Downloaded from orbit.dtu.dk on: Jul 25, 2022Wind resource assessment using the WAsP softwareMortensen, Niels GyllingPublication date:2018Document VersionPublisher's PDF, also known as Version of recordLink back to DTU OrbitCitation (APA):Mortensen, N. G. (2018). Wind resource assessment using the WAsP software. DTU Wind Energy. DTU WindEnergy E No. 174General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyrightowners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. Users may download and print one copy of any publication from the public portal for the purpose of private study or research. You may not further distribute the material or use it for any profit-making activity or commercial gain You may freely distribute the URL identifying the publication in the public portalIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediatelyand investigate your claim.
46200 Planning and Development of Wind Farms:Department ofWind EnergyE Report 2019Wind resource assessment using WAsP softwareNiels G. MortensenDTU Wind Energy E-0174December 2018
Authors: Niels G. MortensenDTU Wind Energy E-0174Title: Wind resource assessment using WAsP softwareDecember 2018Department: Wind EnergySummary (max 2000 characters):These course notes are intended for the three-week course 46200 Planningand Development of Wind Farms given each year at the Technical Universityof Denmark. The purpose of the course notes is to give an introduction towind resource assessment and siting issues using the WAsP (version 12)suite of programs.ISBN no.978-87-93549-42-5Project no.44537 E-13SponsorshipDTU Wind EnergyFront pageProspective wind farm site innorthern Portugal, with a colouredrepresentation of the windresource draped over the terrain.(Image 2009 DigitalGlobe. DataSIO, NOAA, U.S. Navy, NGA,GEBCO)Pages: 43Tables: 3Figures: 28References: 21Technical University of DenmarkDepartment of Wind EnergyFrederiksborgvej 399Building 1184000 RoskildeDenmarkTelephone 46775027nimo@dtu.dkwww.vindenergi.dtu.dk
Contents1 0BIntroduction 51.11.21.31.418BObservation-based wind resource assessment 61 umerical wind atlas methodologies 79BN20BWind resource assessment procedure 821BEnergy yield assessment procedure 92 1BMeteorological measurements 102.1 2BDesign of a measurement programme 102.2 3BQ2 uality assurance 103 2BWind-climatological inputs 113.1 4BW2 ind data analysis 113.2 5BO2 bserved wind climate 124 3BTopographical inputs 134.1 6BE2 levation map 134.2 7BL2 and cover map 144.3 8BS2 heltering obstacles 165 4BWind farm inputs 165.1 9BW2 ind farm layout 165.2 0BW3 ind turbine generator 176 5BWAsP modelling 176.1 Modelling parameters 186.2 32BWAsP analysis 206.3 3BWAsP application 206.4 Validation of the modelling 216.5 35BSpecial considerations 247 6BAdditional technical losses 258 7BModelling error and uncertainty 268.1 6BP3 rediction biases 288.2 7BS3 ensitivity analysis 288.3 8BU3 ncertainty estimation 299 8BWind conditions and site assessment 309.1 39BExtreme wind and turbulence intensity 319.2 40BIEC site assessment 3261BWindfarm Assessment Tool (WAT) 339BReferences 3310BAcknowledgements 35A1BWAsP best practice and checklist 36B12BNote on the use of SAGA GIS 38C13BDigitisation of the land cover (roughness) map 42D14BThe Global Wind Atlas 43DTU Wind Energy E-01743
46200 Planning and Development of Wind FarmsThe general course objectives, learning objectives and contents for DTU 46200 are listedbelow for reference. The full course description is given in the DTU Course Catalogue.The present notes are related to the wind resource assessment and siting parts only.General course objectives15BThe student is provided with an overview of the steps in planning and managing thedevelopment of a new wind farm. The student is introduced to wind resource assessmentand siting, wind farm economics and support mechanisms for wind energy. An overviewof the various environmental impacts and societal challenges from wind farms is offered.Learning objectives16BA student who has met the objectives of the course will be able to: Describe the methodologies of wind resource assessment and their advantagesand limitations. Explain the steps in the selection of a site for measurement of the wind resourceand good practice for measurement of the wind resource. Calculate the annual energy production using the WAsP software for simplewind farm cases in terrain within the operational envelope of the WAsP model. Identify and describe factors adding to the uncertainty of the wind resource andwind farm production estimates. Estimate the most important key financial numbers of a wind project andexplain their relevance. Identify the main environmental impacts from a wind farm and suggestmitigation measures. Explain the three most common policy tools for support of wind energy projects Explain the steps in the development of a wind farm with a balanced emphasison the annual energy production, wind turbine loads, economics, gridconnection, environmental impact and societal context of