbine components are beyond the scope this paper. The paper emphasizes the impact of the wind farms on the electrical side of the power network. A typical wind farm with variable speed wind turbines connected to an existing power grid is investigated. Different control strategies for feeding wind energy into the power network are investigated, and the advantages and disadvantages are presented.

scholarly journals A Study of the Impact of Pitch Misalignment on Wind Turbine Performance

Machines ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 8 ◽  
Author(s):  
Davide Astolfi
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Power Output ◽  
Wind Farm ◽  
Reactive Power ◽  
Power Production ◽  
Test Case ◽  
Before And After ◽  
Input Variables ◽  
The Impact

Pitch angle control is the most common means of adjusting the torque of wind turbines. The verification of its correct function and the optimization of its control are therefore very important for improving the efficiency of wind kinetic energy conversion. On these grounds, this work is devoted to studying the impact of pitch misalignment on wind turbine power production. A test case wind farm sited onshore, featuring five multi-megawatt wind turbines, was studied. On one wind turbine on the farm, a maximum pitch imbalance between the blades of 4.5 ° was detected; therefore, there was an intervention for recalibration. Operational data were available for assessing production improvement after the intervention. Due to the non-stationary conditions to which wind turbines are subjected, this is generally a non-trivial problem. In this work, a general method was formulated for studying this kind of problem: it is based on the study, before and after the upgrade, of the residuals between the measured power output and a reliable model of the power output itself. A careful formulation of the model is therefore crucial: in this work, an automatic feature selection algorithm based on stepwise multivariate regression was adopted, and it allows identification of the most meaningful input variables for a multivariate linear model whose target is the power of the wind turbine whose pitch has been recalibrated. This method can be useful, in general, for the study of wind turbine power upgrades, which have been recently spreading in the wind energy industry, and for the monitoring of wind turbine performances. For the test case of interest, the power of the recalibrated wind turbine is modeled as a linear function of the active and reactive power of the nearby wind turbines, and it is estimated that, after the intervention, the pitch recalibration provided a 5.5% improvement in the power production below rated power. Wind turbine practitioners, in general, should pay considerable attention to the pitch imbalance, because it increases loads and affects the residue lifetime; in particular, the results of this study indicate that severe pitch misalignment can heavily impact power production.

The Impact of Ice Formation on Wind Turbine Performance and Aerodynamics

2011 ◽  
Vol 133 (1) ◽  
Author(s):  
S. Barber ◽  
Y. Wang ◽  
S. Jafari ◽  
N. Chokani ◽  
R. S. Abhari
Keyword(s):  
Wind Energy ◽  
Wind Turbine ◽  
Swiss Alps ◽  
Test Facility ◽  
Ice Formation ◽  
Predictive Tool ◽  
Lower Altitude ◽  
Turbine Performance ◽  
The Impact ◽  
Power Curves

Wind energy is the world’s fastest growing source of electricity production; if this trend is to continue, sites that are plentiful in terms of wind velocity must be efficiently utilized. Many such sites are located in cold, wet regions such as the Swiss Alps, the Scandinavian coastline, and many areas of China and North America, where the predicted power curves can be of low accuracy, and the performance often deviates significantly from the expected performance. There are often prolonged shutdown and inefficient heating cycles, both of which may be unnecessary. Thus, further understanding of the effects of ice formation on wind turbine blades is required. Experimental and computational studies are undertaken to examine the effects of ice formation on wind turbine performance. The experiments are conducted on a dynamically scaled model in the wind turbine test facility at ETH Zurich. The central element of the facility is a water towing tank that enables full-scale nondimensional parameters to be more closely matched on a subscale model than in a wind tunnel. A novel technique is developed to yield accurate measurements of wind turbine performance, incorporating the use of a torquemeter with a series of systematic measurements. These measurements are complemented by predictions obtained using a commercial Reynolds-Averaged Navier–Stokes computational fluid dynamics code. The measured and predicted results show that icing typical of that found at the Guetsch Alpine Test Site (2330 m altitude) can reduce the power coefficient by up to 22% and the annual energy production (AEP) by up to 2%. Icing in the blade tip region, 95–100% blade span, has the most pronounced effect on the wind turbine’s performance. For wind turbines in more extreme icing conditions typical of those in Bern Jura, for example, icing can result in up to 17% losses in AEP. Icing at high altitude sites does not cause significant AEP losses, whereas icing at lower altitude sites can have a significant impact on AEP. Thus, the classification of icing is a key to the further development of prediction tools. It would be advantageous to tailor blade heating for prevention of ice buildup on the blade’s tip region. An “extreme” icing predictive tool for the project development of wind farms in regions that are highly susceptible to icing would be beneficial to wind energy developers.

