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Fix myopic optimization for networks with geothermal district heating #1453
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Model Metrics Comparing |
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Thanks for spotting this! Just had minor comments.
Also, could you update the release notes and show a quick before/after comparison of COPs to make sure everything is working as expected? (e.g. a cooked-down version of the last plot in this PR: #1290 )
@@ -244,6 +244,7 @@ def update_heat_pump_efficiency(n: pypsa.Network, n_p: pypsa.Network, year: int) | |||
# get names of heat pumps in previous iteration | |||
heat_pump_idx_previous_iteration = n_p.links.index[ | |||
n_p.links.index.str.contains("heat pump") | |||
& n_p.links.index.str[:-4].isin(n.links_t.efficiency.columns.str[:-4]) |
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Hmm, I would need an additional comment here to follow here :)
for heat_pump_source in snakemake.params.sector["heat_pump_sources"][ | ||
"urban central" | ||
]: | ||
nodal_heat_name_tech[("urban central", f"{heat_pump_source} heat pump")] = 0.0 |
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If you have the time: could you add a comment or two to the function and convert the function header to a docstring?
Changes proposed in this Pull Request
Geothermal heat for district heating was implemented in #1359. However, it was not working for the myopic code. This PR includes two changes, that fix the issue:
build_existing_heating_distribution
.add_brownfield
. This adjustment had to be done, because some heat pumps initialized inprepare_sector_network
potentially disappear from theirlinks_t
dataframe if their efficiency equals zero (e.g. in Denmark where geothermal source temperatures can exceed district heating supply temperatures). This correction is done to account for the supply temperature dynamics in district heating and should be further adjusted as described in District heating efficiency gains applied to decentral heat pumps #1451 to depict efficiency gains for heat pumps due to technological learning.Checklist
envs/environment.yaml
.config/config.default.yaml
.doc/configtables/*.csv
.doc/data_sources.rst
.doc/release_notes.rst
is added.