VAWTs with HAWTs

Overview

The energy in the wind is the cube of the wind speed. The cube law means creating small increases in wind speed will result in significant increases in a wind turbine’s energy output.

This fundamental physical law of wind energy drives developers to invest in high wind resource sites and to place their turbines where they can harvest the highest velocity wind. It also drives the importance of researching how Vertical Axis Wind Turbines (VAWTs) can be positioned to increase the wind speeds realized by Horizontal Axis Wind Turbines (HAWTs).

A key difference between VAWTs and HAWTs is that HAWT blades send the vibrations caused by turbulence in the wind to the drive train, causing harmful wear and tear to the bearings and gearbox. Near-ground wind is turbulent, a fundamental reason HAWTs are installed high above the ground. This does, however, leave wind farms with good near-ground wind resources such as those with hills, ridgelines or mesas or those set in passes, with an untapped, valuable resource that no HAWT can harvest.

If VAWTs can be installed below and around HAWTs without causing any harmful wake or turbulence to HAWT blades, then the understories of wind farms can be developed. If VAWTs also are able to increase the wind speeds that reach the HAWT rotors above them, the economics and incentives to build out these unharvested resources improve.

Capacity Factor Enhancement

A 1 MW project operating at full power all 8760 hours in a year it would produce 8760 MWhs of energy and achieve a 100% Capacity Factor (CF).   Most wind farms operate with a CF of 25-35% and produce only 2200-3000 MWhs annually per installed MW.

Including VAWTs among the HAWTs without triggering the need for additional substation capacity is called Capacity Factor Enhancement (CFE).  The number of VAWTs that could profitably be installed in such a project depends on:

  • The wind speeds at the site and the power performance curves of the HAWTs and VAWTS.
  • The wear and tear on the HAWTs and the economic benefits of resting them during high wind events.
  • The Power Purchase Agreement for the energy produced including time of day production bonuses.
  • The estimated annual VAWT production that would be lost during high wind speed events.
  • The VAWT project savings that come from not having to invest in new land, roads, and infrastructure.

Research and pilot studies will be important to accurately size CFE projects and increase the Capacity Factors of existing wind farms with new VAWTs.   WHI is writing a Research and Development proposal in response to the CEC EPIC Program’s grant opportunity GFO-16-310 - Improving Performance and Cost Effectiveness of Wind Energy Technologies.  The working title is “Researching and developing the potential of VAWTs to double capacities of California’s wind farms while preventing harm to birds – Phase I”.  This would be a foundational study upon which the more site-specific research on CFE projects can be built.

We are interested hearing from wind farm owners and others interested in how VAWTs could be used in CFE projects.    Let us know your thoughts at comments@windharvest.com.

Porous Wind Fence Effect

Wind fences (aka windrows or windbreaks) “slow the wind in one place by deflecting it to another”[1] and thus reduce the wind speed downwind. Generations of land owners have used windbreaks and wind fences to protect their crops and prevent erosion, but it is only recently that science has been brought to bear on the details of the wind flow patterns they create.

Different porosities of a windbreak will affect the wind speed over its top and downwind. Figure 1 shows how the wind speed increases over the top of a porous wind fence but slows directly behind and downwind of it. Note that the highest speed-up zone is above and slightly downwind of the “fence.” A row of VAWTs is similar to a row of trees, except the porosity of the VAWTs is significantly higher[2] With a highly porous “fence” of VAWTs, Dr. Marius Paraschiviou predicts that the speed-up effect will occur above a 2-4m zone of high turbulence located immediately above the rotating blade tips.[3]

Figure 1.  Note the zone of increased wind speed above and slightly downwind of the “fence”. [4]

Though Dr. Paraschiviou predicts a speed-up effect above the row of VAWTs, its location and how far it will extend requires field data to validate and model. WHI proposes to use Lidar, calibrated in the field with sonic anemometers, to collect high quality wind-speed data above the row of VAWTs and every 15 meters downwind.

This field research will provide the data needed to validate CFD models that then can predict how VAWT arrays of differing solidity and in different configurations could be optimized to create increases in the wind speeds that reach HAWT blades and thus increase their energy output.