a project. Explain the main steps in developing the grid connection of a wind farm. Carry out a simple stakeholder analysis and suggest appropriate engagementstrategies.Contents17BAn introduction to market, policy and support mechanisms relevant to wind energy.Wind resources and wind conditions: anemometry; design and siting of meteorologicalstations; wind distributions; observed, generalised and predicted wind climates;observational and numerical wind atlases, elevation maps and land cover, roughnessclasses and roughness maps; sheltering obstacles; wind farm wake effects, micro-scaleflow modelling (WAsP), wind resource mapping; wind farm layout; wind farm annualenergy production.The procedure for obtaining an environmental permit for a wind farm. The various typesof environmental impacts from a wind farm. Introduction to wind farm economics.Introduction to grid connection. The students will work in groups of 4. The group workwill be documented in a report and will be presented orally by all course participants.4DTU Wind Energy E-0174
1 Introduction0BWind resource assessment is the process of estimating the wind resource or wind powerpotential at one or several sites, or over an area. One common and well-known result ofthe assessment could be a wind resource map, see Figure 1.Figure 1. Wind resource map for Serra Santa Luzia region in Northern Portugal. (Image 2009 DigitalGlobe. Data SIO, NOAA, U.S. Navy, NGA, GEBCO. 2009 Cnes/SpotImage. Image 2009 GeoEye).The wind resource map usually shows the variation over an area of the mean wind speedor power density, for a given height above ground level. While this may provide a goodindication of the relative magnitude of the wind resource, a more realistic estimate isobtained when the sector-wise wind speed distributions are combined with the powercurve of a given wind turbine to obtain a power production map, see Figure 2.Figure 2. Power production map for a sample wind farm in Northern Portugal. (Image 2009 DigitalGlobe. Data SIO, NOAA, U.S. Navy, NGA, GEBCO).DTU Wind Energy E-01745
The result of wind resource assessment is therefore an estimate of the mean wind climateat one or a number of sites, in the form of: Wind direction probability distribution (wind rose), which shows the frequencydistribution of wind directions at the site, i.e. where the wind comes from, Sector-wise wind speed probability distribution functions, which show thefrequency distributions of wind speeds at the site.Wind resource assessment provides important inputs for the siting, sizing and detaileddesign of the wind farm and these inputs are exactly what the WAsP software provides.When it comes to the siting of individual wind turbines, a site assessment (IEC 61400-1)is usually carried out. This will provide estimates for each wind turbine site of the 50year extreme wind, shear of the vertical wind profile, flow and terrain inclination angles,free-stream turbulence, wind speed probability distribution and added wake turbulence.This additional information may be obtained by using the WAsP Engineering software.1.1 Observation-based wind resource assessment18BConventionally, wind resource assessment and wind farm calculations are based on winddata measured at or nearby the wind farm site. The WAsP software (Mortensen et al.,2014) is an implementation of the so-called wind atlas methodology (Troen and Petersen,1989); this is shown schematically in Figure 3.WAsP analysis: from wind data to generalised wind climate1. Time-series of wind speed and direction observed wind climate (OWC)2. OWC met. mast site description generalised wind climate (wind atlas)WAsP application: from generalised to predicted wind climate3. Generalised wind climate site description predicted wind climate (PWC)4. PWC power curve annual energy yield of wind turbineWind farm production: from predicted wind climate to gross yield5. PWC wind turbine (WTG) characteristics ‘WAsP gross’ wind farm yield6. PWC WTG characteristics wind farm layout wind farm wake losses7. ‘WAsP gross’ yield – wake losses ‘WAsP net’ wind farm yieldPost-processing: from ‘WAsP net’ yield to net yield (P50 and Px)8. ‘WAsP net’ yield – technical losses net annual energy yield (P50)9. Net yield – uncertainty estimate Net yield PxFigure 3. Wind atlas methodology of WAsP (Troen and Petersen, 1989). Meteorologicalmodels are used to calculate the generalised wind climatology from the measured data –the analysis part. In the reverse process – the application of wind atlas data – the windclimate at any specific site may be calculated from the generalised wind climatology.Note, that the WAsP software estimates the ‘WAsP gross’ and ‘WAsP net’ yields only(steps 1-7 in Figure 3); the post-processing steps (8-9) must be carried out separately.The wind farm assessment tool (WAT) contain simple tools to aid in these calculations.6DTU Wind Energy E-0174
