Using a pre-arranged simulation workflow¶

• Pre-arranged workflows are available which apply the steps above (and maybe more) automatically
• These workflow functions can automatically simulate turbines of different design in a single function call
• These workflows can also be instructed to distribute themselves across multiple CPUs

Workflow:

1. Import required packages
2. Import csv with turbine placements
3. Simulate turbines
4. Plot different turbines

In [1]:

import reskit as rk
import pandas as pd

import reskit as rk import pandas as pd

In [2]:

# Placement locations do not have to be put in as a pandas dataframe (a list of coordinates would also be okay), but
#  it is also the most flexible. Therefore, this manner is suggested

placements = pd.read_csv(rk.TEST_DATA["turbine_placements.csv"])

placements.head()

# Placement locations do not have to be put in as a pandas dataframe (a list of coordinates would also be okay), but # it is also the most flexible. Therefore, this manner is suggested placements = pd.read_csv(rk.TEST_DATA["turbine_placements.csv"]) placements.head()

Out[2]:

	capacity	hub_height	rotor_diam	lon	lat
0	4000	120	150	5.985195	50.797254
1	4000	120	130	5.994685	50.794208
2	4000	120	150	5.994107	50.800939
3	4000	120	130	6.004750	50.784432
4	4000	120	150	6.004174	50.791162

In [3]:

gen = rk.wind.onshore_wind_merra_ryberg2019_europe(
    placements=placements,
    merra_path=rk.TEST_DATA["merra-like"],  # path to MERRA2 data on your hard drive
    clc2012_path=rk.TEST_DATA[
        "clc-aachen_clipped.tif"
    ],  # Path to corine land cover (or anther land cover dataset) on your hard drive
    gwa_50m_path=rk.TEST_DATA[
        "gwa50-like.tif"
    ],  # Path to global wind atlas (at 50m, to match MERRA) on your hard drive
)

gen = rk.wind.onshore_wind_merra_ryberg2019_europe( placements=placements, merra_path=rk.TEST_DATA["merra-like"], # path to MERRA2 data on your hard drive clc2012_path=rk.TEST_DATA[ "clc-aachen_clipped.tif" ], # Path to corine land cover (or anther land cover dataset) on your hard drive gwa_50m_path=rk.TEST_DATA[ "gwa50-like.tif" ], # Path to global wind atlas (at 50m, to match MERRA) on your hard drive )

DeprecationWarning: /home/docs/checkouts/readthedocs.org/user_builds/ethos-reskit/checkouts/latest/reskit/workflow_manager.py:413
'nan' value for 'nodata_fallback' is deprecated and will be removed soon. Use np.nan instead.

2026-07-28 10:30:49.159763 Based on max_batch_size=560, the total of 560 placements were split into 1 sub batches. Proceeding with batch 1/1 (id=0) with 560 placements.
2026-07-28 10:30:49.164403 Required tolerance of 0.01 reached after 0 additional iteration(s). Maximum remaining rel. deviation: 0.0.

RuntimeWarning: /home/docs/checkouts/readthedocs.org/user_builds/ethos-reskit/checkouts/latest/reskit/wind/workflows/wind_workflow_manager.py:770
divide by zero encountered in divide

In [4]:

gen

gen

Out[4]:

<xarray.Dataset> Size: 1MB
Dimensions:                         (location: 560, time: 71)
Coordinates:
  * location                        (location) int64 4kB 0 1 2 3 ... 557 558 559
  * time                            (time) datetime64[us] 568B 2015-01-01T00:...
Data variables:
    capacity                        (location) int64 4kB 4000 4000 ... 4000 4000
    hub_height                      (location) int64 4kB 120 120 120 ... 120 120
    rotor_diam                      (location) int64 4kB 150 130 150 ... 150 130
    lon                             (location) float64 4kB 5.985 5.995 ... 6.332
    lat                             (location) float64 4kB 50.8 50.79 ... 50.84
    powerCurve                      (location) object 4kB 'SPC:226,25' ... 'S...
    LRA_factor_elevated_wind_speed  (location) float64 4kB 0.7478 ... 0.7794
    roughness                       (location) float64 4kB 0.05 0.05 ... 0.05
    elevated_wind_speed             (time, location) float64 318kB 4.905 ... ...
    surface_pressure                (time, location) float64 318kB 1.012e+05 ...
    surface_air_temperature         (time, location) float64 318kB -1.014 ......
    capacity_factor                 (time, location) float64 318kB 0.07048 .....

