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Prepare v0.7 release in documentation
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KSchoenleber committed Jan 13, 2017
1 parent aec3631 commit 66d2201
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8 changes: 4 additions & 4 deletions doc/conf.py
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master_doc = 'index'

project = u'urbs'
copyright = u'2014-2016, tum-ens'
version = '0.5'
release = '0.5'
copyright = u'2014-2017, tum-ens'
version = '0.7'
release = '0.7'

exclude_patterns = ['_build']
#pygments_style = 'sphinx'
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epub_title = u'urbs'
epub_author = u'tum-ens'
epub_publisher = u'tum-ens'
epub_copyright = u'2014-2016, tum-ens'
epub_copyright = u'2014-2017, tum-ens'

epub_exclude_files = ['search.html']

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14 changes: 8 additions & 6 deletions doc/index.rst
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Expand Up @@ -9,8 +9,8 @@ urbs: A linear optimisation model for distributed energy systems
================================================================

:Maintainer: Johannes Dorfner, <[email protected]>
:Organization: `Institute for Renewable and Sustainable Energy Systems`_,
Technische Universität München
:Organization: `Chair of Renewable and Sustainable Energy Systems`_,
Technical University of Munich
:Version: |version|
:Date: |today|
:Copyright:
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Changes
-------

(Upcoming) Version 0.7
2017-01-13 Version 0.7
^^^^^^^^^^^^^^^^^^^^^^

* Plot function (and ``get_timeseries``) now support grouping of multiple sites
* Environmental commodity costs (e.g. emission taxes or other pollution externalities)
* Maintenance: Model file ``urbs.py`` split into subfiles in folder ``urbs``
* Feature: Usable area in site implemented as possible constraint
* Feature: Plot function (and ``get_timeseries``) now support grouping of multiple sites
* Feature: Environmental commodity costs (e.g. emission taxes or other pollution externalities)
* Bugfix: column *Overproduction* in report sheet did not respect DSM


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* Any solver supported by pyomo; suggestion: `GLPK`_

.. _glpk: https://www.gnu.org/software/glpk/
.. _Institute for Renewable and Sustainable Energy Systems: http://www.ens.ei.tum.de/
.. _Chair of Renewable and Sustainable Energy Systems: http://www.ens.ei.tum.de/
.. _matplotlib: http://matplotlib.org
.. _pandas: http://pandas.pydata.org
.. _pyomo: http://www.pyomo.org
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