As can be deduced from Figure 3, WAsP is then based on two fundamental assumptions:first, the generalised wind climate is assumed to be nearly the same at the predictor (met.station) and predicted sites (wind turbines) and, secondly, the past (historic wind data) isassumed to be representative of the future (the 20-y life time of the wind turbines). Thereliability of any given WAsP prediction depends very much on the extent to which thesetwo assumptions are fulfilled.1.2 Numerical wind atlas methodologies19BWAsP has become part of a much larger framework of wind atlas methodologies, whichalso encompasses mesoscale modelling and satellite imagery analysis. This frameworkhas been developed over the last two decades at Risø and DTU (Frank et al., 2001;Badger et al., 2006; Hansen et al., 2007) in order to be able to assess the wind resourcesof diverse geographical regions where abundant high-quality, long-term measurementdata does not exist and where important flow features may be due to regional-scaletopography. Figure 4 is a schematic presentation of this entire framework.Figure 4. Overview of state-of-the-art wind atlas methodologies (Hansen et al., 2007).Wind resource assessment based on mesoscale modelling, the numerical wind atlas, canprovide reliable data for physical planning on national, regional or local scales, as well asdata for wind farm siting, project development, wind farm layout design and micro-sitingof wind turbines. However, bankable estimates of power productions from prospectivewind farms require additional on-site wind measurements for one or more years.The present course notes thus describe mainly the ‘grey’, ‘green’ and ‘yellow’ parts ofthe diagram above, i.e. what is referred to as the observational wind atlas methodology.Different inputs to the WAsP modelling are described in Sections 2 to 5; the modellingitself is described in Section 6, and the modelling errors and uncertainties in Section 8.Section 7 lists the different types of additional losses in the wind farm and Section 9contains a very brief cookbook approach to site assessment using WAsP Engineering.In addition to the present course notes, the WAsP help system (Mortensen et al.,2014) contains a Quick Start Tutorial section which illustrates the essentials of theWAsP software user interface.DTU Wind Energy E-01747
1.3 Wind resource assessment procedure20BThe descriptions above and in the remainder of these notes reflect closely the structureand terminology of the wind atlas methodology and the WAsP implementation of this. Inmore general terms, the steps in the initial wind resource assessment procedure can beillustrated as is shown in Figure 5.Figure 5. Overview of the steps in the wind resource assessment procedure.Wind measurements are made at wind farm site(s) using met. mast(s); every 10 minutesall year round. These raw site wind data are converted into calibrated wind data by thedata logging system, employing calibration expressions for each individual instrument.The quality and integrity of the calibrated wind data are then assessed; e.g. by visualinspection of the time-series and by data analyses, as described in Section 3. Missingdata may be substituted with values derived from other similar or redundant sensors.The aim is to establish the most accurate, reliable and complete data set for the site mast.Next, this data set must be seen in the context of the long-term wind climate at the siteand an adjusted data set representing the long-term climatology should be established.The analyses so far are mostly carried out using the wind data time-series. When a dataset representing the long-term climatology at the site has been established, this can beused to calculate the statistics of the wind climate: the distributions of wind speed andwind direction, as well as mean values, standard deviations and other statistics.The last step in the wind resource assessment procedure shown in Figure 5 is to predictor estimate the long-term wind climates at the prediction sites, which are most often theturbine sites in a wind farm. The tool used for this step is a microscale flow model whichhas the ability to extrapolate the observed wind climate to the prediction sites.There are several kinds of ‘prediction’ or ‘estimation’ at play here: first, we estimatewhat the wind climate has been like in the past at our site mast, by referencing ourobservations to a suitable long-term data set. Secondly, we try to predict what the windclimate has been like at our wind turbine sites, by extrapolating the observed windclimate from the met. mast to those sites.Finally, we often (silently) make the assumption (and prediction) that the predicted windclimate is representative of what is going to happen in the future; say, the over thelifetime of the wind turbines.8DTU Wind Energy E-0174