xarray.Dataset

• Dimensions:
  • location: 560
  • time: 71
• Coordinates: (2)
  • location
    (location)
    int64
    0 1 2 3 4 5 ... 555 556 557 558 559

    array([  0,   1,   2, ..., 557, 558, 559])

  • time
    (time)
    datetime64[us]
    2015-01-01T00:30:00 ... 2015-01-...

    array(['2015-01-01T00:30:00.000000', '2015-01-01T01:30:00.000000',
           '2015-01-01T02:30:00.000000', '2015-01-01T03:30:00.000000',
           '2015-01-01T04:30:00.000000', '2015-01-01T05:30:00.000000',
           '2015-01-01T06:30:00.000000', '2015-01-01T07:30:00.000000',
           '2015-01-01T08:30:00.000000', '2015-01-01T09:30:00.000000',
           '2015-01-01T10:30:00.000000', '2015-01-01T11:30:00.000000',
           '2015-01-01T12:30:00.000000', '2015-01-01T13:30:00.000000',
           '2015-01-01T14:30:00.000000', '2015-01-01T15:30:00.000000',
           '2015-01-01T16:30:00.000000', '2015-01-01T17:30:00.000000',
           '2015-01-01T18:30:00.000000', '2015-01-01T19:30:00.000000',
           '2015-01-01T20:30:00.000000', '2015-01-01T21:30:00.000000',
           '2015-01-01T22:30:00.000000', '2015-01-01T23:30:00.000000',
           '2015-01-02T00:30:00.000000', '2015-01-02T01:30:00.000000',
           '2015-01-02T02:30:00.000000', '2015-01-02T03:30:00.000000',
           '2015-01-02T04:30:00.000000', '2015-01-02T05:30:00.000000',
           '2015-01-02T06:30:00.000000', '2015-01-02T07:30:00.000000',
           '2015-01-02T08:30:00.000000', '2015-01-02T09:30:00.000000',
           '2015-01-02T10:30:00.000000', '2015-01-02T11:30:00.000000',
           '2015-01-02T12:30:00.000000', '2015-01-02T13:30:00.000000',
           '2015-01-02T14:30:00.000000', '2015-01-02T15:30:00.000000',
           '2015-01-02T16:30:00.000000', '2015-01-02T17:30:00.000000',
           '2015-01-02T18:30:00.000000', '2015-01-02T19:30:00.000000',
           '2015-01-02T20:30:00.000000', '2015-01-02T21:30:00.000000',
           '2015-01-02T22:30:00.000000', '2015-01-02T23:30:00.000000',
           '2015-01-03T00:30:00.000000', '2015-01-03T01:30:00.000000',
           '2015-01-03T02:30:00.000000', '2015-01-03T03:30:00.000000',
           '2015-01-03T04:30:00.000000', '2015-01-03T05:30:00.000000',
           '2015-01-03T06:30:00.000000', '2015-01-03T07:30:00.000000',
           '2015-01-03T08:30:00.000000', '2015-01-03T09:30:00.000000',
           '2015-01-03T10:30:00.000000', '2015-01-03T11:30:00.000000',
           '2015-01-03T12:30:00.000000', '2015-01-03T13:30:00.000000',
           '2015-01-03T14:30:00.000000', '2015-01-03T15:30:00.000000',
           '2015-01-03T16:30:00.000000', '2015-01-03T17:30:00.000000',
           '2015-01-03T18:30:00.000000', '2015-01-03T19:30:00.000000',
           '2015-01-03T20:30:00.000000', '2015-01-03T21:30:00.000000',
           '2015-01-03T22:30:00.000000'], dtype='datetime64[us]')

• Data variables: (12)
  • capacity
    (location)
    int64
    4000 4000 4000 ... 4000 4000 4000

    array([4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
    ...
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000,
           4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000, 4000])

  • hub_height
    (location)
    int64
    120 120 120 120 ... 120 120 120 120

    array([120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
    ...
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120, 120,
           120])

