Calibration run 2023/2024 #45
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Thanks for this PR @virio-andreyana ! I have made a few comments in the code. As we discussed, I have in mind a scaling problem with the generated graphs. I can't suggest a source for the bug based on the code in the PR.
| # 0.63 * 0.6 = 0.378 | ||
| electricity: | ||
| max_hours: |
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I don't think it makes sense to include this in the scenario
config/scenarios.form.yaml
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| onwind: | ||
| cutout: europe-2023-sarah3-era5 | ||
| #correction_factor: 0.93 |
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Correction factor is used for onwind in PyPSA-Ariadne
| district_heating: | ||
| progress: | ||
| 2023: 0.15 #Rough estimate. 70M/448M population uses district heating https://iifiir.org/en/news/state-of-play-of-district-heating-and-cooling-in-europe |
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This may be reduced a bit, using PyPSA-ariadne
| @@ -58,23 +61,39 @@ | |||
| colors["Offshore Wind"] = colors["Offshore Wind (AC)"] | |||
| colors["Gas"] = colors["Combined-Cycle Gas"] | |||
| colors["Hydro"] = colors["Reservoir & Dam"] | |||
| colors["geothermal"] = '#ba91b1' | |||
| colors["biomass"] = '#baa741' | |||
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Would be better to have them in the configuration file
| @@ -2170,7 +2170,7 @@ def add_fuel_cell_cars(n, p_set, fuel_cell_share, temperature): | |||
| suffix=" land transport fuel cell", | |||
| bus=spatial.h2.nodes, | |||
| carrier="land transport fuel cell", | |||
| p_set=profile, | |||
| p_set=profile.loc[n.snapshots], | |||
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Sometimes the snapshots and the profile data are not aligned. If you looked at def add_EVs() they did this snapshot filter already, so its just applying to other transport technologies
rules/validate.smk
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| @@ -11,6 +11,16 @@ CROSS_BORDER_PLOTS = ["trade_time_series", "cross_border_bar"] | |||
| PRICES_PLOTS = ["price_bar", "price_line"] | |||
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| if config["foresight"] == "myopic" or config["foresight"] == "overnight": | |||
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| if config["foresight"] == "myopic" or config["foresight"] == "overnight": | |
| if config["foresight"] in ["myopic", "overnight"]: |
| @@ -207,9 +207,9 @@ def approximate_missing_eia_stats(eia_stats, runoff_fn, countries): | |||
| norm_year = config_hydro.get("eia_norm_year") | |||
| missing_years = contained_years.difference(eia_stats.index) | |||
| if norm_year: | |||
| eia_stats.loc[contained_years] = eia_stats.loc[norm_year] | |||
| eia_stats.loc[contained_years[0]] = eia_stats.loc[norm_year] | |||
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Ideally this should not have to be done. but because 2023 is not within the existing EIA hydro statistics, it keeps getting error unless I do this.
Drawbacks: Not being able to model longer than 1 year. Suggestion is very appreciated!
config/scenarios.form.yaml
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| H2_retrofit: true | ||
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| main-calibration-run: |
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I would expect more changes in term of techs : no dac, no DSM for EV, no V2G, no TES, no SMR CC
…SO-E load data in electricity demand preparations, missing cost years are replaced with the closest available year
…e_dev Update calibrated run branch with the recent addition in form_energy_storage_dev
Changes proposed in this Pull Request
The validation automatically compares historical data and the optimized model of:
The challenge now is, can PyPSA-EUR run for the year 2023?