Experimental evaluation of a tree-shaped quad-rotor wind turbine on power output controllability and survival shutdown capability

Energy Storage Systems (EES) are key to further increase the penetration in energy grids of intermittent renewable energy sources, such as wind, by smoothing out power fluctuations. In order this to be economically feasible; however, the ESS need to be sized correctly and managed efficiently. In the study, the use of discrete wavelet transform (Daubechies Db4) to decompose the power output of utility-scale wind turbines into high and low-frequency components, with the objective of smoothing wind turbine power output, is discussed and applied to four-year Supervisory Control And Data Acquisition (SCADA) real data from multi-MW, on-shore wind turbines provided by the industrial partner. Two main research requests were tackled: first, the effectiveness of the discrete wavelet transform for the correct sizing and management of the battery (Li-Ion type) storage was assessed in comparison to more traditional approaches such as a simple moving average and a direct use of the battery in response to excessive power fluctuations. The performance of different storage designs was compared, in terms of abatement of ramp rate violations, depending on the power smoothing technique applied. Results show that the wavelet transform leads to a more efficient battery use, characterized by lower variation of the averaged state-of-charge, and in turn to the need for a lower battery capacity, which can be translated into a cost reduction (up to −28%). The second research objective was to prove that the wavelet-based power smoothing technique has superior performance for the real-time control of a wind park. To this end, a simple procedure is proposed to generate a suitable moving window centered on the actual sample in which the wavelet transform can be applied. The power-smoothing performance of the method was tested on the same time series data, showing again that the discrete wavelet transform represents a superior solution in comparison to conventional approaches.

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High Efficiency Wind Turbine Using Co-Flow Jet Active Flow Control

10.1115/gt2021-59664 ◽

2021 ◽

Author(s):

Kewei Xu ◽

Gecheng Zha

Keyword(s):

Flow Control ◽

Wind Turbine ◽

Flow Separation ◽

Power Output ◽

Pitch Angle ◽

Active Flow Control ◽

Horizontal Axis Wind Turbine ◽

Negative Power ◽

Freestream Velocity ◽

Active Flow

Abstract This paper applies Co-flow Jet (CFJ) active flow control airfoil to a NREL horizontal axis wind turbine for power output improvement. CFJ is a zero-net-mass-flux active flow control method that dramatically increases airfoil lift coefficient and suppresses flow separation at a low energy expenditure. The 3D Reynolds Averaged Navier-Stokes (RANS) equations with one-equation Spalart-Allmaras (SA) turbulence model are solved to simulate the 3D flows of the wind turbines. The baseline wind turbine is the NREL 10.06m diameter phase VI wind turbine and is modified to a CFJ blade by implementing CFJ along the span. The baseline wind turbine performance is validated with the experiment at three wind speeds, 7m/s, 15m/s, and 25m/s. The predicted blade surface pressure distributions and power output agree well with the experimental measurements. The study indicates that the CFJ can enhance the power output at the condition where angle of attack is increased to the level that conventional wind turbine is stalled. At the speed of 7m/s that the NREL turbine is designed to achieve the optimum efficiency at the pitch angle of 3°, the CFJ turbine does not increase the power output. When the pitch angle is reduced by 13° to −10°, the baseline wind turbine is stalled and generates negative power output at 7m/s. But the CFJ wind turbine increases the power output by 12.3% assuming CFJ fan efficiency of 80% at the same wind speed. This is an effective method to extract more power from the wind at all speeds. It is particularly useful at low speeds to decrease cut-in speed and increase power output without exceeding the structure limit. At the freestream velocity of 15m/s and the CFJ momentum coefficient Cμ of 0.23, the net power output is increased by 207.7% assuming the CFJ fan efficiency of 80%, compared to the baseline wind turbine due to the removal of flow separation. The CFJ wind turbine appears to open a door to a new area of wind turbine efficiency improvement and adaptive control for optimal loading.