  • rotor_diam
    (location)
    int64
    150 130 150 130 ... 150 130 150 130

    array([150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150,
           130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130,
           150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150,
           130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130,
           150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150,
           130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130,
           150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150,
           130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130,
           150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150,
           130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130,
           150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150,
           130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130,
           150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150,
           130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130,
           150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150,
           130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130,
           150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150,
           130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130,
           150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150,
           130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130,
    ...
           150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150,
           130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130,
           150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150,
           130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130,
           150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150,
           130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130,
           150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150,
           130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130,
           150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150,
           130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130,
           150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150,
           130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130,
           150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150,
           130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130,
           150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150,
           130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130,
           150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150,
           130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130,
           150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150, 130, 150,
           130])

  • lon
    (location)
    float64
    5.985 5.995 5.994 ... 6.333 6.332

    array([5.98519518, 5.99468503, 5.99410694, 6.00475009, 6.00417363,
           6.00359696, 6.01308572, 6.01251026, 6.02199919, 6.02142496,
           6.01912596, 6.01855069, 6.03377605, 6.03320406, 6.03148686,
           6.03091405, 6.03034103, 6.02976781, 6.02919439, 6.02862075,
           6.02804691, 6.02747287, 6.04325678, 6.04268621, 6.04211543,
           6.04154446, 6.04097327, 6.04040189, 6.03983029, 6.0392585 ,
           6.0386865 , 6.03811429, 6.03754188, 6.03696926, 6.03639644,
           6.05273624, 6.05216709, 6.05159774, 6.05102819, 6.05045843,
           6.04988846, 6.0493183 , 6.04874792, 6.04817735, 6.04760657,
           6.04703558, 6.04646439, 6.04589299, 6.04532139, 6.06221445,
           6.06164672, 6.06107879, 6.06051066, 6.05994232, 6.05937378,
           6.05880504, 6.05823609, 6.05766694, 6.05709758, 6.05652802,
           6.05595826, 6.07169141, 6.0711251 , 6.07055859, 6.06999188,
           6.06942496, 6.067723  , 6.06715527, 6.06658734, 6.0660192 ,
           6.06545086, 6.06488232, 6.0811671 , 6.08060222, 6.08003713,
           6.07947184, 6.07720865, 6.07664234, 6.07607583, 6.07550912,
           6.07494221, 6.07437509, 6.07380777, 6.07324025, 6.09064154,
           6.09007808, 6.08951441, 6.08895054, 6.08838647, 6.08669304,
           6.08612815, 6.08556307, 6.08499778, 6.08443229, 6.0838666 ,
           6.08330071, 6.0816018 , 6.0810351 , 6.07876623, 6.0781985 ,
    ...
           6.26011915, 6.24719427, 6.24557085, 6.24502932, 6.24123318,
           6.24069009, 6.24014682, 6.23960334, 6.23905967, 6.23851581,
           6.23797175, 6.2743542 , 6.27382099, 6.27115209, 6.25449813,
           6.25179467, 6.25125339, 6.25071192, 6.25017026, 6.24962841,
           6.24908635, 6.24854411, 6.24800167, 6.24745903, 6.28323786,
           6.28270585, 6.27684131, 6.27523789, 6.26072946, 6.26018941,
           6.25964917, 6.25910873, 6.2585681 , 6.25694505, 6.28520779,
           6.27396924, 6.27343197, 6.2728945 , 6.27020425, 6.26966563,
           6.26912681, 6.26858779, 6.26804858, 6.28289699, 6.28236094,
           6.28182469, 6.28128826, 6.28075163, 6.2802148 , 6.27967779,
           6.27914058, 6.27860318, 6.27806559, 6.2775278 , 6.30460478,
           6.29129129, 6.29075627, 6.29022106, 6.28968566, 6.28915006,
           6.28861427, 6.28807829, 6.28754212, 6.28700575, 6.28646919,
           6.28378352, 6.30022303, 6.29968923, 6.29915524, 6.29862107,
           6.2980867 , 6.29755214, 6.29701738, 6.29648244, 6.2959473 ,
           6.29541197, 6.29487645, 6.29434074, 6.29326874, 6.29273245,
           6.29219596, 6.30915614, 6.30702472, 6.30649138, 6.30595786,
           6.30542414, 6.30489024, 6.30435614, 6.30382185, 6.30328736,
           6.31489972, 6.31436723, 6.31383455, 6.31330168, 6.32384296,
           6.3233117 , 6.32278026, 6.33331743, 6.33278759, 6.33225756])

