Running the national scale example model¶

This notebook will show you how to load, build, solve, and examine the results of the national scale example model.

In [1]:

import pandas as pd
import plotly.express as px

import calliope

# We increase logging verbosity
calliope.set_log_verbosity("INFO", include_solver_output=False)

import pandas as pd import plotly.express as px import calliope # We increase logging verbosity calliope.set_log_verbosity("INFO", include_solver_output=False)

Load model and examine inputs¶

In [2]:

model = calliope.examples.national_scale()

model = calliope.examples.national_scale()

[2025-03-14 18:57:16] INFO     Model: initialising

[2025-03-14 18:57:16] INFO     Model: preprocessing stage 1 (model_run)

[2025-03-14 18:57:18] INFO     Model: preprocessing stage 2 (model_data)

[2025-03-14 18:57:18] INFO     Model: preprocessing complete

Model inputs can be viewed at model.inputs. Variables are indexed over any combination of techs, nodes, carriers, costs and timesteps.

In [3]:

model.inputs

model.inputs

Out[3]:

<xarray.Dataset> Size: 82kB
Dimensions:                       (costs: 1, techs: 8, nodes: 5, carriers: 1,
                                   timesteps: 120)
Coordinates:
  * costs                         (costs) object 8B 'monetary'
  * techs                         (techs) object 64B 'battery' ... 'region1_t...
  * carriers                      (carriers) object 8B 'power'
  * nodes                         (nodes) <U9 180B 'region1' ... 'region2'
  * timesteps                     (timesteps) datetime64[ns] 960B 2005-01-01 ...
Data variables: (12/35)
    cost_interest_rate            (costs) float64 8B 0.1
    bigM                          float64 8B 1e+06
    objective_cost_weights        (costs) float64 8B 1.0
    base_tech                     (techs) object 64B 'storage' ... 'transmiss...
    carrier_in                    (nodes, techs, carriers) float64 320B nan ....
    color                         (techs) object 64B '#3B61E3' ... '#8465A9'
    ...                            ...
    sink_use_equals               (timesteps, nodes, techs) float64 38kB nan ...
    source_use_max                (timesteps, nodes, techs) float64 38kB nan ...
    definition_matrix             (nodes, techs, carriers) bool 40B False ......
    distance                      (techs) float64 64B nan nan ... 111.0 512.3
    timestep_resolution           (timesteps) float64 960B 1.0 1.0 ... 1.0 1.0
    timestep_weights              (timesteps) float64 960B 1.0 1.0 ... 1.0 1.0
Attributes:
    calliope_version_defined:      0.7.0
    calliope_version_initialised:  0.7.0.dev5
    applied_overrides:             
    scenario:                      None
    defaults:                      {'bigM': 1000000000.0, 'objective_cost_wei...
    allow_operate_mode:            1
    name:                          National-scale example model
    timestamp_model_creation:      1741978636.499071

xarray.Dataset

• Dimensions:
  • costs: 1
  • techs: 8
  • nodes: 5
  • carriers: 1
  • timesteps: 120
• Coordinates: (5)
  • costs
    (costs)
    object
    'monetary'

    array(['monetary'], dtype=object)

  • techs
    (techs)
    object
    'battery' ... 'region1_to_region2'

    array(['battery', 'ccgt', 'csp', 'demand_power', 'region1_to_region1_1',
           'region1_to_region1_2', 'region1_to_region1_3', 'region1_to_region2'],
          dtype=object)

  • carriers
    (carriers)
    object
    'power'

    array(['power'], dtype=object)

  • nodes
    (nodes)
    <U9
    'region1' 'region1_1' ... 'region2'

    array(['region1', 'region1_1', 'region1_2', 'region1_3', 'region2'],
          dtype='<U9')

  • timesteps
    (timesteps)
    datetime64[ns]
    2005-01-01 ... 2005-01-05T23:00:00

    array(['2005-01-01T00:00:00.000000000', '2005-01-01T01:00:00.000000000',
           '2005-01-01T02:00:00.000000000', '2005-01-01T03:00:00.000000000',
           '2005-01-01T04:00:00.000000000', '2005-01-01T05:00:00.000000000',
           '2005-01-01T06:00:00.000000000', '2005-01-01T07:00:00.000000000',
           '2005-01-01T08:00:00.000000000', '2005-01-01T09:00:00.000000000',
           '2005-01-01T10:00:00.000000000', '2005-01-01T11:00:00.000000000',
           '2005-01-01T12:00:00.000000000', '2005-01-01T13:00:00.000000000',
           '2005-01-01T14:00:00.000000000', '2005-01-01T15:00:00.000000000',
           '2005-01-01T16:00:00.000000000', '2005-01-01T17:00:00.000000000',
           '2005-01-01T18:00:00.000000000', '2005-01-01T19:00:00.000000000',
           '2005-01-01T20:00:00.000000000', '2005-01-01T21:00:00.000000000',
           '2005-01-01T22:00:00.000000000', '2005-01-01T23:00:00.000000000',
           '2005-01-02T00:00:00.000000000', '2005-01-02T01:00:00.000000000',
           '2005-01-02T02:00:00.000000000', '2005-01-02T03:00:00.000000000',
           '2005-01-02T04:00:00.000000000', '2005-01-02T05:00:00.000000000',
           '2005-01-02T06:00:00.000000000', '2005-01-02T07:00:00.000000000',
           '2005-01-02T08:00:00.000000000', '2005-01-02T09:00:00.000000000',
           '2005-01-02T10:00:00.000000000', '2005-01-02T11:00:00.000000000',
           '2005-01-02T12:00:00.000000000', '2005-01-02T13:00:00.000000000',
           '2005-01-02T14:00:00.000000000', '2005-01-02T15:00:00.000000000',
           '2005-01-02T16:00:00.000000000', '2005-01-02T17:00:00.000000000',
           '2005-01-02T18:00:00.000000000', '2005-01-02T19:00:00.000000000',
           '2005-01-02T20:00:00.000000000', '2005-01-02T21:00:00.000000000',
           '2005-01-02T22:00:00.000000000', '2005-01-02T23:00:00.000000000',
           '2005-01-03T00:00:00.000000000', '2005-01-03T01:00:00.000000000',
           '2005-01-03T02:00:00.000000000', '2005-01-03T03:00:00.000000000',
           '2005-01-03T04:00:00.000000000', '2005-01-03T05:00:00.000000000',
           '2005-01-03T06:00:00.000000000', '2005-01-03T07:00:00.000000000',
           '2005-01-03T08:00:00.000000000', '2005-01-03T09:00:00.000000000',
           '2005-01-03T10:00:00.000000000', '2005-01-03T11:00:00.000000000',
           '2005-01-03T12:00:00.000000000', '2005-01-03T13:00:00.000000000',
           '2005-01-03T14:00:00.000000000', '2005-01-03T15:00:00.000000000',
           '2005-01-03T16:00:00.000000000', '2005-01-03T17:00:00.000000000',
           '2005-01-03T18:00:00.000000000', '2005-01-03T19:00:00.000000000',
           '2005-01-03T20:00:00.000000000', '2005-01-03T21:00:00.000000000',
           '2005-01-03T22:00:00.000000000', '2005-01-03T23:00:00.000000000',
           '2005-01-04T00:00:00.000000000', '2005-01-04T01:00:00.000000000',
           '2005-01-04T02:00:00.000000000', '2005-01-04T03:00:00.000000000',
           '2005-01-04T04:00:00.000000000', '2005-01-04T05:00:00.000000000',
           '2005-01-04T06:00:00.000000000', '2005-01-04T07:00:00.000000000',
           '2005-01-04T08:00:00.000000000', '2005-01-04T09:00:00.000000000',
           '2005-01-04T10:00:00.000000000', '2005-01-04T11:00:00.000000000',
           '2005-01-04T12:00:00.000000000', '2005-01-04T13:00:00.000000000',
           '2005-01-04T14:00:00.000000000', '2005-01-04T15:00:00.000000000',
           '2005-01-04T16:00:00.000000000', '2005-01-04T17:00:00.000000000',
           '2005-01-04T18:00:00.000000000', '2005-01-04T19:00:00.000000000',
           '2005-01-04T20:00:00.000000000', '2005-01-04T21:00:00.000000000',
           '2005-01-04T22:00:00.000000000', '2005-01-04T23:00:00.000000000',
           '2005-01-05T00:00:00.000000000', '2005-01-05T01:00:00.000000000',
           '2005-01-05T02:00:00.000000000', '2005-01-05T03:00:00.000000000',
           '2005-01-05T04:00:00.000000000', '2005-01-05T05:00:00.000000000',
           '2005-01-05T06:00:00.000000000', '2005-01-05T07:00:00.000000000',
           '2005-01-05T08:00:00.000000000', '2005-01-05T09:00:00.000000000',
           '2005-01-05T10:00:00.000000000', '2005-01-05T11:00:00.000000000',
           '2005-01-05T12:00:00.000000000', '2005-01-05T13:00:00.000000000',
           '2005-01-05T14:00:00.000000000', '2005-01-05T15:00:00.000000000',
           '2005-01-05T16:00:00.000000000', '2005-01-05T17:00:00.000000000',
           '2005-01-05T18:00:00.000000000', '2005-01-05T19:00:00.000000000',
           '2005-01-05T20:00:00.000000000', '2005-01-05T21:00:00.000000000',
           '2005-01-05T22:00:00.000000000', '2005-01-05T23:00:00.000000000'],
          dtype='datetime64[ns]')