The fact that a “fence” of VAWTs increases the wind speed over their tops creates another opportunity of benefit to HAWTs. In a wind site where the main wind directions are 180° opposite from each other, the VAWTs can be placed under the HAWT rotor, and when the wind direction changes and the HAWTs yaw around into the wind, the VAWT row will be downwind of the HAWT rotor instead of directly beneath. The wind speed will still increase over the VAWTs but won’t reach the now-upwind HAWT blades. The increase in wind speed will, however, lower the pressure behind the HAWT rotor. Higher wind speed creates lower air pressure directly behind the HAWT rotor, increasing the pressure difference between upwind and downwind zones, which, in turn will cause the wind to move faster through the HAWT rotor.

Research is needed to determine how best to install VAWTs around HAWTs on a site where the wind resource is not uni-or bi-directional but comes from multiple directions . Curved, V-shaped or other configurations of VAWT arrays may work better in these situations. Field data will be required to validate computer modeling that can predict the VAWT wake and turbulence effects for each of the different types of terrains and meteorological conditions that occur on  wind farms.

Figure 7 (from Patent)  A “porous wind fence” of VAWTs directly under a HAWT rotor. The solidity of the row of VAWTs will determine where the speed-up effect reaches its maximum, both above and downwind. The VAWTs can be placed on towers to ensure they are high enough to maximize the benefits to the HAWTs without creating turbulence that could damage their blades and drive train.

Vertical Mixing

All objects in the landscape, including VAWTs, create obstacles that block the wind, forcing it to change direction and speed up around them. When VAWT rotors are in motion, they create three types of downwind wake and turbulence:  blade-shed vortices, blade tip-shed vortices, and shear-layer turbulence. This complex flow holds can increase the wind speeds realized by HAWTs and allow the next row of VAWTs to be placed much closer downwind of another row of VAWTs.

Over his years of working on wind farms Bob Thomas observed the vertical mixing that HAWTs were creating in the San Gorgonio Pass and hypothesized that the addition of VAWTs in the “bush-tree” formation would  increase that mixing and bring faster moving wind nearer to HAWT rotors.

Arrays of closely spaced VAWTs enhance vertical mixing mainly due to the vortices of swirling wind produced by their blades as well as by the shear-layer turbulence induced by the closely spaced VAWTs in array. The large, vertically oriented vortices that spin off at the back of the rotating blades produce a low-pressure zone at their center that sucks in higher pressure air from above or below. This, along with the shear-layer turbulence, creates vertical mixing of the layers of slower- and faster-moving wind at different altitudes.

Though the basic physics of vertical mixing are relatively well understood, research will be needed to confirm that it  won’t cause harmful turbulence to reach the HAWT blades and damage their bearings and drive trains.  This can be done using Lidar and sonic anemometers to validate CFD modeling. For more information on WHI's research proposal, see Phase I research below.

 

All objects in the landscape, including VAWTs, create obstacles that block the wind, forcing it to change direction and speed up around them. When VAWT rotors are in motion, they create three types of downwind wake and turbulence:  blade-shed vortices, blade tip-shed vortices, and shear-layer turbulence. This complex flow holds can increase the wind speeds realized by HAWTs and allow the next row of VAWTs to be placed much closer downwind of another row of VAWTs.

Over his years of working on wind farms Bob Thomas observed the vertical mixing that HAWTs were creating in the San Gorgonio Pass and hypothesized that the addition of VAWTs in the “bush-tree” formation would  increase that mixing and bring faster moving wind nearer to HAWT rotors.

Arrays of closely spaced VAWTs enhance vertical mixing mainly due to the vortices of swirling wind produced by their blades as well as by the shear-layer turbulence induced by the closely spaced VAWTs in array. The large, vertically oriented vortices that spin off at the back of the rotating blades produce a low-pressure zone at their center that sucks in higher pressure air from above or below. This, along with the shear-layer turbulence, creates vertical mixing of the layers of slower- and faster-moving wind at different altitudes.

Though the basic physics of vertical mixing are relatively well understood, research will be needed to confirm that it  won’t cause harmful turbulence to reach the HAWT blades and damage their bearings and drive trains.  This can be done using Lidar and sonic anemometers to validate CFD modeling. For more information on WHI's research proposal, see Phase I research below.