  • lat
    (location)
    float64
    50.8 50.79 50.8 ... 50.84 50.84

    array([50.79725388, 50.79420842, 50.8009389 , 50.7844316 , 50.79116216,
           50.79789271, 50.79484573, 50.80157632, 50.79852861, 50.80525925,
           50.83218166, 50.83891222, 50.76855716, 50.77528792, 50.79548011,
           50.80221081, 50.80894149, 50.81567216, 50.82240282, 50.82913346,
           50.83586408, 50.84259469, 50.76550763, 50.77223845, 50.77896926,
           50.78570005, 50.79243082, 50.79916158, 50.80589232, 50.81262305,
           50.81935377, 50.82608447, 50.83281515, 50.83954582, 50.84627648,
           50.76245731, 50.76918819, 50.77591906, 50.78264991, 50.78938074,
           50.79611156, 50.80284236, 50.80957315, 50.81630393, 50.82303469,
           50.82976543, 50.83649616, 50.84322688, 50.84995758, 50.75940621,
           50.76613715, 50.77286807, 50.77959898, 50.78632987, 50.79306075,
           50.79979162, 50.80652246, 50.8132533 , 50.81998412, 50.82671492,
           50.83344571, 50.75635431, 50.76308531, 50.76981629, 50.77654726,
           50.78327822, 50.80347099, 50.81020188, 50.81693276, 50.82366362,
           50.83039447, 50.8371253 , 50.75330163, 50.76003269, 50.76676373,
           50.77349476, 50.80041872, 50.80714967, 50.81388061, 50.82061153,
           50.82734244, 50.83407334, 50.84080421, 50.84753508, 50.75024816,
           50.75697928, 50.76371038, 50.77044147, 50.77717254, 50.79736567,
           50.80409668, 50.81082767, 50.81755866, 50.82428962, 50.83102058,
           50.83775151, 50.85794424, 50.86467512, 50.89159848, 50.89832929,
    ...
           50.59050312, 50.75207524, 50.77227115, 50.77900309, 50.82612626,
           50.83285808, 50.83958989, 50.84632169, 50.85305346, 50.85978523,
           50.86651698, 50.52684228, 50.53357482, 50.5672373 , 50.77593616,
           50.80959592, 50.81632783, 50.82305972, 50.8297916 , 50.83652347,
           50.84325532, 50.84998716, 50.85671898, 50.86345078, 50.53050506,
           50.53723765, 50.61129504, 50.63149219, 50.81326045, 50.8199924 ,
           50.82672434, 50.83345626, 50.84018817, 50.8603838 , 50.62169007,
           50.76306782, 50.76979993, 50.77653202, 50.81019228, 50.81692429,
           50.82365628, 50.83038826, 50.83712023, 50.76673064, 50.77346279,
           50.78019493, 50.78692705, 50.79365916, 50.80039125, 50.80712333,
           50.81385539, 50.82058744, 50.82731948, 50.8340515 , 50.60881567,
           50.77712496, 50.78385714, 50.79058931, 50.79732146, 50.80405359,
           50.81078571, 50.81751782, 50.82424991, 50.83098199, 50.83771405,
           50.87137414, 50.78078645, 50.78751867, 50.79425087, 50.80098306,
           50.80771524, 50.8144474 , 50.82117955, 50.82791169, 50.8346438 ,
           50.84137591, 50.848108  , 50.85484007, 50.86830418, 50.87503622,
           50.88176823, 50.78444724, 50.81137621, 50.81810841, 50.8248406 ,
           50.83157277, 50.83830493, 50.84503708, 50.85176921, 50.85850133,
           50.82850096, 50.83523317, 50.84196538, 50.84869756, 50.83216063,
           50.83889289, 50.84562513, 50.82908729, 50.83581961, 50.84255191])

  • powerCurve
    (location)
    object
    'SPC:226,25' ... 'SPC:301,25'

    array(['SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
    ...
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25',
           'SPC:226,25', 'SPC:301,25', 'SPC:226,25', 'SPC:301,25'],
          dtype=object)

