hypatia-test

.. image:: https://raw.githubusercontent.com/SESAM-Polimi/MARIO/767d2c0e9e42ae0b6acf7c3a1cc379d7bcd367fa/doc/source/_static/images/polimi.svg :width: 200 :align: right

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Hypatia

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An Operation and Planning Energy System Modelling Framework

What is it

Hypatia is an open source modelling framework written in Python that provides a technology-rich basis for optimizing both the operation and planning mode of the energy systems in short-term and long-term time horizons. Hypatia is able to analyze various energy transition scnerios based on different policies such as coal phase out, carbon taxes, renewable incetives and other national and international pledges for the possible future energy systems.

Quickstart

There are different ways to install hypatia software on your machine. The fastest one is through pip:

In case that you are using pip, it is suggested to create a new environment to avoid conflicts of the other packages. To create a new environment, you should use Anaconda Prompt:

.. code-block:: bash

conda create -n hypatia python=3.8

If you create a new environment for hypatia, you need to activate the environment each time you want to use it, by writing the following line in Anaconda Prompt:

.. code-block:: bash

conda activate hypatia

After activating the environment, you can use pip to install hypatia as follow:

.. code-block:: bash

pip install hypatia

Most of the open source solvers that are supported by CVXPY (the optimization library used in Hypatia), will be installed automatically with the software. For the commercial solvers, you should follow the specific installation methods. When Hypatia is installed, you can strat to use the embedded examples as a quick start:

.. code-block:: python

from hypatia import load_example

# Loading the planning example
planning = load_example('Planning')

# Loading the Operation example
operation = load_example('Operation')

# See the configuration of systems
print(planning)
print(operation)

# see the description of systems
print(planning.description)
print(operation.description)

# Running models
planning.run(solver='glpk')

# Save the results
planning.to_csv(path= '../save/directory')

If you want to see the structure of inputs and how the examples are built, you can download the data files to a specific place in your machine:

.. code-block:: python

from hypatia import download_example

# Downloading the Planning example
download_example(example='Planning', destination_path='Where/To/Save')

Python module requirements

Some of the key packages that Hypatia relies on are:

#. Pandas <https://pandas.pydata.org/>_ #. Numpy <https://numpy.org/>_ #. Plotly <https://plotly.com/>_ #. Cvxpy <https://pypi.org/project/cvxpy/>_ (domain-specific language)

Hypatia supports different Open Source and Commercial solvers like:

• CBC <https://projects.coin-or.org/Cbc>_
• GLPK <https://www.gnu.org/software/glpk/>_
• OSQP <https://osqp.org/>_
• ECOS <https://www.embotech.com/ECOS>_
• CVXOPT <http://cvxopt.org/>_
• SCS <https://github.com/cvxgrp/scs>_
• CPLEX <https://www.ibm.com/products/category/business/commerce>_
• GUROBI <https://www.gurobi.com/>_

.. note::

• This project is under active development.

License

.. image:: https://img.shields.io/badge/License-Apache_2.0-blue.svg :target: https://www.apache.org/licenses/

This work is licensed under Apache 2.0 <https://www.apache.org/licenses/>_