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add compatibility with pyomo 5.7.0 (#172)

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* add compatibility with pyomo 5.7.0

* add release notes [skip travis]
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Fabian Neumann 2020-07-20 17:33:15 +02:00 committed by GitHub
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commit 8c5efb5252
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4 changed files with 4 additions and 3 deletions
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1
doc/release_notes.rst
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@ -13,6 +13,7 @@ Upcoming Release
* Added an option to alter the capital cost of carriers by a factor via ``carrier+factor`` in the ``{opts}`` wildcard. This can be useful for exploring uncertain cost parameters. Example: ``solar+0.5`` reduces the capital cost of solar to 50% of original values (`#167 <https://github.com/PyPSA/pypsa-eur/pull/167>`_). * Added an option to alter the capital cost of carriers by a factor via ``carrier+factor`` in the ``{opts}`` wildcard. This can be useful for exploring uncertain cost parameters. Example: ``solar+0.5`` reduces the capital cost of solar to 50% of original values (`#167 <https://github.com/PyPSA/pypsa-eur/pull/167>`_).
* Add compatibility for pyomo 5.7.0 in :mod:`cluster_network` and :mod:`simplify_network`.
PyPSA-Eur 0.2.0 (8th June 2020) PyPSA-Eur 0.2.0 (8th June 2020)
================================== ==================================

2
environment.docs.yaml
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@ -9,7 +9,7 @@ channels:
dependencies: dependencies:
#- python #- python
- pip - pip
- pypsa>=0.17 - pypsa>=0.17.1
- atlite=0.0.3 - atlite=0.0.3
# Dependencies of the workflow itself # Dependencies of the workflow itself

2
environment.yaml
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@ -12,7 +12,7 @@ dependencies:
- python - python
- pip - pip
- pypsa>=0.17 - pypsa>=0.17.1
- atlite=0.0.3 - atlite=0.0.3
# Dependencies of the workflow itself # Dependencies of the workflow itself

2
scripts/cluster_network.py
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@ -221,7 +221,7 @@ def distribute_clusters(n, n_clusters, focus_weights=None, solver_name=None):
opt = po.SolverFactory('ipopt') opt = po.SolverFactory('ipopt')
results = opt.solve(m) results = opt.solve(m)
assert results['Solver'][0]['Status'].key == 'ok', "Solver returned non-optimally: {}".format(results) assert results['Solver'][0]['Status'] == 'ok', "Solver returned non-optimally: {}".format(results)
return pd.Series(m.n.get_values(), index=L.index).astype(int) return pd.Series(m.n.get_values(), index=L.index).astype(int)