  • LRA_factor_elevated_wind_speed
    (location)
    float64
    0.7478 0.7915 ... 0.7613 0.7794

    array([0.74781932, 0.79154657, 0.79422453, 0.70865284, 0.76535585,
           0.8072314 , 0.81875228, 0.80818209, 0.81538499, 0.80886646,
           0.78538709, 0.78708948, 0.69231337, 0.69395296, 0.81471898,
           0.81744072, 0.80379574, 0.78184638, 0.78961663, 0.79389612,
           0.79531584, 0.78922983, 0.69921466, 0.70427159, 0.7254762 ,
           0.76327688, 0.79069138, 0.80650189, 0.81163874, 0.7883263 ,
           0.7848791 , 0.79076334, 0.78869946, 0.7833772 , 0.7757966 ,
           0.6847055 , 0.69369506, 0.70383968, 0.72895598, 0.74496548,
           0.76167612, 0.78266439, 0.77996243, 0.77036614, 0.78199759,
           0.78581058, 0.78482676, 0.77931903, 0.76971852, 0.67065414,
           0.68644689, 0.69270616, 0.71563597, 0.73505475, 0.71114191,
           0.7237427 , 0.74386541, 0.74280411, 0.75400492, 0.76673706,
           0.77184574, 0.64051415, 0.65885599, 0.68081681, 0.6980544 ,
           0.70610292, 0.70841966, 0.72183273, 0.73403143, 0.75271763,
           0.75388315, 0.75290199, 0.6291211 , 0.63717018, 0.64963584,
           0.67139374, 0.69565407, 0.71785886, 0.72887666, 0.74419907,
           0.7552502 , 0.75207638, 0.75416398, 0.75516113, 0.62291482,
           0.63439024, 0.63869451, 0.64444827, 0.66384714, 0.67916757,
           0.7079413 , 0.7335589 , 0.74672627, 0.74291721, 0.75174006,
           0.75565524, 0.74557645, 0.74514851, 0.68520715, 0.69789764,
    ...
           0.68829944, 0.64661849, 0.71172728, 0.71148705, 0.7591919 ,
           0.77567222, 0.77562577, 0.77036596, 0.77536177, 0.77972741,
           0.78504294, 0.71201141, 0.70423478, 0.69605553, 0.73023097,
           0.68357105, 0.68616287, 0.72137251, 0.75154399, 0.77266274,
           0.77554938, 0.78004963, 0.78464195, 0.78726087, 0.72042915,
           0.71057987, 0.69879659, 0.68388983, 0.67395816, 0.6961626 ,
           0.7278623 , 0.76067477, 0.78015573, 0.80347548, 0.70053737,
           0.72373015, 0.7470497 , 0.75924286, 0.66988404, 0.67721001,
           0.71846613, 0.7544203 , 0.78237761, 0.73167226, 0.7612325 ,
           0.74589222, 0.72367197, 0.70541807, 0.69533049, 0.68489234,
           0.67507964, 0.70420358, 0.73996407, 0.77249459, 0.72577718,
           0.73817897, 0.7216929 , 0.71436194, 0.70907164, 0.70683705,
           0.69869525, 0.70395355, 0.73477409, 0.75797299, 0.77648456,
           0.81378615, 0.73234149, 0.73435933, 0.73168352, 0.72059965,
           0.71229493, 0.70949439, 0.73532316, 0.75622774, 0.76568841,
           0.77727722, 0.79169415, 0.80894542, 0.83260454, 0.8243087 ,
           0.81752162, 0.72963924, 0.71458684, 0.72375714, 0.7446561 ,
           0.7605723 , 0.77850681, 0.79784976, 0.81046977, 0.82580037,
           0.75365008, 0.76960899, 0.78991425, 0.80605526, 0.7537158 ,
           0.77928607, 0.80695519, 0.73512012, 0.76134598, 0.77939231])