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Abnormally High Power Output of Wind Turbine in Cold Weather: A Preliminary Study

International Journal of Rotating Machinery ◽

10.1155/s1023621x03000034 ◽

2003 ◽

Vol 9 (1) ◽

pp. 23-33 ◽

Cited By ~ 2

Author(s):

Christophe Leclerc ◽

Christian Masson

Keyword(s):

Wind Turbine ◽

Air Temperature ◽

High Power ◽

Power Output ◽

Cold Weather ◽

Air Density ◽

High Power Output ◽

Wind Velocities ◽

Preliminary Study ◽

Narrow Bands

According to popular belief, air temperature effects on wind turbine power output are produced solely by air density variations, and power is proportional to air density. However, some cases have been reported, all involving stall-controlled wind turbines, in which unexpected high power output was observed at very low temperatures.As a preliminary study, this article intends to quantify the influence of air temperature on the power production of the Tacke TW600 wind turbine installed in Tiverton, Ontario, Canada. Increases in power output due to air temperature variation are stratified by wind velocity, showing that these increases are below the theoretical limits of air density variations during operation in low winds and are comparable to and beyond those theoretical limits at higher wind velocities. At – 9°C and 0°C, narrow bands of power at distinct levels are observed in the stall regime of the turbine; they are typical of many stall phenomena observed on stall-controlled rotors, but these levels have been found to be independent of any parameters recorded.

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Correlations of power output fluctuations in an offshore wind farm using high-resolution SCADA data

Wind Energy Science ◽

10.5194/wes-6-997-2021 ◽

2021 ◽

Vol 6 (4) ◽

pp. 997-1014

Author(s):

Janna Kristina Seifert ◽

Martin Kraft ◽

Martin Kühn ◽

Laura J. Lukassen

Keyword(s):

Wind Turbine ◽

Wind Turbines ◽

Power Output ◽

Wind Farm ◽

Offshore Wind ◽

Offshore Wind Farm ◽

Flow Conditions ◽

Output Fluctuations ◽

Power Difference ◽

Time Correlations

Abstract. Space–time correlations of power output fluctuations of wind turbine pairs provide information on the flow conditions within a wind farm and the interactions of wind turbines. Such information can play an essential role in controlling wind turbines and short-term load or power forecasting. However, the challenges of analysing correlations of power output fluctuations in a wind farm are the highly varying flow conditions. Here, we present an approach to investigate space–time correlations of power output fluctuations of streamwise-aligned wind turbine pairs based on high-resolution supervisory control and data acquisition (SCADA) data. The proposed approach overcomes the challenge of spatially variable and temporally variable flow conditions within the wind farm. We analyse the influences of the different statistics of the power output of wind turbines on the correlations of power output fluctuations based on 8 months of measurements from an offshore wind farm with 80 wind turbines. First, we assess the effect of the wind direction on the correlations of power output fluctuations of wind turbine pairs. We show that the correlations are highest for the streamwise-aligned wind turbine pairs and decrease when the mean wind direction changes its angle to be more perpendicular to the pair. Further, we show that the correlations for streamwise-aligned wind turbine pairs depend on the location of the wind turbines within the wind farm and on their inflow conditions (free stream or wake). Our primary result is that the standard deviations of the power output fluctuations and the normalised power difference of the wind turbines in a pair can characterise the correlations of power output fluctuations of streamwise-aligned wind turbine pairs. Further, we show that clustering can be used to identify different correlation curves. For this, we employ the data-driven k-means clustering algorithm to cluster the standard deviations of the power output fluctuations of the wind turbines and the normalised power difference of the wind turbines in a pair. Thereby, wind turbine pairs with similar power output fluctuation correlations are clustered independently from their location. With this, we account for the highly variable flow conditions inside a wind farm, which unpredictably influence the correlations.

