pypsa/technology-data

Compiles assumptions on energy system technologies (e.g. costs and efficiencies) for various years.

Energy System Technology Data

This script compiles assumptions on energy system technologies (such as costs, efficiencies, lifetimes, etc.) for chosen years (e.g. [2020, 2030, 2050]) from a variety of sources into CSV files to be read by energy system modelling software. The merged outputs have standardized cost years, technology names, units and source information. For further information about the structure and how to add new technologies, see the documentation.

The outputs are used in PyPSA-Eur and PyPSA-Eur-Sec.

Licence

Copyright 2019-2020 Marta Victoria (Aarhus University), Kun Zhu (Aarhus University), Elisabeth Zeyen (TUB), Tom Brown (TUB)

The code in scripts/ is released as free software under the GPLv3, see LICENSE.txt. However, different licenses and terms of use may apply to the various input data.

technology-data's Issues

Data validation

The techno-economical parameters of the different technologies are the main drivers of the PyPSA modeling.

As such, they should be easy to validate by energy experts with e.g. experience in building energy projects.
I structured the data from the PNNL storage database so that it would be easy to see which technologies PyPSA may select. This gives the opportunity to limit the data validation effort to a subset of technologies.

The database structure makes it difficult to do this for all the data, considering the different technology classes (storage (electricity, heat, ...) , generation, transport/transmission, ... ). An approach would be to use more meta-data that allows easy visualization of essential parameters across all technologies.

update offwind grid connecion costs (sea cable,...)

the assumed grid connection costs could be updated with the assumptions of DEA, p.9 in docu/eng_note_on_technology_costs_for_offshore_wind_turbines.pdf

[New tech] Gas holder / spherical gas storage tanks for H2, CH4,

Currently we only have methane and hydrogen storage tanks of different types, i.e. assuming cylinder based gas storage. Large scale storage options exist, such as gas holders for natural gas but also tanks for hydrogen (see here in the background of the image.

track versions of input files

Add version tag to input files

Not all names of input files contain the version information. This should be changed to keep better track of the information

electrolyser technology assumptions

the DEA assumptions for efficiency improvements until 2050 are very low and probably don't match with the large installed capacities and corresponding learning rates we see in our calculations. It would be interesting to include learning rates or check for another data source for the efficiencies.

Update electricity transmission costs

Summary

Paramter & unit	PyPSA-Eur	NEP 23	NEP 21	ACER 23 average	ACER 23 Q3	Vrana & Härtel (2023)	CIGRE (max)	CIGRE (min)	Pathway 2.0
AC overhead (€/MW/km)	442	1325-1384	736	371	481	-	250	130	-
AC underground (€/MW/km)	-	4711	3386	771	821	-	-	-	1200
AC submarine (€/MW/km)	-	-	-	1182	1488	-	-	-	7005
DC overhead (€/MW/km)	442	-	1000	371	481	-	330	180	-
DC underground (€/MW/km)	-	3300-3800	3250	771	821	870	-	-	3690
DC submarine (€/MW/km)	1008	-	-	653	741	1159	1900	1270	2140
DC inverter pair (€/kW)	166	-	600	150	193	-	316	180	-

NEP 2023

https://www.netzentwicklungsplan.de/sites/default/files/2023-03/230321_NEP_Kostenschaetzung_NEP2037_2045_V2023_1.Entwurf.pdf

auf 2x1.698 GW (2 circuits) = 3396 MW

AC-Freileitung:
380-kV HTLS-Parallelneubau (Doppelleitung, 2 Stromkreise) 4,7 Mio. EUR / km
380-kV Neubau in neuer Trasse (Doppelleitung, 2 Stromkreise) 4,5 Mio. EUR / km

1383.98 EUR/MW/km
1325.09 EUR/MW/km

AC-Erdkabel:
380-kV Neubau in neuer Trasse 16 Mio. EUR / km

4711.43 EUR/MW/km

DC-Erdkabel:
320-kV Neubau in neuer Trasse (1 GW ohne metallischen Rückleiter) 3,5 Mio. EUR / km
525-kV Neubau in neuer Trasse (2 GW mit metallischem Rückleiter) 7,6 Mio. EUR / km
525-kV Neubau in neuer Trasse (2 GW) 6,6 Mio. EUR / km

3500 EUR/MW/km
3800 EUR/MW/km
3300 EUR/MW/km

Assumptions for retrofit suggest similar cost of AC-Freileitung and DC-Freileitung.

