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 Microgrids.X 
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*Operational & economic simulation of Microgrid projects*

.. |MG.X icon| image:: images/Microgrids-X-icon.svg
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   :alt: Microgrid.X logo icon

.. image:: images/Microgrids-X.svg
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   :alt: Microgrid.X logo

Project overview
================

.. figure:: images/microgrid_sizing.svg
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   :alt: Microgrid sizing illustrated with a block and power flow diagram of the Microgrid (with storage, generator, wind, solar and load)

Microgrids.X is a collection of packages for the **operational & economic simulation of Microgrid projects**. Based on this microgrid assessement model, an optimization problem can be built to find the most suitable microgrid sizing.

Microgrids.X packages are available open source in the following languages:

* Julia: `Microgrids.jl`_ (yields the fastest simulation performance, by far)
* Python: `Microgrids.py`_ 
* Matlab/Octave: `Microgrids.m`_ 

All these packages aim at providing the same features using a **common architecture and naming scheme**.
Using a native implementation of the same model in three different languages
allows us to better serve the users' preferences.
This can be particularly useful in a teaching context.


Features
========

* Microgrid composed of 1 load, 1 storage device, 1 dispatchable generator and any number of non dispatchable sources (wind, solar)
* **Operational simulation** over a year with a short time step (typically: 1 hour)

    * Energy dispatch with a simple Load Following strategy (load is fed in priority with non dispatchable sources, then the battery, and the dispatchable generator is used in last recourse when the storage is empty)

* **Economic computation** over the project lifecycle (for example: 25 years) by extrapolating the operational results (assuming each year of the project is similar).
  The Economic model takes into account:

    * Financial discount rate
    * Replacement of components based on the their operation-dependent lifetime (e.g. actual operating hours of the generator or number of cycles of the battery)
    * Salvage value of components at the end of the project



Scientific publications
-----------------------

More background (plus extra things on Automatic Differentiation) can be found in:

E. de Godoy Antunes, P. Haessig, C. Wang, and R. Chouhy Leborgne, “Optimal Microgrid Sizing using Gradient-based Algorithms with Automatic Differentiation,” *accepted to ISGT Europe 2022, Novi Sad, Serbia*, 2022. https://hal.archives-ouvertes.fr/hal-03370004


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.. _Microgrids.jl: https://github.com/Microgrids-X/Microgrids.jl
.. _Microgrids.py: https://github.com/Microgrids-X/Microgrids.py
.. _Microgrids.m: https://github.com/Microgrids-X/Microgrids.m