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Wind turbine power output very short-term forecast: A comparative study of data clustering techniques in a PSO-ANFIS model

Journal of Cleaner Production ◽

10.1016/j.jclepro.2020.120135 ◽

2020 ◽

Vol 254 ◽

pp. 120135 ◽

Cited By ~ 15

Author(s):

Paul A. Adedeji ◽

Stephen Akinlabi ◽

Nkosinathi Madushele ◽

Obafemi O. Olatunji

Keyword(s):

Comparative Study ◽

Wind Turbine ◽

Power Output ◽

Data Clustering ◽

Short Term ◽

Anfis Model ◽

Clustering Techniques ◽

Short Term Forecast ◽

Term Forecast

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Design and Modeling of Modified Savonius Highway Wind Turbine

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i4.24.21860 ◽

2018 ◽

Vol 7 (4.24) ◽

pp. 80

Author(s):

P.M. Venkatesh ◽

Dr.K .Suresh ◽

A.R. Vijay Babu

Keyword(s):

Wind Turbine ◽

Power Output ◽

Fast Moving ◽

Power Converter ◽

Wind Data ◽

Constant Power ◽

The Road ◽

Moving Vehicles ◽

Savonius Wind Turbine ◽

Constant Power Output

Abstract— in this paper, the design and modeling of highway wind mill using savonius wind turbine has been done. The highway wind mill is nothing but the wind mill kept in the mid of the road so that , this wind mill utilize the fast moving wind which is produced from fast moving vehicles travels in the high way. In this work the required wind data have been collected in highways and based on these values the design and fabrication have been made. The output of the wind turbine has been given to the power converter in order to get the constant power output.

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Power output prediction and primary evaluation of a unidirectional co-axial series rotors wind turbine

2013 Annual International Conference on Emerging Research Areas and 2013 International Conference on Microelectronics, Communications and Renewable Energy ◽

10.1109/aicera-icmicr.2013.6576030 ◽

2013 ◽

Author(s):

Sandip A. Kale ◽

S. N. Sapali

Keyword(s):

Wind Turbine ◽

Power Output ◽

Primary Evaluation

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Spatial and geographic heterogeneity of wind turbine farms for temporally decoupled power output

Energy ◽

10.1016/j.energy.2018.01.019 ◽

2018 ◽

Vol 145 ◽

pp. 417-429 ◽

Cited By ~ 10

Author(s):

Nathaniel S. Pearre ◽

Lukas G. Swan

Keyword(s):

Wind Turbine ◽

Power Output

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Nondimensional Parameters’ Effects on Hybrid Darrieus–Savonius Wind Turbine Performance

Journal of Energy Resources Technology ◽

10.1115/1.4044517 ◽

2019 ◽

Vol 142 (1) ◽

Cited By ~ 3

Author(s):

Armin Roshan ◽

Amir Sagharichi ◽

Mohammad Javad Maghrebi

Keyword(s):

Wind Turbine ◽

Wind Turbines ◽

Power Output ◽

Urban Areas ◽

Model Performance ◽

Vertical Axis ◽

Favorable Effect ◽

Turbine Performance ◽

Primary Model ◽

Overlap Ratio

Abstract Vertical axial wind turbines are the most commonly used turbines in residential and urban areas. This paper investigates the effect of combining Darrieus and Savonius wind turbines on power output and introduces a wind turbine with high starting torque addition to the wide working domain. A two-dimensional computational fluid dynamics transient simulation is developed, and a moving mesh is implemented for rotating moving parts. Comprehensive research has been carried out to investigate the effects of the initial overlap ratio (ɛ), arc angle Ø, and curvature (α) of Savonius blades on the performance of the turbine and 18 models are simulated at seven tip speed ratios. The results showed that combining the Darrieus turbine with the Savonius turbine has a favorable effect on self-starting performance. Also, it was observed that by changing each of the parameters, the primary model performance could be significantly improved. Finally, it is concluded that ɛ = 0.25, α = 0.25, and ∅ = 150 deg are the optimum values of the parameters which increase turbine power output compared to conventional vertical-axis turbines.

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