  • roughness
    (location)
    float64
    0.05 0.05 0.05 ... 0.05 0.05 0.05

    array([0.05 , 0.05 , 0.05 , 0.05 , 0.03 , 0.03 , 0.05 , 0.05 , 0.03 ,
           0.03 , 0.05 , 0.05 , 0.5  , 0.05 , 0.05 , 0.03 , 0.05 , 0.05 ,
           0.05 , 0.05 , 0.05 , 0.05 , 0.5  , 0.5  , 0.03 , 0.03 , 0.03 ,
           0.05 , 0.05 , 0.05 , 0.05 , 0.05 , 0.05 , 0.05 , 0.05 , 0.5  ,
           0.5  , 0.5  , 0.5  , 0.5  , 0.03 , 0.03 , 0.05 , 0.05 , 0.05 ,
           0.05 , 0.5  , 0.05 , 0.05 , 0.5  , 0.5  , 0.5  , 0.5  , 0.075,
           0.3  , 0.5  , 0.3  , 0.3  , 0.05 , 0.05 , 0.05 , 0.5  , 0.5  ,
           0.5  , 0.5  , 0.075, 0.5  , 0.5  , 0.05 , 0.05 , 0.05 , 0.05 ,
           0.5  , 0.6  , 0.5  , 0.5  , 0.05 , 0.03 , 0.05 , 0.05 , 0.5  ,
           0.5  , 0.5  , 0.5  , 0.5  , 0.5  , 0.5  , 0.5  , 1.2  , 0.03 ,
           0.05 , 0.03 , 0.05 , 0.05 , 0.5  , 0.5  , 0.5  , 0.3  , 0.005,
           0.3  , 0.5  , 0.5  , 0.5  , 0.5  , 0.5  , 0.5  , 0.5  , 0.03 ,
           0.5  , 0.5  , 0.05 , 0.05 , 0.5  , 0.5  , 0.5  , 0.5  , 0.5  ,
           0.5  , 0.5  , 0.05 , 0.5  , 0.05 , 0.05 , 0.5  , 0.5  , 0.6  ,
           0.5  , 0.5  , 0.5  , 0.3  , 0.03 , 0.05 , 0.05 , 0.5  , 0.05 ,
           0.05 , 0.05 , 0.05 , 0.03 , 0.5  , 0.5  , 0.5  , 0.6  , 0.5  ,
           0.5  , 0.03 , 0.03 , 0.5  , 0.5  , 0.5  , 0.05 , 0.05 , 0.05 ,
           0.05 , 0.5  , 0.005, 0.03 , 0.5  , 0.03 , 0.03 , 0.03 , 0.03 ,
           0.5  , 0.5  , 0.5  , 0.5  , 0.05 , 0.5  , 0.5  , 0.05 , 0.5  ,
           0.5  , 0.5  , 0.5  , 0.05 , 0.05 , 0.05 , 0.5  , 0.5  , 0.03 ,
    ...
           0.05 , 0.05 , 0.05 , 0.05 , 0.03 , 0.5  , 0.03 , 0.03 , 0.5  ,
           0.5  , 0.5  , 0.5  , 0.05 , 0.05 , 0.05 , 0.05 , 0.05 , 0.05 ,
           0.5  , 0.5  , 0.03 , 0.05 , 0.05 , 0.05 , 0.05 , 0.5  , 0.05 ,
           0.05 , 0.05 , 0.3  , 0.03 , 0.03 , 0.03 , 0.5  , 0.5  , 0.5  ,
           0.5  , 0.05 , 0.05 , 0.5  , 0.05 , 0.05 , 0.5  , 0.05 , 0.05 ,
           0.5  , 0.05 , 0.05 , 0.5  , 0.05 , 0.05 , 0.5  , 0.03 , 0.03 ,
           0.5  , 0.6  , 0.5  , 0.6  , 0.5  , 0.05 , 0.05 , 0.03 , 0.5  ,
           0.5  , 0.005, 0.05 , 0.05 , 0.005, 0.05 , 0.03 , 0.03 , 0.5  ,
           0.5  , 0.03 , 0.005, 0.03 , 0.03 , 0.05 , 0.05 , 0.5  , 0.05 ,
           0.05 , 0.05 , 0.05 , 0.03 , 0.03 , 0.5  , 0.03 , 0.5  , 0.5  ,
           0.5  , 0.05 , 0.05 , 0.05 , 0.05 , 0.05 , 0.05 , 0.03 , 0.03 ,
           0.03 , 0.5  , 0.5  , 0.5  , 0.05 , 0.05 , 0.05 , 0.05 , 0.03 ,
           0.03 , 0.3  , 0.03 , 0.5  , 0.5  , 0.5  , 0.05 , 0.5  , 0.03 ,
           0.03 , 0.03 , 0.005, 0.05 , 0.5  , 0.5  , 0.5  , 0.5  , 0.05 ,
           0.5  , 0.5  , 0.03 , 0.05 , 0.03 , 0.05 , 0.05 , 0.03 , 0.5  ,
           0.05 , 0.05 , 0.05 , 0.05 , 0.05 , 0.03 , 0.3  , 0.05 , 0.05 ,
           0.03 , 0.5  , 0.05 , 0.5  , 0.05 , 0.05 , 0.05 , 0.05 , 0.05 ,
           0.05 , 0.05 , 0.05 , 0.03 , 0.5  , 0.5  , 0.5  , 0.05 , 0.05 ,
           0.05 , 0.5  , 0.05 , 0.05 , 0.05 , 0.05 , 0.5  , 0.05 , 0.05 ,
           0.05 , 0.05 ])