Grid Tripping and Re-connection: Full-scale Experimental Validation of a Dynamic Wind Turbine Model

2003 ◽  
Vol 27 (3) ◽  
pp. 205-213 ◽  
Author(s):  
Niels Raben ◽  
Martin Heyman Donovan ◽  
Erik Jørgensen ◽  
Jan Thisted ◽  
Vladislav Akhmatov
Keyword(s):  
Wind Turbine ◽  
Wind Power ◽  
Wind Farm ◽  
Power Grid ◽  
System Stability ◽  
Turbine Generator ◽  
Wind Turbine Generator ◽  
Shaft System ◽  
The Impact ◽  
Turbine Model

An experiment with tripping and re-connecting a MW wind turbine generator was carried out at the Nøjsomheds Odde wind farm in Denmark. The experimental results are used primarily to validate the shaft system representation of a dynamic wind turbine model. The dynamic wind turbine model is applied in investigations of power system stability with relation to incorporation of large amounts of wind power into the Danish power grid. The simulations and the measurements are found to agree. The experiment was part of a large R&D program started in Denmark to investigate the impact of the increasing capacity of wind power fed into the Danish power grid.

Reliability Evaluation of New Offshore Wind Farm Electrical Grid Connection Topologies

2013 ◽  
Author(s):  
B. Kazemtabrizi ◽  
C. Crabtree ◽  
S. Hogg
Keyword(s):  
Wind Farm ◽  
Sequential Monte Carlo ◽  
Wind Farms ◽  
Load Level ◽  
Offshore Wind ◽  
Reliability Modeling ◽  
Offshore Wind Farms ◽  
Electrical Grid ◽  
Grid Connection ◽  
Potential Improvement

In this paper, a composite generation transmission approach has been chosen for adequacy evaluation of wind farms integrated with conventional generating units. It has been assumed that the failure characteristics of a turbine’s underlying subassemblies possess the required Markov properties to be modeled as Markov processes. The wind farm along with the offshore connection grid has then been modeled in a sequential Monte Carlo simulation which also contains sequential chronological models for wind speed and load level variations over a specific period of time. The reliability of the wind farm is then evaluated against a series of load- and energy-based indices as well as overall productivity of the farm with different connections. The results indicate a potential improvement in the reliability of wind power output when in cluster-type topologies, where the converters are grouped and maintained in a central offshore platform, in comparison to conventional string-type topologies. Academic researchers involved in reliability modeling and risk analysis of renewable sources of energy, particularly wind, as well as industry professionals both in wind turbine manufacturing and operation and maintenance of offshore wind farms would equally benefit from the degree of detail and accuracy provided by the models presented in this paper.

Handling Wind Variability Using Gas Turbines

2012 ◽  
Author(s):  
L. Branchini ◽  
H. Perez-Blanco
Keyword(s):  
Power Output ◽  
Gas Turbines ◽  
Wind Farm ◽  
Heavy Duty ◽  
Electrical Grid ◽  
Wind Variability ◽  
Turbine Performance ◽  
Start Up ◽  
Viable Solution ◽  
To Come

A significant amount of energy is expected to come from wind in the upcoming years. The variability and uncertainty of this power source needs to be managed by the grid operator. Electricity networks with wind energy need extra reserves to deal with the extra uncertainty associated with the presence of wind. This paper evaluates the possibility to couple a 1000 MW wind farm with gas turbines (GTs) to provide firm capacity to the grid with a reasonable investment. Taking into account two different days of wind production with one minute data, the study analyzes the possibility of integrating the wind power output with two different types of GTs (heavy duty and aeroderivative). GTs operational constrains are included in the model in order to correctly demonstrate how the wind variability stresses turbine performance, as it probably would in extreme cases. Limitations on GTs ramps rates and start–up time are considered for both, heavy duty and aeroderivatives. GTs power output profiles, ramp rates and fuel consumption for the selected days of analysis are shown. The results show that the integration between wind and gas turbines could be a viable solution to compensate wind variability and to accommodate the increasing wind penetration into the electrical grid.

Effect of Flow Inclination on Wind Turbine Performance

2012 ◽  
Vol 134 (12) ◽  
Author(s):  
Christina Tsalicoglou ◽  
Sarah Barber ◽  
Ndaona Chokani ◽  
Reza S. Abhari
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Complex Terrain ◽  
Wake Flow ◽  
Test Facility ◽  
Power Coefficient ◽  
Incoming Flow ◽  
Turbine Performance ◽  
The Impact ◽  
Blade Element

This work examines the effect of flow inclination on the performance of a stand-alone wind turbine and of wind turbines operating in the wakes of upstream turbines. The experimental portion of this work, which includes performance and flowfield measurements, is conducted in the ETH dynamically-scaled wind turbine test facility, with a wind turbine model that can be inclined relative to the incoming flow. The performance of the wind turbine is measured with an in-line torquemeter, and a 5-hole steady-state probe is used to detail the inflow and wake flow of the turbine. Measurements show that over a range of tip-speed ratios of 4–7.5, the power coefficient of a wind turbine with an incoming flow of 15 deg inclination decreases on average by 7% relative to the power coefficient of a wind turbine with a noninclined incoming flow. Flowfield measurements show that the wake of a turbine with an inclined incoming flow is deflected; the deflection angle is approximately 6 deg for an incoming flow with 15 deg inclination. The measured wake profiles are used as inflow profiles for a blade element momentum code in order to quantify the impact of flow inclination on the performance of downstream wind turbines. In comparison to the case without inclination in the incoming flow, the combined power output of two aligned turbines with incoming inclined flow decreases by 1%, showing that flow inclination in complex terrain does not significantly reduce the energy production.

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].

Sign in / Sign up

Export Citation Format

Share Document