Soutenance mémoire
ATMOSPHERIC ICING IMPACT ON WIND TURBINE
PRODUCTION
Wind turbine performance depends mainly on the wind speed and aerodynamics of blades. The roughness generated from ice accretion can significantly reduce the aerodynamics and consequently the power production of the wind turbine. This study locates the glaze and rime ice on the blade, to detect the critical zones involved in significant power production loss. On the blade, the distribution of the elementary power production as well as the type and thickness of the accreted ice are inconsistent. Under icing conditions, the outer section of the blade starting fromthe radial position r/R=0.8 contribute significantly to the blades aerodynamics. The freezing fraction is unevenly distributed; since it initially forms rime ice near the root and then glaze toward the tip of the blade. The critical freezing fraction 0.88 associated with the double horn ice shape is spatially limited and occupies a restricted segment on the blade and gradually moves towards the tip with decreasing temperature. With the use of power degradation analogy with sub-scaled rotor blades of a helicopter under icing conditions, a power loss factor is introduced to quantify and locate power loss along the blades of wind turbines. The study is based on four values of liquid water content that delineate five classes of icing severity. Including power loss factor, the most significant power loss that corresponds to freezing fraction 0.88 is found to be located at r/R ~ [0.93 0.96] which corresponds to T = -2.6 °C, – 4.5 °C, -12 °C, and -20 °C and for liquidwater content LWC=0.04 g·m-3 , 0.07 g·m-3 , 0.2 g·m-3 , and 0.36 g·m−3 respectively. The resulted power degradation can reach a maximum of 40%. Locally it is the shape rather than the thickness of ice that causes more power loss; meanwhile when considering the whole blade, power degradation is controlled mainly by ice thickness regardless of the type of ice. The results obtained can help the setup of a sensor that triggers the ice-protection system upon detection of critical freezing fraction.
Methodology
The models used for the current study attempt to involve more relevant parameters, in order to improve the assessment of the severity of icing events, and more specifically the production loss of wind turbines caused by ice accretion. In addition to the liquid water content and the duration of icing events for different icing severity classes involved in the quantification and the assessment of the icing severity index (Lamraoui et al., 2013), the present study focuses on exploring the aerodynamic degradation distribution along the blade, under different meteorological conditions and geometries of the blades. In order to cover a typical range of liquid water contents and various severity classes (Fikke et al., 2006; Lamraoui et al., 2013), the values of LWC 0.04 g·m-3 (light), 0.07 g·m-3 (moderate), 0.2 g·m -3 (severe), 0.36 g·m -3 (extreme) were considered for ice calculation. Under icing conditions, the distribution of the electric energy production along an optimal blade design was calculated, in order to locate the critical position on the blade that causes the highest power loss during icing events. The use of ice accretion and power loss models with different values of meteorological and geometric parameters enables the exploration to help locate the aerodynamic and mechanical effects along the blade. Several studies (Hochart et al., 2008; Lamraoui et al., 2013) have associated the value of liquid water content 0.2 g·m -3 to representative occurrences of atmospheric icing over Murdochville, and to the average of maximum values during winter months over Mount Bélair (Canada). Therefore, a particular intention was given to production losses that are associated this typically assumed liquid water content. Unlike helicopters that require power to rotate, wind turbines rotate to provide power. Due to the lack of studies that investigate the impact of freezing fraction on wind turbines production, the effect of freezing fraction on power requirements for helicopter is projected on wind turbine power production. To begin, this study identifies the critical location which corresponds to the most aerodynamically hazardous freezing fraction (Fortin and Perron, 2009) on the blade that holds the maximumpower loss. Then, the corresponding temperatures for typical liquid water contents are determined, and finally power loss is evaluated (Fortin and Perron, 2009) .
Generic wind turbine
The investigation was carried out on a generic horizontal axis wind turbine which is based on V80-1.8 MW Vestas characteristics. This type of wind turbine is commonly used in the province of Quebec (Canada). This wind turbine is characterized by a diameter of 80 m and a rated power of 1.8 MW that corresponds to a rated wind speed of 14 m·s-1 . The minimum wind speed at which the wind turbine starts to be operational is 4 m·s-1 . The blades have a variable pitch angle that corresponds to prevailing winds. The wind turbine rotates at approximately 16 rpm (Vestas).
