Morten

The effective TI is the 90% percentile of the statistical distribution of ten-minute mean turbulence conditions. In WAT, this probability distribution is modelled as log-normal distributions for each sectors, and the error message reports a difficulty finding the 90% percentile of the mixed distribution. I think that the problem occurs for observations were some sectors have zero variance. This is incompatible with the assumption of a log-normal distribution, but I remember working with a more robust solver for a not yet released WAT version. You are welcome to send your test project to waspsupport@dtu.dk if you like me to inspect it.

WAT is a 32-bit program. This imply memory limitations, so I decided that it was safer to work with a fixed result table rather than a flexible one.

Hi Dave, The DTU general-purpose files server has been discontinued because the system provider (Hitachi) no longer supports the product. Our IT department instructs us to use MS OneDrive instead, however only to named users, so I cannot give a link to al users. I can mail you a personal link and I will also try to find a general solution as many people have a problem with this. Best regards, Morten

Hi Jonathan, If I understand you correctly, this error occurs during data import in WACA 3.1. The error message does not reveal much, except that the program is taking the logarithm of a negative number as part of a data correction. The problem could either relate to the data or to an unusual option, maybe resulting in a data point with a negative wind speed. If the problem persists, I suggest that you take screen dumps of all steps in WACA import dialog windows and mail them to waspsupport@dtu.dk and include sample data and the version number found in the Help>About Climate Analyst... Cheers, Morten

Unfortunately, WAsP Map Editor 12.4 have problems like this, but the previous version 12.3 still works. I am not sure if we have a recommended way to revert to this version without affecting other programs in the WAsP bundle. Personally, I just stored a copy of WAsPMapEditor12_3.exe on my computer, so I can launch either version 12.3 or 12.4 when needed. I placed a small ZIP file with version 12.3 at https://files.dtu.dk/u/5iTwqxUk8Or0JPCv/444fd5ea-3df6-4597-a484-0591b88dd76f?l and (if your IT department permit) you might download, unzip and run that manually. The download link is active one year from now. NB: The shortcut links from WAsP and the Windows Start menu will still point to version 12.4, so you have to launch version 12.3 from the Windows file manager or similar.

Hi Lino, I lack personal experience with this, but I assume that typical applications for the IEC61400-12-1 power curve test are A turbine manufacturer needs to verify turbine performance in order to help customers predicting the production and economical viability of a wind energy project. These measurements are often made at a special test station in nearly flat terrain. A wind-farm developer and manufacturer agrees to verify the power-curve at a new wind farm and the manufacturer guarantees to compensate the developer if the tested turbine is seriously underperforming. I do not know how the parties agrees which turbine to use, but I assume that they want to avoid wake affects and too complex terrain, and it will be practical to test one representative turbine only. To avoid legal dispute, it is probably wise to make this contract long before wind farm construction and hire a neutral consultant for power-curve tests according to IEC standards.

Hi Deepali, The link points to a ZIP file and for security reasons most browsers will first try to prevent you from downloading it. However, I use Edge and I was able to overrule the warning and download anyway. Here is a short demonstration:

Hi Lino, The IEC61400-12-1 standard states that the ideal distance between the reference mast and the tested turbine is 2.5 times the rotor diameter, 2.5D. I believe this is a compromise between good correlation between the free wind at mast and turbine site and reasonably low effect of flow blockage by the operating turbine. The standard also specify the allowable range to be 2-4D, so unless your turbine is very big, 600m will be a little too far. Sorry for the delay, by mistake I did not subscribe to this topic. Cheers, Morten