Underground assumptions could also be used for submarine assumptions.

NEP 2021

https://www.netzentwicklungsplan.de/sites/default/files/2023-02/NEP_2035_2021_1_Entwurf_Kostenschaetzungen_0.pdf

AC-Freileitung:
380-kV-Neubau Doppelleitung 2,5 Mio. € / km Neubautrasse, Hochstrom

736 €/MW/km

AC-Erdkabel:
Teilverkabelung Neubau
380-kV-Doppelleitung 11,5 Mio. € / km inkl. Kabelübergangsanlage

3386 €/MW/km

DC-Freileitung:
Neubau DC-Freileitung 2,0 Mio. € / km Neubautrasse mit 2 Systemen mit je 2 GW

500 €/MW/km assuming 4GW

DC-Erdkabel:
Neubau DC-Erdkabel 6,5 Mio. € / km Neubautrasse mit 1 x 2 GW

3250 €/MW/km

DC-Konverterstation:
DC-Konverterstation 0,3 Mio. € / MW pro Konverterstation

ACER

https://www.acer.europa.eu/sites/default/files/documents/Publications/ACER_UIC_indicators_table.pdf

Overhead line (million EUR/km) 380-400 kV 2 circuits 1,261 / 1,635
Underground cable (million EUR/km) 300 - 500 kV 1 circuit 1,309 / 1,394
Submarine cable (million EUR/km) AC 2,007 / 2,527- assume 1 circuit?
Submarine cable (million EUR/km) DC 1,108 / 1,258 - assume 1 circuit?
HVDC converters (million EUR/kWh) 0,150 / 0,193 - unit should be MEUR/kW?

average

371.32 EUR/MW/km
770.90 EUR/MW/km
1181.98 EUR/MW/km
652.53 EUR/MW/km
150000 EUR/MW

Q3 values

481.44 EUR/MW/km
820.97 EUR/MW/km
1488.22 EUR/MW/km
740.87 EUR/MW/km
193000 EUR/MW

Langfristszenarien

https://www.langfristszenarien.de/enertile-explorer-wAssets/docs/Consentec-TUBER_BMWK_LFS3_Webinar_Netze_T45_final_v2.pdf

"Kostenansätze entsprechend ÜNB-Annahmen im NEP bzw. Erfahrungswerten Consentec"

TYNDP

TYNDP not published, at least nowhere to be found ?!

DEA

only has distribution level assumptions, no transmission level

Vrana / Härtel

https://pdf.sciencedirectassets.com/271091/1-s2.0-S0378779617X00072/1-s2.0-S0378779617302572/dx.doi.org/10.1016/j.epsr.2017.06.008

https://doi.org/10.1109/EEM58374.2023.10161832

OverHead Lines (OHL) are not included in the new cost
model, as only a few HVDC overhead lines are being built
or planned in Europe

Rating of 2.2 GW

submarine:

1.061 M€/GW/km
2.784 M€ assuming 2.2 GW and 100km length
0.248 M€/km / 2.2 GW

1061 €/MW/km + 112.72 €/MW/km + 12.65 €/MW/km = 1159.37 €/MW/km

underground

0.672 M€/GW/km
2.784 M€ assuming 2.2 GW and 100km length
0.408 M€/km / 2.2 GW

672 €/MW/km + 185.45 €/MW/km + + 12.65 €/MW/km = 870.1 €/MW/km

technology-data

HVAC overhead investment 442.1414 EUR/MW/km
HVDC overhead investment 442.1414 EUR/MW/km
HVDC submarine investment 1008.2934 EUR/MW/km
HVDC inverter pair investment 165803.0398 EUR/MW