• Data variables: (35)
  • cost_interest_rate
    (costs)
    float64
    0.1

    is_result :

    False

    default :

    0

    array([0.1])

  • bigM
    ()
    float64
    1e+06

    is_result :

    False

    default :

    1000000000.0

    array(1000000.)

  • objective_cost_weights
    (costs)
    float64
    1.0

    is_result :

    False

    default :

    1

    array([1.])

  • base_tech
    (techs)
    object
    'storage' ... 'transmission'

    is_result :

    False

    array(['storage', 'supply', 'supply', 'demand', 'transmission',
           'transmission', 'transmission', 'transmission'], dtype=object)

  • carrier_in
    (nodes, techs, carriers)
    float64
    nan nan nan 1.0 ... nan nan nan 1.0

    is_result :

    False

    array([[[nan],
            [nan],
            [nan],
            [ 1.],
            [ 1.],
            [ 1.],
            [ 1.],
            [ 1.]],
    
           [[nan],
            [nan],
            [nan],
            [nan],
            [ 1.],
            [nan],
            [nan],
            [nan]],
    
           [[nan],
            [nan],
    ...
            [nan],
            [nan]],
    
           [[nan],
            [nan],
            [nan],
            [nan],
            [nan],
            [nan],
            [ 1.],
            [nan]],
    
           [[ 1.],
            [nan],
            [nan],
            [ 1.],
            [nan],
            [nan],
            [nan],
            [ 1.]]])

  • color
    (techs)
    object
    '#3B61E3' '#E37A72' ... '#8465A9'

    is_result :

    False

    default :

    nan

    array(['#3B61E3', '#E37A72', '#F9CF22', '#072486', '#6783E3', '#6783E3',
           '#6783E3', '#8465A9'], dtype=object)

  • name
    (techs)
    object
    'Battery storage' ... 'AC power ...

    is_result :

    False

    default :

    nan

    array(['Battery storage', 'Combined cycle gas turbine',
           'Concentrating solar power', 'Power demand',
           'Local power transmission', 'Local power transmission',
           'Local power transmission', 'AC power transmission'], dtype=object)

  • carrier_out
    (nodes, techs, carriers)
    float64
    nan 1.0 nan nan ... nan nan nan 1.0

    is_result :

    False

    array([[[nan],
            [ 1.],
            [nan],
            [nan],
            [ 1.],
            [ 1.],
            [ 1.],
            [ 1.]],
    
           [[nan],
            [nan],
            [ 1.],
            [nan],
            [ 1.],
            [nan],
            [nan],
            [nan]],
    
           [[nan],
            [nan],
    ...
            [nan],
            [nan]],
    
           [[nan],
            [nan],
            [ 1.],
            [nan],
            [nan],
            [nan],
            [ 1.],
            [nan]],
    
           [[ 1.],
            [nan],
            [nan],
            [nan],
            [nan],
            [nan],
            [nan],
            [ 1.]]])

  • flow_cap_max
    (nodes, techs)
    float64
    nan 3e+04 nan nan ... nan nan 1e+04

    is_result :

    False

    default :

    inf

    array([[   nan, 30000.,    nan,    nan,    nan,    nan,    nan, 10000.],
           [   nan,    nan, 10000.,    nan,    nan,    nan,    nan,    nan],
           [   nan,    nan, 10000.,    nan,    nan,    nan,    nan,    nan],
           [   nan,    nan, 10000.,    nan,    nan,    nan,    nan,    nan],
           [ 1000.,    nan,    nan,    nan,    nan,    nan,    nan, 10000.]])

  • flow_cap_max_systemwide
    (techs)
    float64
    nan 1e+05 nan nan nan nan nan nan

    is_result :

    False

    default :

    inf

    array([    nan, 100000.,     nan,     nan,     nan,     nan,     nan,
               nan])

  • flow_out_eff
    (techs)
    float64
    0.95 0.5 0.4 nan nan nan nan 0.85

    is_result :

    False

    default :

    1.0

    array([0.95, 0.5 , 0.4 ,  nan,  nan,  nan,  nan, 0.85])

  • flow_ramping
    (techs)
    float64
    nan 0.8 nan nan nan nan nan nan

    is_result :

    False

    default :

    1.0

    array([nan, 0.8, nan, nan, nan, nan, nan, nan])

  • lifetime
    (techs)
    float64
    25.0 25.0 25.0 nan nan nan nan 25.0

    is_result :

    False

    default :

    inf

    array([25., 25., 25., nan, nan, nan, nan, 25.])

  • area_use_max
    (techs)
    float64
    nan nan inf nan nan nan nan nan

    is_result :

    False

    default :

    inf

    array([nan, nan, inf, nan, nan, nan, nan, nan])

  • flow_cap_per_storage_cap_max
    (techs)
    float64
    4.0 nan 1.0 nan nan nan nan nan

    is_result :

    False

    default :

    inf

    array([ 4., nan,  1., nan, nan, nan, nan, nan])

  • flow_out_parasitic_eff
    (techs)
    float64
    nan nan 0.9 nan nan nan nan nan

    is_result :

    False

    default :

    1.0

    array([nan, nan, 0.9, nan, nan, nan, nan, nan])

  • include_storage
    (techs)
    float64
    nan nan 1.0 nan nan nan nan nan

    is_result :

    False

    default :

    False

    array([nan, nan,  1., nan, nan, nan, nan, nan])

  • source_unit
    (techs)
    object
    nan nan 'per_area' ... nan nan nan

    is_result :

    False

    default :

    absolute

    array([nan, nan, 'per_area', nan, nan, nan, nan, nan], dtype=object)

  • storage_cap_max
    (techs)
    float64
    inf nan 6.14e+05 ... nan nan nan

    is_result :

    False

    default :

    inf

    array([    inf,     nan, 614033.,     nan,     nan,     nan,     nan,
               nan])

  • storage_loss
    (techs)
    float64
    0.0 nan 0.002 nan nan nan nan nan

    is_result :

    False

    default :

    0

    array([0.   ,   nan, 0.002,   nan,   nan,   nan,   nan,   nan])

  • flow_in_eff
    (techs)
    float64
    0.95 nan nan nan nan nan nan nan

    is_result :

    False

    default :

    1.0

    array([0.95,  nan,  nan,  nan,  nan,  nan,  nan,  nan])

  • latitude
    (nodes)
    float64
    40.0 41.0 39.0 39.0 40.0

    is_result :

    False

    array([40., 41., 39., 39., 40.])

  • longitude
    (nodes)
    float64
    -2.0 -2.0 -1.0 -2.0 -8.0

    is_result :

    False

    array([-2., -2., -1., -2., -8.])

  • cost_area_use
    (costs, techs)
    float64
    nan nan 200.0 nan nan nan nan nan

    is_result :

    False

    default :

    0

    array([[ nan,  nan, 200.,  nan,  nan,  nan,  nan,  nan]])

  • cost_flow_cap
    (costs, techs)
    float64
    nan 750.0 1e+03 ... nan nan 200.0

    is_result :

    False

    default :

    0

    array([[  nan,  750., 1000.,   nan,   nan,   nan,   nan,  200.]])