Dear Bepi, The previous question by HPJ concerned flow inclination angles by the WAsP Engineering program. To see a map for a specific wind direction you click Insert> New wind from the WAsP Engineering main menu, select Maps and sites> Wind Grid maps, right-click Flow inclination grid and select Open in new spatial view from the popup menu. WAsP Engineering will display maps of individual velocity components in a similar way. Flow inclination angles are included as fields in the WAsP resource grids. These results are only valid when using the WAsP CFD flow model, not the standard WAsP flow model called IBZ. I think the result for all directions still are calculated as the worst local inclination angle for any wind direction, as defined in previous editions of the IEC 61400-1 standard. To see the inclination angles defined in the current IEC 61400-1 Edition 4 - which is an energy-weighted average over all wind directions - you can either use tools> WAsP CFD results viewer from the WAsP main menu or the Windfarm Assessment Tool. Chapter 11.2 of the IEC 61400-1 standard presents a method involving planes fitted to the terrain elevation surface. The purpose of this is just to assess the terrain complexity, not flow inclination angles. This assessment is implemented in the WAsP CFD results viewer and the Windfarm Assessment Tool, not directly in WAsP or WAsP Engineering. Cheers, Morten

I can think of two related problems: The recommendation for WAsP AEP predictions, before the windfarm construction, is to select a reference mast position, which is as representative as possible, e.g. with a ruggedness index close to the average RIX number of the turbines. Another problem is verification of power performance after wind farm construction, where the IEC 61400-12-1 specifies a procedure for power curve verification. For this, the manufacturer and wind farm operator agrees on test turbine and mast position, where the terrain is not too complex, and only applies data from a sector where measurement are not disturbed by wake effects. WAT can help with the IEC 61400-12-1 terrain assessments. However, your application seems different. I am not sure that I understand what you mean by calibrating the wind speed, but you probably need a reliable wind signal for a wind farm in operation, perhaps with curtailments and other complicating factors. I do not think that there is a standard for this, and the solution may on the application. Things to consider: Are there significant terrain effects? Is it possible to estimate speedup effects by flow model or measurements? Should you avoid wake effects, e.g. by installing multiple reference masts for winds from different directions?

It you deactivate a turbine site in the main WAT object hierarchy, it is treated as if it does not exist in the WF layout. You will also find some check boxes in the additional tree view next to the WF power curve. The production form deselected turbine sites does not contribute directly to the WF power curve, but there is an indirect effect since their wakes affect the selected turbines. You can use it if you want to know the AEP a sub-group of turbines, while other turbine groups are still in operation. The thrust-coefficient curve used in WAsP and WAT has a so-called static thrust coefficient (see the WAsP turbine editor), which is applied outside the wind-speed range of turbine operation, i.e. where the rotor is parked or idling. It is usually quite small and should not affect the AEP integrated over all wind conditions much.

WAT tries to simplify the user interface by hiding options which makes no difference for the current. The options for Performance measurement sectors is a good example of this. as it is only shown when you select at turbine site with an site calibration mast as child object.

I will not claim that WAT has an integrated reporting tool, but you can select a plot or table and copy this to the Windows clipboard via Ctrl+C on the keyboard and then paste it into Excel or Word. This will copy what you currently see on the screen, so you may have to repeat with different modelling options. You can also export tables and plots via the tools under edit>export from the main menu, and some of these will iterate over turbine sites. When implementing this, I imagined that the user was writing a report for a client and just needed to insert key results from WAT. I did not attempt to automate a complete report.

The limit on the length of the local time series is exactly three years. I am not sure why the developers introduced this unnecessary limitation - maybe they were simply proud that the method could make realistic 50-year extreme wind estimates from short time series. The spectral correction method actually applies a 21 year long time series of CFDDA reanalysis data with correction by a short time time series of local observations. The idea is that the local data will add fast variations missing in the CFDDA data. The corrected series (or actually spectrum) will then provide more realistic extreme values. We do not recommend to substitute local observations by mesoscale data as they typically have too little high frequency variation.