1.4 Energy yield assessment procedure21BWe can focus on the energy yield assessment procedure in a similar way as above andidentify the following steps (Figure 6):1. Site wind climate Site wind data [long-term extrapolation effects]Using a long-term extrapolation procedure, the site wind data are referencedand adjusted according to the long-term climatology of the area.2. Reference yield Wind climate at hub height plus [power curve]The reference yield is calculated using the predicted wind climate at hub heightat the mast location and the site-specific wind turbine power curve. However,most of the time this step is surpassed and the gross yield is calculated directly.3. Gross yield Reference yield [terrain effects]Using a flow model, the observed wind climate at the mast site is transformed tothe predicted wind climates at the wind turbine sites of the wind farm. The ‘flowmodelling’ part of Figure 6 includes both vertical and horizontal extrapolations.4. Potential yield Gross yield – [wake losses]Using a wake model, the wake losses at each turbine site are estimated andsubtracted from the gross yield. This corresponds to the WAsP ‘net yield’.5. Net yield Potential yield – [technical losses]The additional technical (operational) losses in the wind farm are subsequentlyestimated and subtracted from the potential yield to get the net yield value (P50)at the point of common coupling (PCC).6. P90 yield P50 yield – 1.282 [uncertainty estimate]The aggregate uncertainty of the entire energy yield assessment process isestimated and the net yield may be adjusted to obtain a net value correspondingto a certain probability of exceedance, e.g. the P90 value as shown above.By dividing the prediction process into these steps we have isolated the different modelcalculation results and it is therefore fairly straightforward to compare different methodsand models (Mortensen et al., 2012, 2015). Figure 6 illustrates the steps in the procedure.Figure 6. Overview of steps in the wind farm energy yield assessment procedure.These steps and their definitions are not universally agreed or even used; however, IECand Measnet working groups are addressing these issues at the moment.DTU Wind Energy E-01749
2 Meteorological measurements1BWAsP predictions are mostly based on the observed wind climate at the met. station site;i.e. time-series data of measured wind speeds and directions over one or several yearsthat have been binned into intervals of wind direction (the wind rose) and wind speed(the histograms). Therefore, the quality of the measurement data has direct implicationsfor the quality of the WAsP predictions of wind climate and annual energy production.In short, the wind data must be accurate, representative and reliable.2.1 Design of a measurement programme2BIt is beyond the scope of these course notes to describe best practice for wind measurements in detail, but the aspects discussed below are particularly important.If possible, the measurement programme should be designed based on a preliminaryWAsP analysis of the wind farm site. Such design ensures that the measurements will berepresentative of the site, i.e. that the mast site(s) represent the relevant ranges ofelevation, land cover, exposure, ruggedness index, etc. found on the site. In short, weapply the WAsP similarity principle (Landberg et al., 2003) as much as possible whensiting the mast(s). This design analysis may conveniently be based on SRTM elevationdata and land cover information from satellite imagery such as Google Earth.It is equally important in the design stage to use an observed wind climate that resemblesthe wind climate that may be observed at the wind farm site; e.g. by using data from anearby met. station or modelled data from the region. A representative wind rose isparticularly valuable as this may be used to determine the design of the mast layout; e.g.the optimum boom direction is at an angle of 90 (lattice mast) or 45 (tubular mast) tothe prevailing wind direction. The height of the top (reference) anemometer should besimilar to that of the wind turbine hub height; preferably 2/3 hhub.Anemometers should be individually calibrated according to international or at leasttraceable standards. Several levels of anemometry should be installed in order to obtain ahigh data recovery rate (above 90-95%) and for analyses of the vertical wind profiles.Air temperature (preferably at hub height) and barometric pressure should be measuredin order to be able to calculate air density, which is used to select the appropriate windturbine power curve data set.It is extremely valuable – and sometimes required for bankable estimates – to install twoor more masts at the wind farm site; cross-prediction between such masts will provideassessments of the accuracy and uncertainty of the flow modelling over the site. Two ormore masts are also required in complex and steep terrain, where ruggedness index(RIX) and RIX analyses – as well as WAsP CFD calculations – are necessary.2.2 Quality assurance23BFor projects where the measurement campaign has already been initiated or carried out,it is important to try to assess the quality of the collected wind data, as well as to ensurethe quality of any and all site data used for the analysis. A site inspection trip is requiredand should be part of any (commercial) WAsP study – whether it is a second opinion,due diligence or feasibility study.A number of WAsP Site/Station Inspection checklists and forms exist for planning thesite visit and for recording the necessary information. The positions of the met. mast(s)and turbine sites are particularly important. Bring a handheld GPS (Global Positioning10DTU Wind Energy E-0174
