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PyPSA · Feb 16, 2024 · ac67edb · ac67edb
2 parents c2d9c7b + bdfc3d0
commit ac67edb
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Showing 4 changed files with 10 additions and 6 deletions.
diff --git a/config.yaml b/config.yaml
@@ -1,4 +1,4 @@
-version: 0.6.2
+version: 0.7.0
 
 # considered years for output data
 years : [2020, 2025, 2030, 2035, 2040, 2045, 2050]

diff --git a/docs/conf.py b/docs/conf.py
@@ -73,9 +73,9 @@
 # built documents.
 #
 # The short X.Y version.
-version = u'0.6'
+version = u'0.7'
 # The full version, including alpha/beta/rc tags.
-release = u'0.6.2'
+release = u'0.7.0'
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.

diff --git a/docs/release_notes.rst b/docs/release_notes.rst
@@ -2,8 +2,11 @@
 Release Notes
 ##########################################
 
-Upcoming Release
-================
+.. Upcoming Release
+.. ================
+
+Technology-Data 0.7.0 (7 February 2024)
+=======================================
 
 * Updated to latest release of DEA renewable fuels (released January 2024). With the following changes
   * The following technologies have updated assumptions: ['BioSNG', 'BtL', 'Fischer-Tropsch', 'Haber-Bosch', 'air separation unit', 'biogas', 'biogas CC', 'biogas plus hydrogen', 'biogas upgrading', 'biomass-to-methanol', 'electrobiofuels', 'electrolysis', 'methanolisation']

diff --git a/scripts/compile_cost_assumptions.py b/scripts/compile_cost_assumptions.py
@@ -1057,6 +1057,7 @@ def order_data(tech_data):
         # ----- efficiencies ------
         efficiency = df[(df.index.str.contains("efficiency") |
                          (df.index.str.contains("Hydrogen output, at LHV"))|
+                         (df.index.str.contains("Hydrogen Output"))|
                          (df.index.str.contains("FT Liquids Output, MWh/MWh Total Input"))|
                          (df.index.str.contains("Methanol Output"))|
                          (df.index.str.contains("District heat  Output"))|
@@ -1090,7 +1091,7 @@ def order_data(tech_data):
             efficiency_heat = efficiency[with_heat_recovery].copy()
             efficiency_heat["parameter"] = "efficiency-heat"
             clean_df[tech] = pd.concat([clean_df[tech], efficiency_heat])
-            efficiency_h2 = efficiency[efficiency.index.str.contains("Hydrogen")].copy()
+            efficiency_h2 = efficiency[efficiency.index.str.contains("Hydrogen Output")].copy()
             efficiency_h2["parameter"] = "efficiency"
             clean_df[tech] = pd.concat([clean_df[tech], efficiency_h2])