  • cost_flow_in
    (costs, techs)
    float64
    nan 0.02 nan nan nan nan nan nan

    is_result :

    False

    default :

    0

    array([[ nan, 0.02,  nan,  nan,  nan,  nan,  nan,  nan]])

  • cost_flow_out
    (costs, techs)
    float64
    nan nan 0.002 nan nan nan nan 0.002

    is_result :

    False

    default :

    0

    array([[  nan,   nan, 0.002,   nan,   nan,   nan,   nan, 0.002]])

  • cost_source_cap
    (costs, techs)
    float64
    nan nan 200.0 nan nan nan nan nan

    is_result :

    False

    default :

    0

    array([[ nan,  nan, 200.,  nan,  nan,  nan,  nan,  nan]])

  • cost_storage_cap
    (costs, techs)
    float64
    200.0 nan 50.0 nan nan nan nan nan

    is_result :

    False

    default :

    0

    array([[200.,  nan,  50.,  nan,  nan,  nan,  nan,  nan]])

  • sink_use_equals
    (timesteps, nodes, techs)
    float64
    nan nan nan ... nan nan nan

    is_result :

    False

    default :

    nan

    array([[[nan, nan, nan, ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan]],
    
           [[nan, nan, nan, ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan]],
    
           [[nan, nan, nan, ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan]],
    
           ...,
    
           [[nan, nan, nan, ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan]],
    
           [[nan, nan, nan, ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan]],
    
           [[nan, nan, nan, ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan]]])

  • source_use_max
    (timesteps, nodes, techs)
    float64
    nan nan nan nan ... nan nan nan nan

    is_result :

    False

    default :

    inf

    array([[[nan, nan, nan, ..., nan, nan, nan],
            [nan, nan,  0., ..., nan, nan, nan],
            [nan, nan,  0., ..., nan, nan, nan],
            [nan, nan,  0., ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan]],
    
           [[nan, nan, nan, ..., nan, nan, nan],
            [nan, nan,  0., ..., nan, nan, nan],
            [nan, nan,  0., ..., nan, nan, nan],
            [nan, nan,  0., ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan]],
    
           [[nan, nan, nan, ..., nan, nan, nan],
            [nan, nan,  0., ..., nan, nan, nan],
            [nan, nan,  0., ..., nan, nan, nan],
            [nan, nan,  0., ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan]],
    
           ...,
    
           [[nan, nan, nan, ..., nan, nan, nan],
            [nan, nan,  0., ..., nan, nan, nan],
            [nan, nan,  0., ..., nan, nan, nan],
            [nan, nan,  0., ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan]],
    
           [[nan, nan, nan, ..., nan, nan, nan],
            [nan, nan,  0., ..., nan, nan, nan],
            [nan, nan,  0., ..., nan, nan, nan],
            [nan, nan,  0., ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan]],
    
           [[nan, nan, nan, ..., nan, nan, nan],
            [nan, nan,  0., ..., nan, nan, nan],
            [nan, nan,  0., ..., nan, nan, nan],
            [nan, nan,  0., ..., nan, nan, nan],
            [nan, nan, nan, ..., nan, nan, nan]]])

  • definition_matrix
    (nodes, techs, carriers)
    bool
    False True False ... False True

    is_result :

    False

    array([[[False],
            [ True],
            [False],
            [ True],
            [ True],
            [ True],
            [ True],
            [ True]],
    
           [[False],
            [False],
            [ True],
            [False],
            [ True],
            [False],
            [False],
            [False]],
    
           [[False],
            [False],
    ...
            [False],
            [False]],
    
           [[False],
            [False],
            [ True],
            [False],
            [False],
            [False],
            [ True],
            [False]],
    
           [[ True],
            [False],
            [False],
            [ True],
            [False],
            [False],
            [False],
            [ True]]])

  • distance
    (techs)
    float64
    nan nan nan ... 140.4 111.0 512.3

    is_result :

    False

    default :

    1.0

    array([         nan,          nan,          nan,          nan,
           111.04426088, 140.44294774, 111.02504555, 512.26635523])

  • timestep_resolution
    (timesteps)
    float64
    1.0 1.0 1.0 1.0 ... 1.0 1.0 1.0 1.0

    is_result :

    False

    array([1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
           1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
           1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
           1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
           1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
           1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
           1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
           1.])

  • timestep_weights
    (timesteps)
    float64
    1.0 1.0 1.0 1.0 ... 1.0 1.0 1.0 1.0

    is_result :

    False

    array([1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
           1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
           1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
           1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
           1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
           1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
           1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.,
           1.])

• Indexes: (5)
  • costs
    PandasIndex

    PandasIndex(Index(['monetary'], dtype='object', name='costs'))

  • techs
    PandasIndex

    PandasIndex(Index(['battery', 'ccgt', 'csp', 'demand_power', 'region1_to_region1_1',
           'region1_to_region1_2', 'region1_to_region1_3', 'region1_to_region2'],
          dtype='object', name='techs'))

  • carriers
    PandasIndex

    PandasIndex(Index(['power'], dtype='object', name='carriers'))

  • nodes
    PandasIndex

    PandasIndex(Index(['region1', 'region1_1', 'region1_2', 'region1_3', 'region2'], dtype='object', name='nodes'))

  • timesteps
    PandasIndex

    PandasIndex(DatetimeIndex(['2005-01-01 00:00:00', '2005-01-01 01:00:00',
                   '2005-01-01 02:00:00', '2005-01-01 03:00:00',
                   '2005-01-01 04:00:00', '2005-01-01 05:00:00',
                   '2005-01-01 06:00:00', '2005-01-01 07:00:00',
                   '2005-01-01 08:00:00', '2005-01-01 09:00:00',
                   ...
                   '2005-01-05 14:00:00', '2005-01-05 15:00:00',
                   '2005-01-05 16:00:00', '2005-01-05 17:00:00',
                   '2005-01-05 18:00:00', '2005-01-05 19:00:00',
                   '2005-01-05 20:00:00', '2005-01-05 21:00:00',
                   '2005-01-05 22:00:00', '2005-01-05 23:00:00'],
                  dtype='datetime64[ns]', name='timesteps', length=120, freq=None))

• Attributes: (8)

  calliope_version_defined :

  0.7.0

  calliope_version_initialised :

  0.7.0.dev5

  applied_overrides :

  scenario :

  None

  defaults :

  {'bigM': 1000000000.0, 'objective_cost_weights': 1, 'color': nan, 'name': nan, 'cap_method': 'continuous', 'integer_dispatch': False, 'include_storage': False, 'force_async_flow': False, 'flow_cap_per_storage_cap_min': 0, 'flow_cap_per_storage_cap_max': inf, 'flow_cap': inf, 'flow_cap_max': inf, 'flow_cap_max_systemwide': inf, 'flow_cap_min': 0, 'flow_cap_min_systemwide': 0, 'flow_out_min_relative': 0, 'flow_cap_per_unit': nan, 'flow_in_eff': 1.0, 'flow_out_eff': 1.0, 'flow_out_parasitic_eff': 1.0, 'flow_ramping': 1.0, 'export_max': inf, 'lifetime': inf, 'area_use': inf, 'area_use_max': inf, 'area_use_min': 0, 'area_use_per_flow_cap': nan, 'storage_cap': inf, 'storage_cap_max': inf, 'storage_cap_min': 0, 'storage_cap_per_unit': nan, 'storage_discharge_depth': 0, 'storage_initial': 0, 'storage_loss': 0, 'cyclic_storage': True, 'purchased_units_min_systemwide': 0, 'purchased_units_max_systemwide': inf, 'purchased_units': inf, 'purchased_units_min': 0, 'purchased_units_max': inf, 'sink_unit': 'absolute', 'sink_use_min': 0, 'sink_use_max': inf, 'sink_use_equals': nan, 'source_unit': 'absolute', 'source_cap_equals_flow_cap': False, 'source_eff': 1.0, 'source_use_min': 0, 'source_use_max': inf, 'source_use_equals': nan, 'source_cap': inf, 'source_cap_max': inf, 'source_cap_min': 0, 'one_way': False, 'distance': 1.0, 'flow_in_eff_per_distance': 1.0, 'flow_out_eff_per_distance': 1.0, 'cost_flow_cap_per_distance': 0, 'cost_purchase_per_distance': 0, 'cost_flow_cap': 0, 'cost_export': 0, 'cost_interest_rate': 0, 'cost_om_annual': 0, 'cost_om_annual_investment_fraction': 0, 'cost_flow_in': 0, 'cost_flow_out': 0, 'cost_purchase': 0, 'cost_area_use': 0, 'cost_source_cap': 0, 'cost_storage_cap': 0, 'cost_depreciation_rate': 1, 'available_area': inf}

  allow_operate_mode :

  1

  name :

  National-scale example model

  timestamp_model_creation :

  1741978636.499071

Individual data variables can be accessed easily, to_series().dropna() allows us to view the data in a nice tabular format.