System) for the site visit and note down the projection and datum settings; change theseif required. Determine the coordinates of all masts, turbine sites, landmarks and othercharacteristic points on site (repeated readings over several days increase the accuracy).Documentation of the mast setup and site may be done by taking photos of the stationand its surroundings (12 30 -sector panorama). Use a compass when taking the sectorpictures. Download the GPS data and photographs to your PC as soon as possible (daily).The characteristics of anemometers and wind vanes deteriorate over time and after oneor a few years they may not operate according to specifications. An important part ofoperating a wind-monitoring mast is therefore to exchange the instruments at regularintervals, as well as rehabilitating and recalibrating instruments in stock.3 Wind-climatological inputs2BThe wind-climatological input to WAsP is given in the observed wind climate, whichcontains the wind direction distribution (wind rose) and the sector-wise distributions ofmean wind speed (histograms), see Figure 7. The observed wind climate file should alsocontain the wind speed sensor (anemometer) height above ground level in metres and thegeographical coordinates of the mast site: latitude and longitude. The latitude is used byWAsP to calculate the Coriolis parameter.Figure 7. Sample observed wind climate from Sprogø 1977-99; wind rose to the left andomni-directional wind speed distribution to the right (data courtesy of Sund & Bælt).Wind speeds must be given in metres per second [ms 1] and wind directions in degreesclockwise from north [ ], i.e. from 0 (north) through 360 . The wind direction indicatesthe direction from which the wind blows. The observed wind climate is usually given for12 sectors and the wind speed histograms using 1 ms 1 wind speed bins.3.1 Wind data analysis24BThe wind data analysis and calculation of the observed wind climate may convenientlybe done using the WAsP Climate Analyst. Whether the wind data are measured by theorganisation carrying out the analysis or by a third party, a number of data characteristicsmust be known, such as: the data file structure, time stamp definition, data resolution(discretisation), calm thresholds, and any flag values used for calms and missing data.This information may be collected by filling out a WAsP Data Description Form; in thesubsequent analysis all input values in the Climate Analyst should correspond to the dataspecifications.In the Climate Analyst, the time traces of wind direction and speed, as well as a polarrepresentation of concurrent data, can be plotted and inspected, see Figure 8.DTU Wind Energy E-017411
Figure 8. Time traces of wind direction (upper, 0-360 ) and wind speed (lower, 0-30m/s) from Sprogø for the year 1989. The graphic in the lower left of the Climate Analystwindow shows concurrent data in a polar representation (data courtesy of Sund & Bælt).The Climate Analyst checks the time stamps and observation intervals upon input ofeach data file, and also checks for missing records in the data series. However, the mainquality assurance (QA) is done by visual inspection of the time series and polar plot, aswell as the resulting observed wind climate. Things to look out for are e.g.:1. Are there any spikes or sudden drops in the data series?2. Are there periods of constant data values in the data series?3. Are there periods of missing data in the data series?4. Are there any unusual patterns in the data series?5. Are there any unusual patterns in the polar scatter plot?6. Do the wind speed time traces follow each other for different anemometers?7. Do the wind direction time traces follow each other for different vanes?8. Do the measured and Weibull-derived values of U and P compare well?9. Does the calm class (0-1 ms 1) in the histogram look realistic?Finally, the observed wind climate is calculated and exported to an OWC file. The OWCfile can subsequently be inserted into the WAsP hierarchy, as a child of a meteorologicalstation member.3.2 Observed wind climate25BThe observed wind climate (OWC) should represent as closely as possible the long-termwind climate at anemometer height at the position of the meteorological mast. Therefore,an integer number of full years must be used when calculating the OWC, in order toavoid any seasonal bias. For the same reason, the data recovery rate must be quite high( 90-95%) and any missing observations should preferably be distributed randomlyover the entire period.Wind data series from prospective wind farm sites rarely cover more than one or a fewfull years, so they must be evaluated within the context of the long-term wind climate, inorder to avoid any long-term or climatological bias. Comparisons to near-by, long-termmeteorological stations or to long-term modelled data for the area can be made usingsimple (or complicated) measure-correlate-predict (MCP) techniques.12DTU Wind Energy E-0174