You are right. Sometimes the software enables you to calculate EWC and U50 estimates even with sparse data and you wonder about the accuracy. Both annual-maximum and peak-over-threshold methods have associated uncertainty estimates. In WAsP Engineering, these uncertainties are indicated by the curves around the extreme wind versus return period plot. This statistical uncertainty depends on sample size and Gumbel alpha parameter. However, there is even uncertainty on the uncertainty estimate itself, so take care with very small samples. The IEC 61400-1 standard includes an annex on measure-correlate-predict methods based on correlation with a reference station. It also discusses extreme-wind estimates based on the MCP long-term-corrected series, and it recommends at least seven years for the reference station. For extreme winds in tropical storms, it recommends methods based on satellite-tracking. I think you need something similar if you only have local data, but it also depends on the uncertainty you are willing to accept. In WAsP Engineering, I recommend to use the spectral correction method, whenever possible. This combines local information with a database using 21 years of modelled data with a short time series of local observations, e.g. only one year long. Unfortunately, the database does not yet cover Australia.

Hi Cristi, I contacted our programmer who replied: Hi Morten, your advice on the forum is correct. There is nothing we can do to make it work, as far as I know. The drivers for the dongles were provided by the company who made the hardware dongles and there is no upgrade for modern Windows OS. Sorry. Best regards, Morten

Hi Cristi, I think the license system of WAsP 10 was the old one based on hardware dongles, and my guess is that the software drivers of those dongle are incompatible with Windows 11. We had reports from Windows 10 users with similar problems. Unfortunately, we no longer support WAsP 10, so my advice is to upgrade to the present WAsP version. Best regards, Morten

In the context of fitting a Weibull distribution to an empirical distribution, I would call the wind speeds above the mean wind speed the high wind speed range. Try to open an observed wind climate in WAsP or WACA and compare the two distributions for high wind speeds and for low ones, and I think you will see what I mean. I do not recommend any correction to the model. We should remember that the AEP is found by an integral of the mean wind speed probability distribution and power curve, so we are not concerned about PDF model errors at wind speeds with zero or very low production.

In WAsP, the WTG object refer to the wind turbine generator, specifying power and thrust-coefficient curves, so I guess that you are actually referring to a turbine site placed at the met mast position. In this way you are making a self-prediction test, and wonder about discrepancies in the predicted mean wind speed. There are many ways to fit a Weibull distribution and in WAsP the fit is designed to match the mean of the cube of the observed wind speeds and the probability of winds higher than the empirical mean wind speed. This usually results in a good fit to data in the high-wind range but a less accurate fit at lower wind speeds. This is a deliberate choice, as wind power production mostly depends on accurate modelling in the high wind-speed range. However, unless the observed wind speed distribution is a perfect Weibull distribution, there is no guarantee that the fitted distribution will match the mean wind speed of observation. This is the main reason for the discrepancy. In addition, there can be small errors in sector-wise frequencies and Weibull distributions, due to a rotation of the wind rose when converting the observed wind climate to the generalized wind climate and a reverse rotation back to a (self-)predicted wind climate. These rotations shifts probability mass between sectors, and the finite sector width leads to discretization errors. This type of error increases for wind climates with a large variation between neighboring sectors.

WAsP applies the wind atlas method. The traditional input is 10-min time series of wind speed and direction measured by a Lidar or anemometer on a mast near the site of application. First step in the analysis is to remove effects of local terrain around the reference meteorological station and produce mean wind climate statistics for the resulting generalized winds, i.e. winds over flat uniform terrain. At the site of application, WAsP will model terrain effects near every wind turbine site and predict local mean wind climates based on speed-up factors and the generalized mean wind climate. Now, reanalysis data are predicted by global circulation models with simplified terrain models capturing only large-scale flow effects. To use them in a WAsP context we need to calculate the generalized wind climate by a method we call downscaling, see https://orbit.dtu.dk/en/publications/mesoscale-and-microscale-downscaling-for-the-wind-atlas-of-south-. We have not done so with the MERRA2 data as input, but the Global Wind Atlas made a downscaling with the WRF (mesoscale) and WAsP (microscale) flow models based on the ECWMF ERA5 2008-2017 reanalysis dataset, see https://globalwindatlas.info/about/method for a quick read. It is possible to download the GWA generalized wind climates from https://globalwindatlas.info/ and use them in WAsP for preliminary wind resource estimates when local data are unavailable. We still recommend local measurements for bankable results.