In [4]:

model.inputs.flow_cap_max.to_series().dropna()

model.inputs.flow_cap_max.to_series().dropna()

Out[4]:

nodes      techs             
region1    ccgt                  30000.0
           region1_to_region2    10000.0
region1_1  csp                   10000.0
region1_2  csp                   10000.0
region1_3  csp                   10000.0
region2    battery                1000.0
           region1_to_region2    10000.0
Name: flow_cap_max, dtype: float64

You can apply node/tech/carrier/timesteps only operations, like summing information over timesteps

In [5]:

model.inputs.sink_use_equals.sum(
    "timesteps", min_count=1, skipna=True
).to_series().dropna()

model.inputs.sink_use_equals.sum( "timesteps", min_count=1, skipna=True ).to_series().dropna()

Out[5]:

nodes    techs       
region1  demand_power    3793748.48
region2  demand_power     288114.75
Name: sink_use_equals, dtype: float64

Build and solve the optimisation problem.¶

Results are loaded into model.results. By setting the log verbosity at the start of this tutorial to "INFO", we can see the timing of parts of the run, as well as the solver's log.

In [6]:

model.build()
model.solve()

model.build() model.solve()

[2025-03-14 18:57:18] INFO     Model: backend build starting

[2025-03-14 18:57:18] INFO     Math preprocessing | added file 'plan'.

[2025-03-14 18:57:18] INFO     Math preprocessing | validated math against schema.

[2025-03-14 18:57:18] INFO     Optimisation Model | parameters | Generated.

[2025-03-14 18:57:20] INFO     Optimisation Model | Validated math strings.

[2025-03-14 18:57:21] INFO     Optimisation Model | variables | Generated.

[2025-03-14 18:57:21] INFO     Optimisation Model | global_expressions | Generated.

[2025-03-14 18:57:23] INFO     Optimisation Model | constraints | Generated.

[2025-03-14 18:57:23] INFO     Optimisation Model | piecewise_constraints | Generated.

[2025-03-14 18:57:23] INFO     Optimisation Model | objectives | Generated.

[2025-03-14 18:57:23] INFO     Model: backend build complete

[2025-03-14 18:57:23] INFO     Optimisation model | starting model in plan mode.

[2025-03-14 18:57:23] INFO     Backend: solver finished running. Time since start of solving optimisation problem: 0:00:00.366870

[2025-03-14 18:57:23] WARNING  Postprocessing: All values < 1e-10 set to 0 in flow_out, flow_in, storage, flow_out_inc_eff, flow_in_inc_eff, capacity_factor

[2025-03-14 18:57:23] INFO     Postprocessing: ended. Time since start of solving optimisation problem: 0:00:00.460292

[2025-03-14 18:57:23] INFO     Backend: model solve completed. Time since start of solving optimisation problem: 0:00:00.462693

Model results are held in the same structure as model inputs. The results consist of the optimal values for all decision variables, including capacities and carrier flow. There are also results, like system capacity factor and levelised costs, which are calculated in postprocessing before being added to the results Dataset

Examine results¶

In [7]:

model.results

model.results

Out[7]:

<xarray.Dataset> Size: 317kB
Dimensions:                      (nodes: 5, techs: 8, carriers: 1,
                                  timesteps: 120, costs: 1)
Coordinates:
  * techs                        (techs) object 64B 'battery' ... 'region1_to...
  * carriers                     (carriers) <U5 20B 'power'
  * nodes                        (nodes) <U9 180B 'region1' ... 'region2'
  * timesteps                    (timesteps) datetime64[ns] 960B 2005-01-01 ....
  * costs                        (costs) object 8B 'monetary'
Data variables: (12/24)
    flow_cap                     (nodes, techs, carriers) float64 320B nan .....
    link_flow_cap                (techs) float64 64B nan nan ... 3.23e+03
    flow_out                     (nodes, techs, carriers, timesteps) float64 38kB ...
    flow_in                      (nodes, techs, carriers, timesteps) float64 38kB ...
    area_use                     (nodes, techs) float64 320B nan nan ... nan nan
    source_use                   (nodes, techs, timesteps) float64 38kB nan ....
    ...                           ...
    cost_investment_annualised   (nodes, techs, costs) float64 320B nan ... 4...
    cost                         (nodes, techs, costs) float64 320B nan ... 1...
    capacity_factor              (nodes, techs, carriers, timesteps) float64 38kB ...
    systemwide_capacity_factor   (techs, carriers) float64 64B 0.1317 ... 0.3738
    systemwide_levelised_cost    (carriers, techs, costs) float64 64B 0.1 ......
    total_levelised_cost         (carriers, costs) float64 8B 0.06701
Attributes: (12/13)
    termination_condition:         optimal
    calliope_version_defined:      0.7.0
    calliope_version_initialised:  0.7.0.dev5
    applied_overrides:             
    scenario:                      None
    defaults:                      {'bigM': 1000000000.0, 'objective_cost_wei...
    ...                            ...
    name:                          National-scale example model
    timestamp_model_creation:      1741978636.499071
    timestamp_build_start:         1741978638.386217
    timestamp_build_complete:      1741978643.435761
    timestamp_solve_start:         1741978643.437133
    timestamp_solve_complete:      1741978643.899826

xarray.Dataset

• Dimensions:
  • nodes: 5
  • techs: 8
  • carriers: 1
  • timesteps: 120
  • costs: 1
• Coordinates: (5)
  • techs
    (techs)
    object
    'battery' ... 'region1_to_region2'

    array(['battery', 'ccgt', 'csp', 'demand_power', 'region1_to_region1_1',
           'region1_to_region1_2', 'region1_to_region1_3', 'region1_to_region2'],
          dtype=object)

  • carriers
    (carriers)
    <U5
    'power'

    array(['power'], dtype='<U5')

  • nodes
    (nodes)
    <U9
    'region1' 'region1_1' ... 'region2'

    array(['region1', 'region1_1', 'region1_2', 'region1_3', 'region2'],
          dtype='<U9')

  • timesteps
    (timesteps)
    datetime64[ns]
    2005-01-01 ... 2005-01-05T23:00:00

