.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/sustainability/plot_cumulative_co2.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        Click :ref:`here <sphx_glr_download_auto_examples_sustainability_plot_cumulative_co2.py>`
        to download the full example code

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_sustainability_plot_cumulative_co2.py:


==================================
Cumulative CO2 Production and Cost
==================================

Given the power consumption of a process unit and data regarding the emissions and cost factors, we can work out the total amount of
CO2 produced and the cost associated with that. Here is an example using the power used by a gas compressor at the Valhall platform.

.. GENERATED FROM PYTHON SOURCE LINES 9-68



.. image-sg:: /auto_examples/sustainability/images/sphx_glr_plot_cumulative_co2_001.png
   :alt: Compressor Power Output, Rate of CO2 Production, Cumulative Sum of CO2 Production, Cumulative Cost of CO2
   :srcset: /auto_examples/sustainability/images/sphx_glr_plot_cumulative_co2_001.png
   :class: sphx-glr-single-img





.. code-block:: default


    import os

    import matplotlib.pyplot as plt
    import pandas as pd

    from indsl.sustainability.co2_emissions_calculations import (
        cumulative_co2_cost,
        cumulative_co2_production,
        rate_of_emissions,
    )


    # Load and pre-process data
    base_path = os.path.dirname("")
    data = pd.read_csv(os.path.join(base_path, "../../datasets/data/compressor_power_output.csv"), index_col=0)
    data.index = pd.to_datetime(data.index)
    power = data[data.columns[0]].resample("1H").mean().ffill()  # Unit is in kW

    # Specify factors
    co2_cost_factor = 0.5  # NOK/kg CO2
    emissions_factor = 0.21  # kg CO2/kWh

    # Perform emissions calculations
    rate_co2_produced = rate_of_emissions(power, emissions_factor)
    co2_produced = cumulative_co2_production(rate_co2_produced)
    co2_cost = cumulative_co2_cost(power, co2_cost_factor=co2_cost_factor, emissions_factor=emissions_factor)


    # Plotting
    plt.subplots(2, 2, figsize=(10, 10))

    ax = plt.subplot(2, 2, 1)
    (power).plot(ax=ax)
    plt.ylabel("Power (kW)")
    plt.xlabel("Date")
    plt.title("Compressor Power Output")

    ax = plt.subplot(2, 2, 2)
    (rate_co2_produced).plot(ax=ax)
    plt.ylabel("CO2 Production Rate (kg CO2/hr)")
    plt.xlabel("Date")
    plt.title("Rate of CO2 Production")


    ax = plt.subplot(2, 2, 3)
    (co2_produced / 1000).plot(ax=ax)
    plt.ylabel("Mass CO2 Emitted (tonnes)")
    plt.xlabel("Date")
    plt.title("Cumulative Sum of CO2 Production")


    ax = plt.subplot(2, 2, 4)
    (co2_cost / 1e6).plot(ax=ax)
    plt.ylabel("Cost (MNOK)")
    plt.xlabel("Date")
    plt.title("Cumulative Cost of CO2")

    plt.show()


.. rst-class:: sphx-glr-timing

   **Total running time of the script:** ( 0 minutes  0.511 seconds)


.. _sphx_glr_download_auto_examples_sustainability_plot_cumulative_co2.py:


.. only :: html

 .. container:: sphx-glr-footer
    :class: sphx-glr-footer-example



  .. container:: sphx-glr-download sphx-glr-download-python

     :download:`Download Python source code: plot_cumulative_co2.py <plot_cumulative_co2.py>`



  .. container:: sphx-glr-download sphx-glr-download-jupyter

     :download:`Download Jupyter notebook: plot_cumulative_co2.ipynb <plot_cumulative_co2.ipynb>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_