Hi Ines, The profile between lower and upper tip height is what matters for site assessment, so I would focus on heights in that range. It is also important to use a selection of data with simultaneous measurements from all the heights used for the profile. You may want to skip a height if it has lots of missing observations. As I remember, WindPro can plot the fitted profile and the reference points together. This is a good quality check and might help you deciding which heights to include. Best regards, Morten

Hi Ines, There are lots of internal processing in a lidar, which results in time series of horizontal speed and direction for different heights. Presumably, the data are also screened for measurement errors, which are reported by status codes. If lots of data are missing for some heights, e.g. at the top, you might want to disregard those heights. Basically, you can only measure the wind component along the laser beam, so a single lidar deduces the horizontal wind by several measurements along slanted beams with different azimuth angles. This deduction usually rely on an assumption of zero vertical wind velocity, so results for the lowest heights might be compromised in complex terrain. It is possible to corrects for effects of non-zero wind velocity by a flow model, as I think we mention this in the WAsP Engineering course. I have heard that some manufactures offers this correction as an optional service inside instrument. Basically it is a correction table, which can be calculated based on the orientation of the instrument and the terrain around the measurement position. Hope that this helps a little. We have a large group of lidar specialist here at DTU Wind Energy working on advanced techniques, like multiple coordinated lidars, dedicated scanning patterns and new data processing for turbulence measurements. I must confess that compared to them, I know very little on the topic. With best regards, Morten

Hi Inés, I just remembered one more reservation: WAsP applies the geostrophic drag law for conversions between actual and generalized winds. This law works well for wind climate statistics, but you often see deviations from the geostrophic balance when considering 10-min measurement periods and the site of prediction is not close to the reference site BR Morten

Hi Inés, We know that time series of power production has many applications, but we have not yet found a way to support this in WAsP. WAsP is basically designed to work with climate statistics and predict annual energy productions. One might use the flow corrections of WAsP to translate wind conditions for each record in a reference time series to individual turbine sites, and I think our partners at WindPro offers a module, which follow this approach. There are however some general concerns: WAsP operates with wind sector statistics, e.g. effects of roughness changes are modelled as average corrections for each wind sector. Real terrain might be more complicated. The background wind profile in WAsP includes the average effect of atmospheric stability, but not time-dependent variation of atmospheric stability. Wind conditions measured over 10-min periods at reference mast and site of prediction are not perfectly correlated for individual records in the time series. This de-correlation is expected to depend on the distance from the reference site, terrain, wind speed, turbulence, mesoscale convection, etc. Realistic time series simulation may have to include a stochastic element to model these effects. The standard WAsP wake model does not include effects of variable atmospheric stability conditions affecting the wake development. The model also ignores wake meandering causing fluctuation in the wake loss. These concerns may not be relevant for all applications, e.g. you might consider the above-mentioned effects as acceptable uncertainties. Best regards, Morten

Hi Erkan, Both of the attached WindPRO error messages say “project class failed to create a new project instance” which indicates a problem with the installation. I also see a button called “show bug report” and I guess that you will get detailed information when you press that. If that does not help you, I suggest that you contact WindPRO support. If I read your question correctly, you were able to calculate with WEng 4.0, but now are having problems going back to WEng 3.1. I don't know whether the two versions are supposed to co-exist under a WindPRO installation. If you were running our programs directly, I would recommend that you switched to WEng 4.0. Actually, we no longer support WEng 3.1 (latest version is from 2015) so I no longer have it on my PC. Best regards, Morten