  • elevated_wind_speed
    (time, location)
    float64
    4.905 5.191 5.217 ... 6.12 6.271

    array([[4.90475713, 5.19131432, 5.21674988, ..., 4.85629974, 5.03737875,
            5.16481271],
           [4.93926353, 5.22442092, 5.25213226, ..., 4.82976222, 5.01168692,
            5.14034956],
           [4.91519087, 5.19625101, 5.22521683, ..., 4.76174563, 4.94261138,
            5.07103677],
           ...,
           [4.1370214 , 4.39452829, 4.39961837, ..., 4.35836331, 4.49954588,
            4.5915557 ],
           [4.46522621, 4.73685985, 4.76027815, ..., 4.91181786, 5.08885995,
            5.21135532],
           [5.5450376 , 5.87698034, 5.90828943, ..., 5.90357056, 6.11991708,
            6.27087215]])

  • surface_pressure
    (time, location)
    float64
    1.012e+05 1.012e+05 ... 9.999e+04

    array([[101248.24728916, 101213.85316145, 101260.5603818 , ...,
            101116.35116052, 101170.04132549, 101223.75680374],
           [101247.20935001, 101212.9366924 , 101259.63651312, ...,
            101119.06726719, 101172.74084572, 101226.43991942],
           [101247.34997501, 101213.0773174 , 101259.77713812, ...,
            101119.57243636, 101173.22942844, 101226.9120976 ],
           ...,
           [ 99761.07001272,  99726.42086263,  99772.60569239, ...,
             99601.08523915,  99653.90533677,  99706.75168575],
           [ 99907.91380639,  99873.16256381,  99919.20606043, ...,
             99742.65577993,  99795.36816053,  99848.10679273],
           [100062.02156174, 100026.95463632, 100072.91264399, ...,
             99885.01923267,  99937.63067816,  99990.26837791]])

  • surface_air_temperature
    (time, location)
    float64
    -1.014 -1.044 ... -1.071 -1.044

    array([[-1.01401637, -1.04377745, -1.01646283, ..., -1.52243529,
            -1.499578  , -1.47672575],
           [-0.93711752, -0.96425598, -0.93907914, ..., -1.43801379,
            -1.41765795, -1.39730858],
           [-0.90531322, -0.92889468, -0.90556949, ..., -1.3511966 ,
            -1.33168028, -1.31216973],
           ...,
           [-1.65410146, -1.65686971, -1.6546221 , ..., -1.72694263,
            -1.72567729, -1.72439987],
           [-1.53859159, -1.55313887, -1.53149112, ..., -1.53966408,
            -1.51730774, -1.49491786],
           [-1.13726117, -1.15412638, -1.12712551, ..., -1.0979303 ,
            -1.07108455, -1.04420548]])

  • capacity_factor
    (time, location)
    float64
    0.07048 0.05571 ... 0.2154 0.154

    array([[0.07047806, 0.05571119, 0.09921612, ..., 0.03727737, 0.08180391,
            0.0541426 ],
           [0.07390768, 0.05809232, 0.10299821, ..., 0.03592092, 0.0800284 ,
            0.05258938],
           [0.07133069, 0.05650117, 0.10015808, ..., 0.03326523, 0.07390768,
            0.0487753 ],
           ...,
           [0.0246053 , 0.01907235, 0.03727737, ..., 0.01803572, 0.04288669,
            0.02577928],
           [0.04074945, 0.03196664, 0.05969819, ..., 0.04004594, 0.08719858,
            0.05729489],
           [0.13549641, 0.1106725 , 0.1837451 , ..., 0.11358644, 0.21535322,
            0.15403718]])

In [5]:

# Access raw data
gen["capacity_factor"].data

# Access raw data gen["capacity_factor"].data

Out[5]:

array([[0.07047806, 0.05571119, 0.09921612, ..., 0.03727737, 0.08180391,
        0.0541426 ],
       [0.07390768, 0.05809232, 0.10299821, ..., 0.03592092, 0.0800284 ,
        0.05258938],
       [0.07133069, 0.05650117, 0.10015808, ..., 0.03326523, 0.07390768,
        0.0487753 ],
       ...,
       [0.0246053 , 0.01907235, 0.03727737, ..., 0.01803572, 0.04288669,
        0.02577928],
       [0.04074945, 0.03196664, 0.05969819, ..., 0.04004594, 0.08719858,
        0.05729489],
       [0.13549641, 0.1106725 , 0.1837451 , ..., 0.11358644, 0.21535322,
        0.15403718]])

