spelling corrections

This commit is contained in:
Fabian Neumann 2023-03-06 09:23:30 +01:00
parent 7f7ad55c31
commit 2f39280f14
3 changed files with 3 additions and 3 deletions

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@ -495,7 +495,7 @@ The production of glass is assumed to be fully electrified based on the current
**Non-ferrous Metals**
The non-ferrous metal subsector includes the manufacturing of base metals (aluminium, copper, lead, zink), precious metals (gold, silver), and technology metals (molybdenum, cobalt, silicon).
The non-ferrous metal subsector includes the manufacturing of base metals (aluminium, copper, lead, zinc), precious metals (gold, silver), and technology metals (molybdenum, cobalt, silicon).
The manufacturing of aluminium accounts for more than half of the final energy consumption of this subsector. Two alternative processing routes are used today to manufacture aluminium in Europe. The primary route represents 40% of the aluminium pro- duction, while the secondary route represents the remaining 60%.

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@ -586,7 +586,7 @@ def map_to_lstrength(l_strength, df):
def calculate_heat_losses(u_values, data_tabula, l_strength, temperature_factor):
"""
calculates total annual heat losses Q_ht for different insulation thicknesses
(l_strength), depening on current insulation state (u_values), standard
(l_strength), depending on current insulation state (u_values), standard
building topologies and air ventilation from TABULA (data_tabula) and
the accumulated difference between internal and external temperature
during the heating season (temperature_factor).

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@ -2521,7 +2521,7 @@ def add_waste_heat(n):
n.links.loc[urban_central + " Fischer-Tropsch", "bus3"] = urban_central + " urban central heat"
n.links.loc[urban_central + " Fischer-Tropsch", "efficiency3"] = 0.95 - n.links.loc[urban_central + " Fischer-Tropsch", "efficiency"]
# TODO integrate useable waste heat efficiency into technology-data from DEA
# TODO integrate usable waste heat efficiency into technology-data from DEA
if options.get('use_electrolysis_waste_heat', False):
n.links.loc[urban_central + " H2 Electrolysis", "bus2"] = urban_central + " urban central heat"
n.links.loc[urban_central + " H2 Electrolysis", "efficiency2"] = 0.84 - n.links.loc[urban_central + " H2 Electrolysis", "efficiency"]