Difference between revisions of "Notes - Wind Turbine ISR-G"

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These are notes for my wind turbine independent study with Jeff Dusek.
 
These are notes for my wind turbine independent study with Jeff Dusek.
  
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## 10/01/2020
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__Moving forward, I will:__
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- I will look into saving data on SD-card with an Arduino. I will also try to set up Arduino MATLAB.
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- Mount new anemometers, and figure out how to read their outputs.
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- CAD solar panel mount. (I just couldn't find the time to do that last week.)
 +
- clear out the area for solar panel mounts and start locating post holes
 +
- Reassess locations for turbines. I have been trying to find spots, but I will approach this question more professionally.
  
  

Revision as of 16:16, 1 October 2020

These are notes for my wind turbine independent study with Jeff Dusek.

10/01/2020

Moving forward, I will:

  • I will look into saving data on SD-card with an Arduino. I will also try to set up Arduino MATLAB.
  • Mount new anemometers, and figure out how to read their outputs.
  • CAD solar panel mount. (I just couldn't find the time to do that last week.)
  • clear out the area for solar panel mounts and start locating post holes
  • Reassess locations for turbines. I have been trying to find spots, but I will approach this question more professionally.

9/24/2020

Wind Energy Extraction

Rotating lift-based machines

Horizontal axis wind turbine, Darrieus turbine, vertical axis wind turbine with blades,

Rotating drag-based machines

Vertical axis turbines - similar to cup anemometer; Savonius (efficiency 10%-15%) could be nice for aesthetically pleasing turbine

Flying lift-based machines

pulls up sail that pulls on a cord that spins spindel

Machines using flow-induced vibrations

Financing

Our revenue is the production of net electricity in Wh (Annual Energy Production): Capacity of Farm x 8760h x capacity factor 0.25

1 - Simple payback time (SPT)

Simplistic Calculation

  • estimate of annual production in Wh
  • annual revenue - production x energy sale price
  • annual operating costs

2 - Net present value (NPV)

(revenue - costs) - original investment
if less than 0, probably not profitable

excel has NPV function

3 - Levelised cost of Energy (LCoE)

goal is to find cost per MWh that can be used for comparison:
(Capital Investment + Operational Costs + Decommissioning Cost)/ MWh

Wind Drag on Solar Panel Plate

drag force on five solar panels at varying angles approximated

Individual solar panels have an aspect ratio of 1:2 (62.2 x 31.8 x 1.4 inches). The current plan for the five panels is to mount them side by side resulting in an aspect ratio of 1:2.56 (62.2 x 159 x 1.4 inches).

F = 1/2 * p * v^2 * A * 2pi * sin(alpha); (p - density of air, v - wind speed, 2pi sin(a) - drag coefficient); density of 10 celsius air - 1.246 kg/m^3;
solar panel dimension - 62.2 x 31.8 x 1.4 inches - 1.58m x 0.8m x 0.0355; area = 1.264 m^2
Lift on all five panels: F = 0.5 * 1.246 kg/m^3 * (17.8 m/s)^2 * 1.264 m^2 * 5 * 2pi * sin(a) <= 7835 N

Sources

Remote Wind Speed Sensing

  • two challanges: low noise to signal ratio, need to measure volume not single point
  • LIDAR & SODAR Doppler shift measuring; LIDAR measurements are more precise

Statistical Analysis of Wind Speeds and Turbulence

  • Navier-Stokes equation (evolution equation) to calculate wind speeds in space
  • statistical analysis, spectra, turbulence intensity is obtained by mean wind speed and standard deviation of wind speeds
  • every wavelength (after Fourier transform) can be thought of as a length scale
  • wind vector (u, v, w)
  • integral length scale; from time series, we compute the auto-correlation function
  • turbulence spectra
  • averaging periods of 10 min are commonly used; 30 min period for turbulence studies; the larger integral time scale, the larger should be averaging period; sampling frequencies should be much smaller than integral time scale
  • you have to detrend te time series to get rid of high-frequency fluctuation

Sources:

Flat Plate Approximation - Caltech

Turbulence Spectra and Scales

Transition to turbulence begins when some flow instability (such as the instability analyzed in sections (Bkc) and (Bkd)) leads to some fairly large scale disturbance(s) or “eddies” in the flow field. As these disturbances gather energy from the mean flow, they begin to spawn smaller disturbances or eddies which, in turn spawn even smaller eddies. This process ends because, eventually, the eddies reach a size for which viscous effects become important and the very small eddies are damped out by viscosity. Eventually, the spectrum of spatial or temporal eddy sizes reaches a “fully developed” state in which energy is fed from the mean flow into large eddies and then continually cascades down to smaller and then smaller eddies eventually reaching a size at which viscosity becomes important and damps out those small eddies. In this fully-developed state the disturbance energy for any one size of eddy becomes relatively constant though it can, of course, continue to change with the flow conditions.

Next Steps

  • write up questions about auto-correlation function
  • include lift coefficient in flat plate lift equation
  • reading on the efficiency of vertical turbines vs conventional turbines
  • interview farmer Ann again
  • ask Ayden to mount anemometer
  • CAD solar panel construction, include Jasmine

9/17/2020 - Wind Profiles

What I did:

  • I measured wind speeds throughout the week. At a height of 4 m, the wind speeds vary around 0-4 mph. We had gust of up to 10-15 mph. However, wind speeds seem to be quite low. From talking to a nearby farmer I learned that wind speeds increase during the months November - January.
  • I completed the first two weeks on Coursera, but I didn't take the quizzes due to limited time
  • We have been working on a mount for the five solar panels. We will most likely build a solar-sail that rotates around its middle axis. Its angle of rotation can be manually adjusted for winter and summer times. We will have to dig at least four post holes to keep the construction sturdy during heavy storms.
  • the surface roughness is important for wind energy estimations
  • surface roughness is hard to determine

To Do:

  • orientation of the turbine
  • mount anemometer higher up in the trees
  • look into turbine tree mounting techniques
  • finish week three and take week 2 quizzes
  • work when it doesn't rain
  • what's the surface roughness here at the farm?
  • find possible turbine spots
  • research boundary layers and atmospheric stability correction
  • look into calculating the lift of solar panels (flat plate approximation - coefficient for lift and drag)

9/12/2020 - I began Coursera Course

  • we have a hight surface roughness probably around z_0=0.4 (wind profiles)
  • Eddies are swirls of a fluid and it's reverse current in a turbulent flow regime (Wikipedia)

Wind Resource Assessment

  • due to roughness of the forest, wind speed increases
  • The Wind Atlas Analysis And Application Program (WAsP) provides an upward and downard analysis of the terrain
  • on top of hills, we have over speeding due to continuity
  • What is Weibull distribution?

9/10/2020 - First Semester Call with Jeff

site assessment - take photography and topography

data collection with raspi anemometer

hard part: is there enough detail in the Coursera course?

deliverables: structural design of design the tower, beam bending, blade design --> lifting line theory

model for the amount of power --> modeling in Simulink --> amount of wind, size of turbine...

Grade? --> a few deliverables: weekly journal entry/blog, Coursera quizzes (weekly entry), site assessment, modeling,

Get started: Coursera, as you work trough (document built-in quizzes) Do Simulink onramp

To-do for next week:

  • Write up ISR-G application
  • First week or two of Coursera course, wind resources, tests, and measurement part
  • Personal notes in a google doc, final Report - technical report in latex, final deliverable that is more public-facing