Blade
The generic blades have a radius of 40 m and are designed to provide more power and to minimize mechanical strains and sound. Since the blade design with more efficiency is complex and costly, a simplified alternative that represents a linear variation of the chord along the span was suggested (Burton et al., 2001).
Airfoil
In order to substitute NACA 44xx airfoil, Danish wind turbine designers started to use NACA 63(2)-xx airfoils that showed a reduced sensitivity to leading edge roughness. According to Abbot and von Doenhoff (1959) and Hansen (2008), wind turbine blades are often designed with a profile having similar characteristics to NACA 63–415 airfoil due to its stall characteristics. The roughness that is caused by dirt and insect accumulation can decrease the power output up to 40% (Manwell et al., 2009). The leading edge is considered the zone on the blade that has the highest sensitivity to surface roughness (Jacobs, 1932; Jones andWilliams, 1936).
Water collection effeciency
According to Eq. (3), collection efficiency is an important factor that contributes in controlling the amount of accreted ice. Therefore, within similar meteorological and geometric conditions, hydrometeors with different subfreezing water droplet diameters generate different collection efficiencies along the blade. Figure 3.5 shows three profiles of collection efficiency that correspond to supercooled stratus clouds (fog), supercooled drizzle and freezing rain with droplet diameters 20 μm, 200 μm and 2000 μm respectively. Due to the large size of rain drops, the water drops are all collected when at impact with the leading edge along the entire blade, . Except for a slight decrease of collection efficiency near the root of the blade, the drizzle droplets maintain a high collection which is compared to that of rain droplets. Distinctively, supercooled fog droplets with a diameter of 20 μm are characterized with a collection efficiency that varies approximately from 0.09 near the root of the blade to more than 0.9 at the tip. Depending on the radial position, the rotational motion of wind turbine leads to a linear increase of relative velocity, starting from the root of the blade to the tip. The outer section of the blade has the smallest chord length and leading edge. Furthermore, Figure. 5 corroborates the fact (Eqs. (4)–(5)) that higher velocity, smaller water drops and cylinder diameter all increase the droplet collection efficiency.
|
Table des matières
CHAPTER 1
1. ATMOSPHERIC ICING SEVERITY: QUANTIFICATION AND MAPPING
Abstract
1.1 Introduction
1.2 Methodology
1.2.1 Reanalysis Data
1.2.2 Icing calculations
1.2.3 Icing events
1.2.4 Freezing rain storm of 1998
1.2.5 Icing severity index
1.3 Results
1.3.1 Case studies
1.3.2 Ice storm of January 1998
1.3.3 Icing severity index
1.4 Discussion of the results
1.5 Conclusion
1.6 References
CHAPTER 2
2. HYBRID FINE SCALE CLIMATOLOGY AND MICROPHYSICS OF IN-CLOUD
ICING: FROM 32KM REANALYSIS TO 5KM MESOSCALE MODELING
Abstract
2.1 Introduction
2.2 Method
2.3 Results
2.3.1 Climatology of atmospheric icing
2.3.2 Transition from 32-year to 15-year
2.3.3 GEM-LAM and NARR performances
2.3.4 Selection of significant days
2.3.5 Mesoscale modeling and simulation setup
2.3.6 Statistics and cloud microphysics properties
2.3.7 Vertical profile of icing events climatology
2.3.8 Icing severity index at fine scale resolution
2.4 Conclusion
2.5 References
CHAPTER 3
3. ATMOSPHERIC ICING IMPACT ON WIND TURBINE PRODUCTION
Abstract
3.1 Introduction
3.2 Methodology
3.2.1 Generic wind turbine
3.2.2 Blade
3.2.3 Chord
3.2.4 Airfoil
3.2.5 Speed
3.3 Ice accretion model
3.4 Power distribution model
3.5 Results
3.5.1 Power along the blade
3.5.2 Water collection effeciency
3.5.3 Ice mass rate
3.5.4 Aerodynamic effect
3.5.5 Freezing fraction
3.5.6 Power loss
3.6 Analysis
3.7 Conclusion
3.8 References
GENERAL CONCLUSION
Télécharger le rapport complet