    array(['2005-01-01T00:00:00.000000000', '2005-01-01T01:00:00.000000000',
           '2005-01-01T02:00:00.000000000', '2005-01-01T03:00:00.000000000',
           '2005-01-01T04:00:00.000000000', '2005-01-01T05:00:00.000000000',
           '2005-01-01T06:00:00.000000000', '2005-01-01T07:00:00.000000000',
           '2005-01-01T08:00:00.000000000', '2005-01-01T09:00:00.000000000',
           '2005-01-01T10:00:00.000000000', '2005-01-01T11:00:00.000000000',
           '2005-01-01T12:00:00.000000000', '2005-01-01T13:00:00.000000000',
           '2005-01-01T14:00:00.000000000', '2005-01-01T15:00:00.000000000',
           '2005-01-01T16:00:00.000000000', '2005-01-01T17:00:00.000000000',
           '2005-01-01T18:00:00.000000000', '2005-01-01T19:00:00.000000000',
           '2005-01-01T20:00:00.000000000', '2005-01-01T21:00:00.000000000',
           '2005-01-01T22:00:00.000000000', '2005-01-01T23:00:00.000000000',
           '2005-01-02T00:00:00.000000000', '2005-01-02T01:00:00.000000000',
           '2005-01-02T02:00:00.000000000', '2005-01-02T03:00:00.000000000',
           '2005-01-02T04:00:00.000000000', '2005-01-02T05:00:00.000000000',
           '2005-01-02T06:00:00.000000000', '2005-01-02T07:00:00.000000000',
           '2005-01-02T08:00:00.000000000', '2005-01-02T09:00:00.000000000',
           '2005-01-02T10:00:00.000000000', '2005-01-02T11:00:00.000000000',
           '2005-01-02T12:00:00.000000000', '2005-01-02T13:00:00.000000000',
           '2005-01-02T14:00:00.000000000', '2005-01-02T15:00:00.000000000',
           '2005-01-02T16:00:00.000000000', '2005-01-02T17:00:00.000000000',
           '2005-01-02T18:00:00.000000000', '2005-01-02T19:00:00.000000000',
           '2005-01-02T20:00:00.000000000', '2005-01-02T21:00:00.000000000',
           '2005-01-02T22:00:00.000000000', '2005-01-02T23:00:00.000000000',
           '2005-01-03T00:00:00.000000000', '2005-01-03T01:00:00.000000000',
           '2005-01-03T02:00:00.000000000', '2005-01-03T03:00:00.000000000',
           '2005-01-03T04:00:00.000000000', '2005-01-03T05:00:00.000000000',
           '2005-01-03T06:00:00.000000000', '2005-01-03T07:00:00.000000000',
           '2005-01-03T08:00:00.000000000', '2005-01-03T09:00:00.000000000',
           '2005-01-03T10:00:00.000000000', '2005-01-03T11:00:00.000000000',
           '2005-01-03T12:00:00.000000000', '2005-01-03T13:00:00.000000000',
           '2005-01-03T14:00:00.000000000', '2005-01-03T15:00:00.000000000',
           '2005-01-03T16:00:00.000000000', '2005-01-03T17:00:00.000000000',
           '2005-01-03T18:00:00.000000000', '2005-01-03T19:00:00.000000000',
           '2005-01-03T20:00:00.000000000', '2005-01-03T21:00:00.000000000',
           '2005-01-03T22:00:00.000000000', '2005-01-03T23:00:00.000000000',
           '2005-01-04T00:00:00.000000000', '2005-01-04T01:00:00.000000000',
           '2005-01-04T02:00:00.000000000', '2005-01-04T03:00:00.000000000',
           '2005-01-04T04:00:00.000000000', '2005-01-04T05:00:00.000000000',
           '2005-01-04T06:00:00.000000000', '2005-01-04T07:00:00.000000000',
           '2005-01-04T08:00:00.000000000', '2005-01-04T09:00:00.000000000',
           '2005-01-04T10:00:00.000000000', '2005-01-04T11:00:00.000000000',
           '2005-01-04T12:00:00.000000000', '2005-01-04T13:00:00.000000000',
           '2005-01-04T14:00:00.000000000', '2005-01-04T15:00:00.000000000',
           '2005-01-04T16:00:00.000000000', '2005-01-04T17:00:00.000000000',
           '2005-01-04T18:00:00.000000000', '2005-01-04T19:00:00.000000000',
           '2005-01-04T20:00:00.000000000', '2005-01-04T21:00:00.000000000',
           '2005-01-04T22:00:00.000000000', '2005-01-04T23:00:00.000000000',
           '2005-01-05T00:00:00.000000000', '2005-01-05T01:00:00.000000000',
           '2005-01-05T02:00:00.000000000', '2005-01-05T03:00:00.000000000',
           '2005-01-05T04:00:00.000000000', '2005-01-05T05:00:00.000000000',
           '2005-01-05T06:00:00.000000000', '2005-01-05T07:00:00.000000000',
           '2005-01-05T08:00:00.000000000', '2005-01-05T09:00:00.000000000',
           '2005-01-05T10:00:00.000000000', '2005-01-05T11:00:00.000000000',
           '2005-01-05T12:00:00.000000000', '2005-01-05T13:00:00.000000000',
           '2005-01-05T14:00:00.000000000', '2005-01-05T15:00:00.000000000',
           '2005-01-05T16:00:00.000000000', '2005-01-05T17:00:00.000000000',
           '2005-01-05T18:00:00.000000000', '2005-01-05T19:00:00.000000000',
           '2005-01-05T20:00:00.000000000', '2005-01-05T21:00:00.000000000',
           '2005-01-05T22:00:00.000000000', '2005-01-05T23:00:00.000000000'],
          dtype='datetime64[ns]')

  • costs
    (costs)
    object
    'monetary'

    array(['monetary'], dtype=object)

• Data variables: (24)
  • flow_cap
    (nodes, techs, carriers)
    float64
    nan 3e+04 nan ... nan nan 3.23e+03

    title :

    Technology flow (a.k.a. nominal) capacity

    description :

    A technology's flow capacity, also known as its nominal or nameplate capacity.

    default :

    0

    unit :

    power

    is_result :

    1

    array([[[       nan],
            [30000.    ],
            [       nan],
            [39033.52  ],
            [ 9000.    ],
            [    0.    ],
            [ 2280.3859],
            [ 3230.4729]],
    
           [[       nan],
            [       nan],
            [10000.    ],
            [       nan],
            [ 9000.    ],
            [       nan],
            [       nan],
            [       nan]],
    
           [[       nan],
            [       nan],
    ...
            [       nan],
            [       nan]],
    
           [[       nan],
            [       nan],
            [ 2533.7621],
            [       nan],
            [       nan],
            [       nan],
            [ 2280.3859],
            [       nan]],
    
           [[ 1000.    ],
            [       nan],
            [       nan],
            [ 2909.836 ],
            [       nan],
            [       nan],
            [       nan],
            [ 3230.4729]]])

  • link_flow_cap
    (techs)
    float64
    nan nan nan ... 2.28e+03 3.23e+03

    title :

    Link flow capacity

    description :

    A transmission technology's flow capacity, also known as its nominal or nameplate capacity.

    default :

    0

    unit :

    power

    is_result :

    1

    array([      nan,       nan,       nan,       nan, 9000.    ,   -0.    ,
           2280.3859, 3230.4729])

  • flow_out
    (nodes, techs, carriers, timesteps)
    float64
    nan nan nan ... 2.254e+03 2.295e+03

    title :

    Carrier outflow

    description :

    The outflow of a technology per timestep, also known as the flow discharged (from `storage` technologies) or the flow received (by `transmission` technologies) on a link.

    default :

    0

    unit :

    energy

    is_result :

    1

    array([[[[       nan,        nan,        nan, ...,        nan,
                     nan,        nan]],
    
            [[27936.36  , 26894.673 , 26189.672 , ..., 25234.128 ,
              23042.504 , 22834.531 ]],
    
            [[       nan,        nan,        nan, ...,        nan,
                     nan,        nan]],
    
            ...,
    
            [[    0.    ,     0.    ,     0.    , ...,     0.    ,
                  0.    ,     0.    ]],
    
            [[    0.    ,     0.    ,     0.    , ...,     0.    ,
                  0.    ,     0.    ]],
    
            [[    0.    ,     0.    ,     0.    , ...,     0.    ,
                  0.    ,     0.    ]]],
    
    ...
    
           [[[    0.    ,     0.    ,     0.    , ...,     0.    ,
                  0.    ,     0.    ]],
    
            [[       nan,        nan,        nan, ...,        nan,
                     nan,        nan]],
    
            [[       nan,        nan,        nan, ...,        nan,
                     nan,        nan]],
    
            ...,
    
            [[       nan,        nan,        nan, ...,        nan,
                     nan,        nan]],
    
            [[       nan,        nan,        nan, ...,        nan,
                     nan,        nan]],
    
            [[ 2254.098 ,  2131.148 ,  2090.164 , ...,  2459.016 ,
               2254.098 ,  2295.082 ]]]])

  • flow_in
    (nodes, techs, carriers, timesteps)
    float64
    nan nan nan nan ... 0.0 0.0 0.0 0.0

    title :

    Carrier inflow

    description :

    The inflow to a technology per timestep, also known as the flow consumed (by `storage` technologies) or the flow sent (by `transmission` technologies) on a link.

    default :

    0

    unit :

    energy

    is_result :

    1

    array([[[[      nan,       nan,       nan, ...,       nan,       nan,
                    nan]],
    
            [[      nan,       nan,       nan, ...,       nan,       nan,
                    nan]],
    
            [[      nan,       nan,       nan, ...,       nan,       nan,
                    nan]],
    
            ...,
    
            [[   0.    ,    0.    ,    0.    , ...,    0.    ,    0.    ,
                 0.    ]],
    
            [[   0.    ,    0.    ,    0.    , ...,    0.    ,    0.    ,
                 0.    ]],
    
            [[2651.88  , 2507.2329, 2459.0165, ..., 2892.96  , 2651.88  ,
              2700.0965]]],
    
    ...
    