WAsP uses Weibull distributions to represent the sector-wise wind speed distributionsand the so-called emergent distribution for the total (omni-directional) distribution. Thedifference between the fitted (and emergent) and the observed wind speed distributionsshould therefore be small: less than about 1% for mean power density (which is used forthe Weibull fitting) and less than a few per cent for mean wind speed.4 Topographical inputs3BThe topographical inputs to WAsP are given in a vector map, which can contain heightcontour lines, roughness change lines and lines with no attributes (say the border of thewind farm site). In addition, nearby sheltering obstacles may be specified in a separateobstacle group, which can be shown on the map too.Map coordinates and elevations must be specified in meters and given in a Cartesian mapcoordinate system. The map projection and datum should be specified in the Map Editorso this information is embedded in the map file. All metric coordinates used in the WAsPworkspace should of course refer to the same map coordinate system. Obstacle distancesand dimensions must likewise be given in meters.The Map Editor can do the transformation from one map coordinate system to another;the Geo-projection utility program in the Tools menu can further transform single points,lists of points and lists of points given in an ASCII data file.4.1 Elevation map26BThe elevation map contains the height contours of the terrain, see Figure 9. These maybe digitised from a scanned paper map – as described in the Map Editor Help facility –or may be obtained from a database of previously digitised height contours, establishedby e.g. the Survey and Cadastre of a country or region. Alternatively, they can also begenerated from gridded or random spot height data using contouring software.The elevation map should extend at least several (2-3) times the horizontal scale ofsignificant orographic features from any site – meteorological mast, reference site, windturbine site or resource grid point. This is typically 5-10 km. A widely cited rule for theminimum extent of the WAsP map is max(100 h, 10 km), where h is the height of thecalculation point above ground level; this is usually sufficient for the elevation map too.The accuracy and detail of the elevation map are most critical close to the site(s),therefore it is recommended to add all spot heights within the wind farm site and close tothe meteorological mast(s); one can also interpolate or digitise extra height contours ifnecessary. The contour interval should be small ( 10 m) close to calculation sites,whereas the contour interval can be larger further away from these sites ( 10 m).Non-rectangular maps (circular, elliptic, irregular) are allowed and sometimes preferred,e.g. in order to reduce the number of points in the map, while at the same time retainingmodel calculation accuracy. There is no limitation to the size of the map, but thecalculation time is proportional to the computer memory used for the map data.The final elevation map should be checked for outliers and errors by checking the rangeof elevations in the map. An elevation map generated from a gridded data set could alsobe compared to a scanned paper map of the same area. If comparing the relief to GoogleEarth (GE), it should be borne in mind that the GE representation of the 3D terrain isusually much smoother than the WAsP representation.DTU Wind Energy E-017413
Figure 9. Elevation map for a meteorological station in South Africa (data courtesy ofthe WASA project). Three contour intervals are used: 5 m close the site and 10 and 20 mfurther away. Map grid lines are shown for every 10 km.Contour maps from gridded data48BHigh-resolution gridded (raster) elevation data exist for many parts of the world, onesuch data set is derived from the Shuttle Radar Topography Mission (SRTM). The MapEditor can employ SRTM data directly for making elevation vector maps.For other gridded data sets, it may be necessary to construct the height contours (vectormap) from the raster data. One freely available software program that can be used tomake WAsP vector maps from gridded data is described in appendix B: “A note on theuse of SAGA GIS” (Conrad et al., 2015)
DTU Wind Energy E-0174 5 1 0BIntroduction Wind resource assessment is the process of estimating the wind resource or wind power potential at one or several sites, or over an area. One common and well-known result of the assessment could be a wind resource map, see Figure 1. Figure 1. Wind resource map for Serra Santa Luzia region in Northern .
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