In [6]:

# Recover as a dataframe
gen["capacity_factor"].to_dataframe().unstack(level=-1)

# Recover as a dataframe gen["capacity_factor"].to_dataframe().unstack(level=-1)

Out[6]:

	capacity_factor
location	0	1	2	3	4	5	6	7	8	9	...	550	551	552	553	554	555	556	557	558	559
time
2015-01-01 00:30:00	0.070478	0.055711	0.099216	0.028192	0.077387	0.060507	0.116519	0.063776	0.109705	0.062134	...	0.105859	0.051052	0.102998	0.067940	0.078265	0.074773	0.114562	0.037277	0.081804	0.054143
2015-01-01 01:30:00	0.073908	0.058092	0.102998	0.028808	0.080028	0.062953	0.119470	0.066264	0.112613	0.064602	...	0.102998	0.049530	0.101102	0.066264	0.075641	0.073046	0.111642	0.035921	0.080028	0.052589
2015-01-01 02:30:00	0.071331	0.056501	0.100158	0.027581	0.077387	0.060507	0.115540	0.063776	0.109705	0.062134	...	0.095473	0.045797	0.093616	0.061319	0.070478	0.067100	0.103950	0.033265	0.073908	0.048775
2015-01-01 03:30:00	0.064602	0.050289	0.090850	0.024605	0.069629	0.054143	0.104903	0.057295	0.099216	0.055711	...	0.081804	0.037963	0.080028	0.051819	0.059698	0.057295	0.089933	0.027581	0.062953	0.040749
2015-01-01 04:30:00	0.080028	0.062953	0.109705	0.031325	0.085389	0.067100	0.126424	0.070478	0.118485	0.067940	...	0.092691	0.043608	0.090850	0.058893	0.067940	0.064602	0.101102	0.031967	0.071331	0.046536
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
2015-01-03 18:30:00	0.019072	0.014601	0.028192	0.005930	0.021217	0.015073	0.033922	0.015551	0.030056	0.014135	...	0.006909	0.002093	0.005619	0.002714	0.003658	0.003410	0.006249	0.001084	0.003658	0.001722
2015-01-03 19:30:00	0.024605	0.019072	0.035921	0.009067	0.028808	0.020672	0.045797	0.021217	0.041457	0.019600	...	0.031967	0.011905	0.026975	0.014601	0.021217	0.019072	0.029430	0.008689	0.021767	0.011905
2015-01-03 20:30:00	0.024605	0.019072	0.037277	0.008689	0.028808	0.021217	0.046536	0.022886	0.043608	0.021767	...	0.055711	0.024027	0.051052	0.031325	0.040046	0.037277	0.058092	0.018036	0.042887	0.025779
2015-01-03 21:30:00	0.040749	0.031967	0.059698	0.015073	0.045797	0.035250	0.073046	0.037963	0.069629	0.037277	...	0.106817	0.051052	0.102998	0.067100	0.080915	0.076513	0.116519	0.040046	0.087199	0.057295
2015-01-03 22:30:00	0.135496	0.110672	0.183745	0.060507	0.147802	0.119470	0.214252	0.127425	0.205469	0.125425	...	0.257636	0.141621	0.252032	0.179446	0.204375	0.197825	0.277888	0.113586	0.215353	0.154037

71 rows × 560 columns

In [7]:

%matplotlib inline
import matplotlib.pyplot as plt

plt.rc("font", size=18)
df = gen["capacity_factor"].to_dataframe().unstack(level=-1)
df.plot(legend=False, figsize=(12, 6))
plt.ylabel("Generation [kWh]")
plt.xlabel("Time")
plt.grid()
plt.show()

%matplotlib inline import matplotlib.pyplot as plt plt.rc("font", size=18) df = gen["capacity_factor"].to_dataframe().unstack(level=-1) df.plot(legend=False, figsize=(12, 6)) plt.ylabel("Generation [kWh]") plt.xlabel("Time") plt.grid() plt.show()