           [[[   0.    ,    0.    ,    0.    , ...,    0.    ,    0.    ,
                 0.    ]],
    
            [[      nan,       nan,       nan, ...,       nan,       nan,
                    nan]],
    
            [[      nan,       nan,       nan, ...,       nan,       nan,
                    nan]],
    
            ...,
    
            [[      nan,       nan,       nan, ...,       nan,       nan,
                    nan]],
    
            [[      nan,       nan,       nan, ...,       nan,       nan,
                    nan]],
    
            [[   0.    ,    0.    ,    0.    , ...,    0.    ,    0.    ,
                 0.    ]]]])

  • area_use
    (nodes, techs)
    float64
    nan nan nan nan ... nan nan nan nan

    title :

    Area utilisation

    description :

    The area in space utilised directly (e.g., solar PV panels) or indirectly (e.g., biofuel crops) by a technology.

    default :

    0

    unit :

    area

    is_result :

    1

    array([[        nan,         nan,         nan,         nan,         nan,
                    nan,         nan,         nan],
           [        nan,         nan, 130384.99  ,         nan,         nan,
                    nan,         nan,         nan],
           [        nan,         nan,      0.    ,         nan,         nan,
                    nan,         nan,         nan],
           [        nan,         nan,   8486.0609,         nan,         nan,
                    nan,         nan,         nan],
           [        nan,         nan,         nan,         nan,         nan,
                    nan,         nan,         nan]])

  • source_use
    (nodes, techs, timesteps)
    float64
    nan nan nan nan ... nan nan nan nan

    title :

    Source flow use

    description :

    The carrier flow consumed from outside the system boundaries by a `supply` technology.

    default :

    0

    unit :

    energy

    is_result :

    1

    array([[[      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            [55872.72 , 53789.346, 52379.345, ..., 50468.256, 46085.008,
             45669.062],
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            ...,
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan]],
    
           [[      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            [    0.   ,     0.   ,     0.   , ...,     0.   ,     0.   ,
                 0.   ],
    ...
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan]],
    
           [[      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            ...,
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan]]])

  • source_cap
    (nodes, techs)
    float64
    nan 6e+04 nan nan ... nan nan nan

    title :

    Source flow capacity

    description :

    The upper limit on a flow that can be consumed from outside the system boundaries by a `supply` technology in each timestep.

    default :

    0

    unit :

    power

    is_result :

    1

    array([[       nan, 60000.    ,        nan,        nan,        nan,
                   nan,        nan,        nan],
           [       nan,        nan, 67215.287 ,        nan,        nan,
                   nan,        nan,        nan],
           [       nan,        nan,     0.    ,        nan,        nan,
                   nan,        nan,        nan],
           [       nan,        nan,  2291.9577,        nan,        nan,
                   nan,        nan,        nan],
           [       nan,        nan,        nan,        nan,        nan,
                   nan,        nan,        nan]])

  • storage_cap
    (nodes, techs)
    float64
    nan nan nan nan ... nan nan nan nan

    title :

    Stored carrier capacity

    description :

    The upper limit on a carrier that can be stored by a technology in any timestep.

    default :

    0

    unit :

    energy

    is_result :

    1

    array([[        nan,         nan,         nan,         nan,         nan,
                    nan,         nan,         nan],
           [        nan,         nan, 244300.4   ,         nan,         nan,
                    nan,         nan,         nan],
           [        nan,         nan,      0.    ,         nan,         nan,
                    nan,         nan,         nan],
           [        nan,         nan,  25300.418 ,         nan,         nan,
                    nan,         nan,         nan],
           [  5239.2461,         nan,         nan,         nan,         nan,
                    nan,         nan,         nan]])

  • storage
    (nodes, techs, timesteps)
    float64
    nan nan nan nan ... nan nan nan nan

    title :

    Stored carrier

    description :

    The carrier stored by a `storage` technology in each timestep.

    default :

    0

    unit :

    energy

    is_result :

    1

    array([[[      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            ...,
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan]],
    
           [[      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            [    0.   ,     0.   ,     0.   , ..., 47357.277, 22262.562,
                 0.   ],
    ...
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan]],
    
           [[    0.   ,     0.   ,     0.   , ...,     0.   ,     0.   ,
                 0.   ],
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            ...,
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan],
            [      nan,       nan,       nan, ...,       nan,       nan,
                   nan]]])

  • unmet_demand
    (nodes, carriers, timesteps)
    float64
    0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0

    is_result :

    1

    array([[[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0.]],
    
           [[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0.]],
    
           [[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
    ...
             0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0.]],
    
           [[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0.]],
    
           [[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
             0., 0., 0., 0., 0., 0., 0., 0.]]])

  • flow_out_inc_eff
    (nodes, techs, carriers, timesteps)
    float64
    nan nan nan ... 2.652e+03 2.7e+03

    title :

    Carrier outflow including losses

    description :

    Outflows after taking efficiency losses into account.

    default :

    0

    is_result :

    1

    array([[[[           nan,            nan,            nan, ...,
                         nan,            nan,            nan]],
    
            [[55872.72      , 53789.346     , 52379.344     , ...,
              50468.256     , 46085.008     , 45669.062     ]],
    
            [[           nan,            nan,            nan, ...,
                         nan,            nan,            nan]],
    
            ...,
    
            [[    0.        ,     0.        ,     0.        , ...,
                  0.        ,     0.        ,     0.        ]],
    
            [[    0.        ,     0.        ,     0.        , ...,
                  0.        ,     0.        ,     0.        ]],
    
            [[    0.        ,     0.        ,     0.        , ...,
                  0.        ,     0.        ,     0.        ]]],
    
    ...
    
           [[[    0.        ,     0.        ,     0.        , ...,
                  0.        ,     0.        ,     0.        ]],
    
            [[           nan,            nan,            nan, ...,
                         nan,            nan,            nan]],
    
            [[           nan,            nan,            nan, ...,
                         nan,            nan,            nan]],
    
            ...,
    
            [[           nan,            nan,            nan, ...,
                         nan,            nan,            nan]],
    
            [[           nan,            nan,            nan, ...,
                         nan,            nan,            nan]],
    
            [[ 2651.88      ,  2507.23294118,  2459.01647059, ...,
               2892.96      ,  2651.88      ,  2700.09647059]]]])

  • flow_in_inc_eff
    (nodes, techs, carriers, timesteps)
    float64
    nan nan nan nan ... 0.0 0.0 0.0 0.0

    title :

    Carrier inflow including losses

    description :

    Inflows after taking efficiency losses into account.

    default :

    0

    is_result :

    1

    array([[[[      nan,       nan,       nan, ...,       nan,       nan,
                    nan]],
    
            [[      nan,       nan,       nan, ...,       nan,       nan,
                    nan]],
    
            [[      nan,       nan,       nan, ...,       nan,       nan,
                    nan]],
    
            ...,
    
            [[   0.    ,    0.    ,    0.    , ...,    0.    ,    0.    ,
                 0.    ]],
    
            [[   0.    ,    0.    ,    0.    , ...,    0.    ,    0.    ,
                 0.    ]],
    
            [[2651.88  , 2507.2329, 2459.0165, ..., 2892.96  , 2651.88  ,
              2700.0965]]],
    
    ...
    
           [[[   0.    ,    0.    ,    0.    , ...,    0.    ,    0.    ,
                 0.    ]],
    
            [[      nan,       nan,       nan, ...,       nan,       nan,
                    nan]],
    
            [[      nan,       nan,       nan, ...,       nan,       nan,
                    nan]],
    
            ...,
    
            [[      nan,       nan,       nan, ...,       nan,       nan,
                    nan]],
    
            [[      nan,       nan,       nan, ...,       nan,       nan,
                    nan]],
    
            [[   0.    ,    0.    ,    0.    , ...,    0.    ,    0.    ,
                 0.    ]]]])

  • cost_operation_variable
    (nodes, techs, costs, timesteps)
    float64
    nan nan nan ... 4.918 4.508 4.59

    title :

    Variable operating costs

    description :

    The operating costs per timestep of a technology.

    default :

    0

    unit :

    cost_per_time

    is_result :

    1

    array([[[[         nan,          nan,          nan, ...,          nan,
                       nan,          nan]],
    
            [[1117.4544   , 1075.78692  , 1047.5869   , ..., 1009.36512  ,
               921.70016  ,  913.38124  ]],
    
            [[         nan,          nan,          nan, ...,          nan,
                       nan,          nan]],
    
            ...,
    
            [[         nan,          nan,          nan, ...,          nan,
                       nan,          nan]],
    
            [[         nan,          nan,          nan, ...,          nan,
                       nan,          nan]],
    
            [[   0.       ,    0.       ,    0.       , ...,    0.       ,
                 0.       ,    0.       ]]],
    
    ...
    