 

Phase 1 Research

Researching and developing the potential of VAWTs to double the capacities of California’s wind farms while preventing harm to birds
A research and development proposal for presentation to the California Energy Commission EPIC Program.  Last updated:  18 May 2017

Wind Harvest International (WHI) is seeking grant funding to conduct research on the effects of integrating Vertical Axis Wind Turbines (VAWTs) into existing and new wind farms that are now composed solely of Horizontal Axis Wind Turbines (HAWTs).

Before VAWT developments will be allowed, verification is needed to help ensure that the new, vertically spinning turbines do not create wake and turbulence that damages the HAWTs above and downwind of them. If these wind farms include habitat of rare and endangered birds, then third-party collected data will be needed to demonstrate either that the VAWTs won’t harm these species or that they can be operated safely when these birds and bats are in their vicinity.

In April 2017, the CEC’s EPIC Program released a grant opportunity entitled “Improving Performance and Cost Effectiveness of Wind Energy Technologies.”  In response, WHI is presenting its application entitled “Researching and developing VAWTs potential to double the capacities of California’s wind farms while  preventing harm to birds.”  This R&D project will make innovative use of Doppler Lidar, sonic anemometers and computational fluid dynamics (CFD) to map out and model the wake and turbulence that result from closely spaced pairs of WHI’s G168 VAWTs.

At the same time, the grant will fund the evaluation of bird detection and recording technologies that can rapidly and inexpensively increase the data on what happens when birds come into the vicinity of VAWTs. This first round of basic research can lead to later testing of how well avoidance technology prevents those birds and bats that are unable to detect the VAWTs from coming into harm’s way.

Schematic of Lidar vertical scanning geometry for near wake measurements. Not drawn to scale.

The proposed project will be conducted in two parts. Using CEC EPIC program funding,WHI's VAWTs currently undergoing certification at UL's Advanced Wind Turbine Testing Facility on the plains of the Texas Panhandle will produce baseline data in this flat land with excellent "laboratory conditions" winds. That data will help calibrate the CFD modeling that will be done by a team from Stanford University. This, along with the Lidar and anemometer analysis, will help map and analyze key attributes of VAWT-induced wake and turbulence. It would also become the data upon which modeling of more complex terrains and conditions can be evaluated.

The second part of the project will take place near one of  California's Wind Resource Areas, with priority being given to the Solano WRA. Here, the marine layer off San Francisco races up the Sacramento River to the low-pressure zone created by massive amounts of air rising in the heat of the Central Valley. Similar to that of the Texas site, the wind in the Solano WRA has a low turbulence but adds the variable of hilly terrain.

Together, the two parts of the project will produce:

  1.  Datasets and analysis, including CFD modeling, on wind movements around, over and downwind of counter-rotating pairs of 70 kW-sized VAWTs in both "laboratory conditions" and in hilly terrain.
  2. Modeling and analysis to help assure HAWT owners that a VAWT array can be safely placed a distance upwind (to be determined by Phase I research) or a short distance downwind of their turbines. A Phase II project could then take place among the HAWTS in the 1000 MW Solano WRA to begin analyzing HAWT-VAWT wake interactions.
  3. Data on the "porous wind fence" speed-up effect that will help model at what height above a VAWT array the effect lasts and where it is the strongest.
  4. Data and analysis on how birds interact with VAWTs and whether the DTBird motion detection and recording technology can be relied upon to accurately record whether the turbines harm wildlife..

Project Team
WHI is pleased to have recruited an excellent team of scientists to collaborate on this proposal.

Dr. Craig Clements, San Jose State University, Lidar

Joe Drennan and Eric Jepsen, Garcia and Associates, Bird research

Adam Holman, UL and West Texas A&M University

Neil Kelley, NREL retired, Senior Investigator

Dr. Scott Larwood, University of the Pacific, Sonic Anemometers

Dr. Sanjiva Lele, Stanford University, CFD Modeling

Kevin Wolf, Chief Operating Officer, WHI, and Project Manager

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