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optihood
========
optihood provides a complete python-based framework to OPTImize the investment in alternative energy
technologies (heat pump, solar thermal, PV, etc.) as well as the operation of available energy resources (natural gas,
sun, grid electricity, etc.) at a neighbourHOOD-scale. It is designed to facilitate the researchers and energy planners
in optimizing an energy neighbourhood in terms of cost and/or environmental criteria. It enables the users to perform
both single-objective and multi-objective optimization and analysis. The energy model and it's associated parameters
can be defined easily using an excel file. Additionally, a variety of plotting methods are defined for easy and fast
result visualization.
The package was developed at the `SPF - Institute for Solar Technology `_ at the `OST - Eastern
Switzerland University of Applied Sciences `_ and `Haute Ecole d'Ingénierie et de Gestion du Canton Vaud `_.
.. image:: ./guide/resources/spf_logos.svg
:width: 500
:alt: spf_logos
.. image:: ./guide/resources/heig_logo.svg
:width: 200
:scale: 40 %
:alt: heig_logo
:align: right
Table of contents
=================
.. toctree::
:maxdepth: 2
guide/getting_started
guide/energy_system_component_models
guide/defining_an_energy_network
guide/optimizing_the_energy_network
guide/processing_results
guide/advanced_under_development_features
Code Reference
Indices and tables
==================
* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`
Developers
^^^^^^^^^^
- SPF Institute for Solar Technology, Rapperswil, Switzerland
- HEIG VD, Yverdon-les-Bains, Switzerland
Acknowledgements
^^^^^^^^^^^^^^^^
This framework was created in 2021 and made open-source in 2022. We would like to thank the Swiss Federal Office Of Energy
(SFOE) for the support and funding received in the projects OptimEase and SolHood which allowed us to spend efforts in
developing and sharing the code and becoming a part of the open-source community.