WAsP 10 review

The latest version 10 of Risoe's wind-analysis software WAsP has been released for a few months now, and after working with it for a while I thought I'd post a few thoughts and comments on how it's working.

WAsP is a micro-scale wind modeling software package used to estimate wind speeds over a region based on measured wind speeds at discrete points (typically met masts). WAsP also forms the backbone for other wind packages such as Windfarmer and Windpro. The orographic-flow model used by WAsP is the 'BZ-model' of Troen (1990), which in simple terms places a high-resolution 2D polar grid over the measured wind source to estimate the flow perturbations over the region - so this isn't a CFD package. Importantly, the resolution and accuracy of the grid reduces the farther away from the initiation point. The flow model used to estimate the perturbation also assumes that there is no flow separation, and therefore the validity breaks down with more complex terrain.

One of the biggest changes in this release in my opinion is the new Google Earth integration, and it works very well (in the northern hemisphere at least - see below). In a few simple clicks, WAsP will send your live turbine layout and met mast locations into Google earth so you can visualise the turbines and masts, as well as your topographic and roughness assumptions, and any resource grid you run. It's a well implemented feature and actually models your turbine tower height and rotor diameter based on your .wtg model. Eye candy aside, this can really help in layout development as it allows you to have your land boundaries and other GIS data in Google Earth (as .shp files for example) and develop your layout around it. It also allows you to bring the satellite imagery back into WAsP as an overlay image.

Official demo site in Portugal - wind resource grid and turbines visible.

There are also some great user friendly changes in WAsP, such as the turbine diameter circles around your positions (this was my favourite), and the added reference locations (which allows you to check how the wind modeling is handling certain features of interest, such as other masts).

workspace view with orography, turbines, and spacing visible

Unfortunately a minor bug in WAsP still hasn't been fixed, and that is that it assumes all map projections are in the northern hemisphere. What this means is that for projects in the southern hemisphere, the WAsP map editor can't convert between datums and projections, and the Google earth integration doesn't work! The actual wind modeling isn't affected however, so it's more of a cosmetic issue that can be overcome with another GIS package. Risoe have told me they are working on a fix for this however.

Overall however I think this is an excellent and constantly evolving software package, and is well
worth the one-off EUR 3300 license fee. For users of Windfarmer and Windpro, I thoroughly recommend looking into your base flow model again!

note: I have no affiliation with Risoe/WAsP and have fully paid for my licensed copy! :)

LIDAR-based wind turbine control system

There's been a little bit of interest in laser based anemometry, or LIDAR, wind turbine control systems. It's been the precept of Risoe's Windscanner program below, and several Risoe-DTU papers at EWEC 2009. It even made this month's Economist technology quarterly. As rotors get bigger, I believe this concept will become more and more import - both for energy production optimisation, and for loads reduction on the blades and drive train.

So what is LIDAR? LIDAR is simply the use of a laser in the same way a RADAR is used, by measuring the time it takes for pulses to return after they have bounced off minute particulates carried in the air, a profile of the wind speed can be developed. If used in an array, a three-dimensional picture of the column of approaching wind can be more accurately estimated.

How does this help a wind turbine? At the moment, wind turbines estimate the wind speed based on a nacelle-based anemometer - typically ultrasonic, or a traditional cup anemometers. The wind speed measured here is used as the basis for the controller to estimate the wind speed over the entire rotor and set the appropriate pitch setting of the blades to optimise the angle of attack. Wind turbine blades operate most efficiently at only one angle of attack setting - too much, or too little reduces the aerodynamic efficiency and therefore the energy output.

The bigger rotors get, the less accurate it is to estimate the entire wind speed of the column of wind based on one single anemometer input. So, a LIDAR can help by providing a more accurate distribution of wind speeds of the incoming wind. Armed with this, the controller can then anticipate more accurately the pitch settings to use (possibly even individual blade pitch settings). In the case of an extreme gust, the blades could then feather and dramatically reduce the loads on the turbine, where as a traditional system will only know a gust after it's experienced it.

There are some definite practical engineering problems with integrating this system however. If you base it on the ground, how do you yaw it efficiently to align with the turbine? If you base it on the nacelle, you have to place it in the rotating hub and allow for the complications of rotating a delicate laser array continuously. Whether or not the increased cost and complication of this system will be balanced by the production increase and possible cost reduction in structure optimisation: only industry experience will tell.