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National Renewable Energy Laboratory's (NREL's) Wind AnalysisLibrary: NRWAL

Project description

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The National Renewable Energy Laboratory Wind Analysis Library (NRWAL):

  1. A library of offshore wind cost equations (plus new energy technologies like marine hydro!)

  2. Easy equation manipulation without editing source code

  3. Full continental-scale integration with the NREL Renewable Energy Potential Model (reV)

  4. Ready-to-use configs for basic users

  5. Dynamic python tools for intuitive equation handling

  6. One seriously badass sea unicorn

To get started with NRWAL, check out the NRWAL Config documentation or the NRWAL example notebook. You can also launch the notebook in an interactive jupyter shell right in your browser without any downloads or software using binder.

Ready to build a model with NRWAL but don’t want to contribute to the library? No problem! Check out the example getting started project here.

Here is the important stuff:

Installing NRWAL

NRWAL Variables for Offshore Wind (OSW)

NRWAL Inputs

Variable Name

Long Name

Source

Units

aeff

Array Efficiency

array_efficiency input layer, computed from ORBIT

%

capex_multi

CAPEX Multiplier

Supplied by user

unit-less

depth

Water depth (positive values)

bathymetry input layer

m

dist_a_to_s

Distance from assembly area to site

Computed from assembly_area input layer

km

dist_op_to_s

Distance from operating port to site

ports_operations input layer

km

dist_p_to_a

Distance from port (construction no-limit) to assembly area

assembly_area input layer

km

dist_p_to_s

Distance from construction port to site

ports_construction input layer

km

dist_p_to_s_nolimit

Distance from no-limit construction port to site

ports_construction_nolimit input layer

km

dist_s_to_l

Distance site to nearest land

dist_to_coast input layer

km

fixed_downtime

Average weather downtime for fixed structure turbines

weather_downtime_fixed_bottom input layer

fraction

floating_downtime

Average weather downtime for floating structure turbines

weather_downtime_floating input layer

fraction

gcf

Gross capacity factor

Computed by reV / SAM with losses == 0

unit-less

hs_average

Significant wave height to determine weather downtime

weather_downtime_mean_wave_height_buoy input layer

m

num_turbines

Number of turbines in array

Supplied by user

unit-less

transmission_multi

Tranmission cost multiplier

Supplied by user

unit-less

turbine_capacity

Capacity of each turbine in the array

Supplied by user

MW

Project details


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