           [[[         nan,          nan,          nan, ...,          nan,
                       nan,          nan]],
    
            [[         nan,          nan,          nan, ...,          nan,
                       nan,          nan]],
    
            [[         nan,          nan,          nan, ...,          nan,
                       nan,          nan]],
    
            ...,
    
            [[         nan,          nan,          nan, ...,          nan,
                       nan,          nan]],
    
            [[         nan,          nan,          nan, ...,          nan,
                       nan,          nan]],
    
            [[   4.508196 ,    4.262296 ,    4.180328 , ...,    4.918032 ,
                 4.508196 ,    4.590164 ]]]])

  • cost_investment_flow_cap
    (nodes, techs, carriers, costs)
    float64
    nan 2.25e+07 nan ... nan 3.23e+05

    title :

    Flow capacity investment costs

    description :

    The investment costs associated with the nominal/rated capacity of a technology.

    default :

    0

    is_result :

    1

    array([[[[        nan]],
    
            [[22500000.  ]],
    
            [[        nan]],
    
            [[        nan]],
    
            [[        nan]],
    
            [[        nan]],
    
            [[        nan]],
    
            [[  323047.29]]],
    
    
           [[[        nan]],
    
            [[        nan]],
    ...
            [[        nan]],
    
            [[        nan]]],
    
    
           [[[        nan]],
    
            [[        nan]],
    
            [[        nan]],
    
            [[        nan]],
    
            [[        nan]],
    
            [[        nan]],
    
            [[        nan]],
    
            [[  323047.29]]]])

  • cost_investment_storage_cap
    (nodes, techs, costs)
    float64
    nan nan nan nan ... nan nan nan nan

    title :

    Storage capacity investment costs

    description :

    The investment costs associated with the storage capacity of a technology.

    default :

    0

    is_result :

    1

    array([[[        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan]],
    
           [[        nan],
            [        nan],
            [12215020.  ],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan]],
    
           [[        nan],
            [        nan],
    ...
            [        nan],
            [        nan]],
    
           [[        nan],
            [        nan],
            [ 1265020.9 ],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan]],
    
           [[ 1047849.22],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan]]])

  • cost_investment_source_cap
    (nodes, techs, costs)
    float64
    nan nan nan nan ... nan nan nan nan

    title :

    Source flow capacity investment costs

    description :

    The investment costs associated with the source consumption capacity of a technology.

    default :

    0

    is_result :

    1

    array([[[        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan]],
    
           [[        nan],
            [        nan],
            [13443057.4 ],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan]],
    
           [[        nan],
            [        nan],
    ...
            [        nan],
            [        nan]],
    
           [[        nan],
            [        nan],
            [  458391.54],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan]],
    
           [[        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan]]])

  • cost_investment_area_use
    (nodes, techs, costs)
    float64
    nan nan nan nan ... nan nan nan nan

    title :

    Area utilisation investment costs

    description :

    The investment costs associated with the area used by a technology.

    default :

    0

    is_result :

    1

    array([[[        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan]],
    
           [[        nan],
            [        nan],
            [26076998.  ],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan]],
    
           [[        nan],
            [        nan],
    ...
            [        nan],
            [        nan]],
    
           [[        nan],
            [        nan],
            [ 1697212.18],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan]],
    
           [[        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan]]])

  • cost_investment
    (nodes, techs, costs)
    float64
    nan 2.25e+07 nan ... nan 3.23e+05

    title :

    Total investment costs

    description :

    The installation costs of a technology, including those linked to the nameplate capacity, land use, storage size, and binary/integer unit purchase.

    default :

    0

    unit :

    cost

    is_result :

    1

    array([[[        nan],
            [22500000.  ],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [  323047.29]],
    
           [[        nan],
            [        nan],
            [61735075.4 ],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan]],
    
           [[        nan],
            [        nan],
    ...
            [        nan],
            [        nan]],
    
           [[        nan],
            [        nan],
            [ 5954386.72],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan]],
    
           [[ 1047849.22],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [        nan],
            [  323047.29]]])

  • cost_investment_annualised
    (nodes, techs, costs)
    float64
    nan 3.396e+04 nan ... nan nan 487.5

    title :

    Equivalent annual investment costs

    description :

    An annuity factor has been applied to scale lifetime investment costs to annual values that can be directly compared to operation costs. If the modeling period is not equal to one full year, this will be scaled accordingly.

    default :

    0

    unit :

    cost

    is_result :

    1

    array([[[           nan],
            [33955.91266131],
            [           nan],
            [           nan],
            [           nan],
            [           nan],
            [           nan],
            [  487.52735843]],
    
           [[           nan],
            [           nan],
            [93167.5923743 ],
            [           nan],
            [           nan],
            [           nan],
            [           nan],
            [           nan]],
    
           [[           nan],
            [           nan],
    ...
            [           nan],
            [           nan]],
    
           [[           nan],
            [           nan],
            [ 8986.07268515],
            [           nan],
            [           nan],
            [           nan],
            [           nan],
            [           nan]],
    
           [[ 1581.36340429],
            [           nan],
            [           nan],
            [           nan],
            [           nan],
            [           nan],
            [           nan],
            [  487.52735843]]])

  • cost
    (nodes, techs, costs)
    float64
    nan 1.703e+05 nan ... nan 1.067e+03

    title :

    Total costs

    description :

    The total annualised costs of a technology, including installation and operation costs.

    default :

    0

    unit :

    cost

    is_result :

    1

    array([[[            nan],
            [170306.86648131],
            [            nan],
            [            nan],
            [            nan],
            [            nan],
            [            nan],
            [   487.52735843]],
    
           [[            nan],
            [            nan],
            [ 94592.4283661 ],
            [            nan],
            [            nan],
            [            nan],
            [            nan],
            [            nan]],
    
           [[            nan],
            [            nan],
    ...
            [            nan],
            [            nan]],
    
           [[            nan],
            [            nan],
            [  9013.12138729],
            [            nan],
            [            nan],
            [            nan],
            [            nan],
            [            nan]],
    
           [[  1581.36340429],
            [            nan],
            [            nan],
            [            nan],
            [            nan],
            [            nan],
            [            nan],
            [  1067.17246823]]])

  • capacity_factor
    (nodes, techs, carriers, timesteps)
    float64
    0.0 0.0 0.0 ... 0.6978 0.7104

    is_result :

    1

    array([[[[0.        , 0.        , 0.        , ..., 0.        ,
              0.        , 0.        ]],
    
            [[0.931212  , 0.8964891 , 0.87298907, ..., 0.8411376 ,
              0.76808347, 0.76115103]],
    
            [[0.        , 0.        , 0.        , ..., 0.        ,
              0.        , 0.        ]],
    
            ...,
    
            [[0.        , 0.        , 0.        , ..., 0.        ,
              0.        , 0.        ]],
    
            [[0.        , 0.        , 0.        , ..., 0.        ,
              0.        , 0.        ]],
    
            [[0.        , 0.        , 0.        , ..., 0.        ,
              0.        , 0.        ]]],
    
    ...
    
           [[[0.        , 0.        , 0.        , ..., 0.        ,
              0.        , 0.        ]],
    
            [[0.        , 0.        , 0.        , ..., 0.        ,
              0.        , 0.        ]],
    
            [[0.        , 0.        , 0.        , ..., 0.        ,
              0.        , 0.        ]],
    
            ...,
    
            [[0.        , 0.        , 0.        , ..., 0.        ,
              0.        , 0.        ]],
    
            [[0.        , 0.        , 0.        , ..., 0.        ,
              0.        , 0.        ]],
    
            [[0.697761  , 0.65970156, 0.64701487, ..., 0.76119382,
              0.697761  , 0.71044769]]]])

  • systemwide_capacity_factor
    (techs, carriers)
    float64
    0.1317 0.9469 ... 0.02471 0.3738

    is_result :

    1

    array([[0.13173452],
           [0.94688162],
           [0.48265792],
           [0.        ],
           [0.32982315],
           [0.        ],
           [0.02471137],
           [0.37381338]])

  • systemwide_levelised_cost
    (carriers, techs, costs)
    float64
    0.1 0.04996 0.1427 ... nan 0.005364

    is_result :

    1

    array([[[0.10003474],
            [0.04996133],
            [0.1427187 ],
            [       nan],
            [       nan],
            [       nan],
            [       nan],
            [0.00536432]]])

  • total_levelised_cost
    (carriers, costs)
    float64
    0.06701

    is_result :

    1

    array([[0.06700544]])

• Indexes: (5)
  • techs
    PandasIndex

    PandasIndex(Index(['battery', 'ccgt', 'csp', 'demand_power', 'region1_to_region1_1',
           'region1_to_region1_2', 'region1_to_region1_3', 'region1_to_region2'],
          dtype='object', name='techs'))

