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Record W7033969748

Study of Atmospheric Ice Accretion on Wind Turbine Blades

2021· dissertation· en· W7033969748 on OpenAlexaboutno aff

Bibliographic record

VenueMunin Open Research Archive (The Arctic University of Norway) · 2021
Typedissertation
Languageen
FieldArts and Humanities
TopicLiterature and Cultural Memory
Canadian institutionsnot available
FundersInterregCranfield UniversityUniversitetet i Tromsø
KeywordsIcingWind powerIcing conditionsTurbineWind speedMaximum sustained windAccretion (finance)Turbine blade
DOInot available

Abstract

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<p>This Ph.D. work concerns itself with the atmospheric ice accretion on wind turbine blades. The wind energy has been at the forefront of the renewable energy generation for the last several decades, with the amount and capacity of installed wind turbines steadily increasing. The cold climate (CC) regions around the world like Finland, Germany, Slovak Republic, Norway, Czech Republic, UK, Sweden, Bulgaria, Hungary, Russia, Canada and USA have great potential of wind resources. Estimated wind energy capacity in CC is about 60 GW. [1] However, due to this steady increase in the installed power capacity, more and more turbines have to be placed in regions with harsh geographical conditions, such as arctic regions, in which the temperatures below the normal operating conditions can result in the atmospheric icing to accumulate on the wind turbines particularly along blades. The icing on wind turbines blades leads to negative effects, such as, decreased lift and increased drag, increased mechanical wear and fatigue, possibility of ice throw, which negatively impacts the personnel and life in the area, aeroacoustics noise, generated from iced wind turbines, etc. The icing on wind turbines occurs when super-cooled water droplets collide with the wind turbine structure in the passing clouds (in-cloud icing) and/or freezing rain or drizzle freezes on the exposed wind turbine structure (precipitation icing). Within the scope of this Ph.D. work, the focus is made on the in-cloud icing on the wind turbines.\n<p>While there are existing standards and guidelines for the design and operation of wind turbines in normal, temperate climates, for example, the International Electrotechnical Commission standards for offshore turbines, including IEC 61400-1, IEC 61400-3, and the standards for the processes of type certification, which are commonly used to certify turbines in Europe (IEC 2001, 2005, 2010a, 2010b). However, no such definite framework exists for the design, operation and maintenance of wind turbines in cold, ice-prone regions. Thus, the better understanding of the atmospheric ice accretions on wind turbines and their negative effects, such as losses in power production due to the icing is a critical objective for the successful operation of the wind power in CC, ice-prone regions.\n<p>For the purposes of better understanding of the icing physics, involved in the icing on the wind turbines, the analytical, numerical and the experimental tools are used in this project. The analytical modelling is done by using the ISO 12494 standard: “Atmospheric Icing on Structures” with some modifications done to it, in order to permit analytical modelling of ice accretion on wind turbines, using basic circular cylinders from ISO 12494 as a reference collector. The numerical modelling scheme employs the usage of modern Computational Fluid Dynamics (CFD) tools such an ANSYS FENSAP-ICE and ANSYSFluent which are used to study the ice accretion process on airfoils and blades. These CFD tools allow for the study of icing physics in greater detail than the analytical model allows, for example by simulating the resultant ice shapes and their impact on the aerodynamic performance of the iced airfoils, when compared to the clean ones. The experimental methodology of this work encompasses usage of the icing tunnel experimental data, for the validation purposes of the numerical modelling, and the field measurements data from the Supervisory Control and Data Acquisition (SCADA) system, taken from a wind park operating in the CC region. The main reason for this is to perform a wind resource assessment study in the CC, ice prone region, in addition to the use of supplementary statistical and numerical modelling tools, such as T19IceLossMethod and WindSim.\n<p>The results of atmospheric ice accretion on the wind turbine blades show that the aerodynamic performance changes mainly due to difference in droplet freezing fraction as due to low freezing fraction for the glaze ice conditions, higher amount of the water runback and the aerodynamic heat flux along leading edge is observed which results in the complex horn type ice shapes. The phenomenon of the flow interaction in the third dimension results in the velocity magnitudes being reduced in the 3D simulations, when compared to the 2D simulations. This, in turn, affects the ice accretion process, as the higher velocity magnitudes in the 2D cases result in the higher droplet inertia, collision efficiencies and the maximum impingement angles, which results in more ice mass accreted along the leading edge with the thicker and larger ice shapes present in the 2D simulations.\n<p>The results of wind resource assessment of ice prone region show that power production for wind parks can be lower in CC regions when compared to identical wind parks/turbines situated in warmer temperate climates. However, the icing-related issues and the associated power losses need to be solved. It shows that duration and timing of the icing event is different for different wind turbines in a wind park, which clearly indicates that the icing events depend upon the meteorological conditions, airflow behaviour and also the location of the wind turbine. Even in the same wind park, it is not given that ice will accrete on all wind turbines under the same instrumental and on-site conditions. The wind park layout and changes in flow behaviour affects the occurrence of ice accretion, despite the favourable conditions for icing events being present.\n<p>Two main topics have been considered in this Ph.D. work: the atmospheric ice accretion on wind turbine blade and the performance losses associated with it; and the wind resource assessment in the ice prone region. Both of these topics are of major importance for the wind industry in CC, ice prone regions, due to the challenges present in the form of potential icing conditions and events and the resultant energy production losses. The results obtained in this Ph.D. thesis can be summarized, in short, as follows: power losses due to icing on wind turbines occur not because of a single reason, but through a combination of effects that need to be taken into account carefully during the wind park design process. These effects include the blade profile surface roughness and heat fluxes, which change significantly during the ice accretion process, and, in turn, affect the airflow and droplet behaviour. The change in the accreted ice shape affects both the airflow behaviour and the aerodynamics performance. With the increase in the atmospheric temperature, the type of accreted ice also changes from dry rime to wet glaze ice, which leads to a change in the ice density and also the accreted ice shapes on the wind turbine blades. Generally, wet ice growth is more damaging for wind turbine operations in icing conditions as compared to dry rime ice growth, due to higher degradation of aerodynamic characteristics under the glaze icing conditions.\n<p>The results obtained in this work also provide the need and motivation for improving the understanding about icing effects on the wind turbine blades and the improvement of the existing (or creating new) anti-/de-icing technologies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.067
GPT teacher head0.301
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2021
Admission routes1
Has abstractyes

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