  • carriers
    PandasIndex

    PandasIndex(Index(['power'], dtype='object', name='carriers'))

  • nodes
    PandasIndex

    PandasIndex(Index(['region1', 'region1_1', 'region1_2', 'region1_3', 'region2'], dtype='object', name='nodes'))

  • timesteps
    PandasIndex

    PandasIndex(DatetimeIndex(['2005-01-01 00:00:00', '2005-01-01 01:00:00',
                   '2005-01-01 02:00:00', '2005-01-01 03:00:00',
                   '2005-01-01 04:00:00', '2005-01-01 05:00:00',
                   '2005-01-01 06:00:00', '2005-01-01 07:00:00',
                   '2005-01-01 08:00:00', '2005-01-01 09:00:00',
                   ...
                   '2005-01-05 14:00:00', '2005-01-05 15:00:00',
                   '2005-01-05 16:00:00', '2005-01-05 17:00:00',
                   '2005-01-05 18:00:00', '2005-01-05 19:00:00',
                   '2005-01-05 20:00:00', '2005-01-05 21:00:00',
                   '2005-01-05 22:00:00', '2005-01-05 23:00:00'],
                  dtype='datetime64[ns]', name='timesteps', length=120, freq=None))

  • costs
    PandasIndex

    PandasIndex(Index(['monetary'], dtype='object', name='costs'))

• Attributes: (13)

  termination_condition :

  optimal

  calliope_version_defined :

  0.7.0

  calliope_version_initialised :

  0.7.0.dev5

  applied_overrides :

  scenario :

  None

  defaults :

  {'bigM': 1000000000.0, 'objective_cost_weights': 1, 'color': nan, 'name': nan, 'cap_method': 'continuous', 'integer_dispatch': False, 'include_storage': False, 'force_async_flow': False, 'flow_cap_per_storage_cap_min': 0, 'flow_cap_per_storage_cap_max': inf, 'flow_cap': inf, 'flow_cap_max': inf, 'flow_cap_max_systemwide': inf, 'flow_cap_min': 0, 'flow_cap_min_systemwide': 0, 'flow_out_min_relative': 0, 'flow_cap_per_unit': nan, 'flow_in_eff': 1.0, 'flow_out_eff': 1.0, 'flow_out_parasitic_eff': 1.0, 'flow_ramping': 1.0, 'export_max': inf, 'lifetime': inf, 'area_use': inf, 'area_use_max': inf, 'area_use_min': 0, 'area_use_per_flow_cap': nan, 'storage_cap': inf, 'storage_cap_max': inf, 'storage_cap_min': 0, 'storage_cap_per_unit': nan, 'storage_discharge_depth': 0, 'storage_initial': 0, 'storage_loss': 0, 'cyclic_storage': True, 'purchased_units_min_systemwide': 0, 'purchased_units_max_systemwide': inf, 'purchased_units': inf, 'purchased_units_min': 0, 'purchased_units_max': inf, 'sink_unit': 'absolute', 'sink_use_min': 0, 'sink_use_max': inf, 'sink_use_equals': nan, 'source_unit': 'absolute', 'source_cap_equals_flow_cap': False, 'source_eff': 1.0, 'source_use_min': 0, 'source_use_max': inf, 'source_use_equals': nan, 'source_cap': inf, 'source_cap_max': inf, 'source_cap_min': 0, 'one_way': False, 'distance': 1.0, 'flow_in_eff_per_distance': 1.0, 'flow_out_eff_per_distance': 1.0, 'cost_flow_cap_per_distance': 0, 'cost_purchase_per_distance': 0, 'cost_flow_cap': 0, 'cost_export': 0, 'cost_interest_rate': 0, 'cost_om_annual': 0, 'cost_om_annual_investment_fraction': 0, 'cost_flow_in': 0, 'cost_flow_out': 0, 'cost_purchase': 0, 'cost_area_use': 0, 'cost_source_cap': 0, 'cost_storage_cap': 0, 'cost_depreciation_rate': 1, 'available_area': inf}

  allow_operate_mode :

  1

  name :

  National-scale example model

  timestamp_model_creation :

  1741978636.499071

  timestamp_build_start :

  1741978638.386217

  timestamp_build_complete :

  1741978643.435761

  timestamp_solve_start :

  1741978643.437133

  timestamp_solve_complete :

  1741978643.899826

We can sum electricity output over all locations and turn the result into a pandas DataFrame.

Note: electricity output of transmission technologies (e.g., region1_to_region2) is the import of electricity at nodes.

In [8]:

df_electricity = model.results.flow_out.sel(carriers="power").sum("nodes").to_series()
df_electricity.head()

df_electricity = model.results.flow_out.sel(carriers="power").sum("nodes").to_series() df_electricity.head()

Out[8]:

techs    timesteps          
battery  2005-01-01 00:00:00    0.0
         2005-01-01 01:00:00    0.0
         2005-01-01 02:00:00    0.0
         2005-01-01 03:00:00    0.0
         2005-01-01 04:00:00    0.0
Name: flow_out, dtype: float64

We can also view total costs associated with each of our technologies at each of our nodes:

In [9]:

costs = model.results.cost.to_series().dropna()
costs.head()

costs = model.results.cost.to_series().dropna() costs.head()

Out[9]:

nodes      techs               costs   
region1    ccgt                monetary    170306.866481
           region1_to_region2  monetary       487.527358
region1_1  csp                 monetary     94592.428366
region1_2  csp                 monetary         0.000000
region1_3  csp                 monetary      9013.121387
Name: cost, dtype: float64

We can also examine levelized costs for each location and technology, which is calculated in a post-processing step:

In [10]:

lcoes = model.results.systemwide_levelised_cost.to_series().dropna()
lcoes

lcoes = model.results.systemwide_levelised_cost.to_series().dropna() lcoes

Out[10]:

carriers  techs               costs   
power     battery             monetary    0.100035
          ccgt                monetary    0.049961
          csp                 monetary    0.142719
          region1_to_region2  monetary    0.005364
Name: systemwide_levelised_cost, dtype: float64

Visualising results¶

We can use plotly to quickly examine our results. These are just some examples of how to visualise Calliope data.

In [11]:

# We set the color mapping to use in all our plots by extracting the colors defined in the technology definitions of our model.
colors = model.inputs.color.to_series().to_dict()

# We set the color mapping to use in all our plots by extracting the colors defined in the technology definitions of our model. colors = model.inputs.color.to_series().to_dict()

Plotting flows¶

We do this by combinging in- and out-flows and separating demand from other technologies. First, we look at the aggregated result across all nodes, then we look at each node separately.

In [12]:

df_electricity = (
    (model.results.flow_out.fillna(0) - model.results.flow_in.fillna(0))
    .sel(carriers="power")
    .sum("nodes")
    .to_series()
    .where(lambda x: x != 0)
    .dropna()
    .to_frame("Flow in/out (kWh)")
    .reset_index()
)
df_electricity_demand = df_electricity[df_electricity.techs == "demand_power"]
df_electricity_other = df_electricity[df_electricity.techs != "demand_power"]

print(df_electricity.head())

fig1 = px.bar(
    df_electricity_other,
    x="timesteps",
    y="Flow in/out (kWh)",
    color="techs",
    color_discrete_map=colors,
)
fig1.add_scatter(
    x=df_electricity_demand.timesteps,
    y=-1 * df_electricity_demand["Flow in/out (kWh)"],
    marker_color="black",
    name="demand",
)

df_electricity = ( (model.results.flow_out.fillna(0) - model.results.flow_in.fillna(0)) .sel(carriers="power") .sum("nodes") .to_series() .where(lambda x: x != 0) .dropna() .to_frame("Flow in/out (kWh)") .reset_index() ) df_electricity_demand = df_electricity[df_electricity.techs == "demand_power"] df_electricity_other = df_electricity[df_electricity.techs != "demand_power"] print(df_electricity.head()) fig1 = px.bar( df_electricity_other, x="timesteps", y="Flow in/out (kWh)", color="techs", color_discrete_map=colors, ) fig1.add_scatter( x=df_electricity_demand.timesteps, y=-1 * df_electricity_demand["Flow in/out (kWh)"], marker_color="black", name="demand", )

     techs           timesteps  Flow in/out (kWh)
0  battery 2005-01-01 14:00:00         -76.402643
1  battery 2005-01-01 15:00:00        -286.886000
2  battery 2005-01-01 16:00:00         163.934000
3  battery 2005-01-01 17:00:00         122.950000
4  battery 2005-01-01 18:00:00          40.984000