Pathway 2.0 Techno-economic data

https://zenodo.org/records/10101328

CIGRE

(e-mail Strommarkttreffen)

https://groups.io/g/strommarkttreffen/message/5721

globaler Wertebereich

	Cost (M€)	DC OHL (M€/km/GW)	DC USC (M€/km/GW)	AC OHL (M€/km/GW)	AC/DC Converter (M€/GW for one SS)	AC/AC Back to Back SS (M€/GW for one SS)
Max	0.33	1.90	0.25	158	158	158
Min	0.18	1.27	0.13	90	90	90

Update DEA input data to release from April 2021

update H2 pipeline costs for inflation

see https://www.hydrogeninsight.com/production/europes-hydrogen-backbone-of-cross-border-pipelines-will-cost-billions-more-euros-than-initial-estimates/2-1-1560429

Adjust DEA and other EUR-2015 if config['eur_year'] != 2015

Currently inflation adjustment are only made to data with EUR-year != 2015, since 2015 is the DEA default. But if somebody enters config['eur_year'] != 2015, the script should also adjust the DEA values to the new year.

Integrate carbon capture function in existing processing

The function add_carbon_capture(data, tech_data) should be better integrated into the other code for processing DEA assumptions. The current way it is implemented is a hack, since it has to read in the electricity and heat inputs and outputs and capture rates, which aren't required for other technologies.

See also discussion in PR #20.

Publish releases to zenodo

Update submarine HVDC cable cost

we should maybe update the HVDC submarine cable because the current 471.16 €/MWkm are half the cost of other sources like Härtel 2017 with 960 €/MWkm or 1187€/MWkm from ETYS15

Include tech data from other countries than Europe

Include technology assumptions from other countries than Europe

Investment costs vary depending on the country. Currently the cost assumptions are mainly based on cost assumptions for Europe. It would be nice to extend the technology-data also to other countries.

@pz-max @euronion do you have some insights for cost assumptions in other countries?
@Tomkourou kindly offered to help to feed data from other countries back into technology-data

Wrong currency year assumed for electrolysis

DEA data states 2020 in Excel file, compile_cost_assumption does not adjust, assumes 2015.

Preprocessing script (fixing inconsistent DEA entries)

I'm becoming a bit frustrated by the inconsistent data format of the DEA input data.

E.g.: Column orders and names being inconsistent, most unchanging values are filled across all years while sometimes they are not. The inconsistencies for "Hydrogen to Jet Fuel" are e.g. at an extend were I simply started extracting the numbers by hand rather than automatically =/

The inconsistencies also make the compile_cost_assumption.py script more and more bloated and unreadable.

Suggestion:
Have a pre-processing script which is responsible for creating a consistent input data format and move all "if this tech than special treatment" cases there.

new cost module to avoid using vresutilis

Describe the feature you'd like to see

Please give a clear and concise description and provide context why the feature would be useful.
Also, we'd appreciate any implementation ideas and references you already have.

Add source as a third index

Add source as a third index

Add source to the multi-index to allow faster filtering for a certain data source. Therefore one could make a multi-index with technology name (e.g. solar PV), parameter (e.g. investment) and source (e.g. DEA).

electrolysis investment costs

Investment cost assumptions of electrolysis from DEA

Investment cost assumptions of DEA are very optimistic, especially for the near-term. Cost could be adjusted to a smaller plant size (1 MW), and the upper uncertainty bound from DEA.

Include time evolution of DAC cost

Guidelines for adding new data sources

Write a guide in the documentation for how to add new data sources to the database.

technologies with old pypsa assumptions

There are still a few technologies where the old pypsa cost assumptions are used and could be updated with the DEA assumptions, namely:

• decentral resistive heater
• decentral water tanks
• solar thermal ( costs are even higher in DEA and are currently already not really used)
• oil boiler
• Fischer Tropsch

and a few others which capacities are not extendable or not included (geothermal, hydro, PHS)

create config.yaml and snakemake workflow

move all the settings to a config.yaml (retrieve data, which solar data, inflation rate,....)
and automate the workflow with snakemake

Update DEA data to version Feb 2022

The Danish Energy Agency just released an update of their data. Main changes refer to solar PV and offshore wind.

https://ens.dk/service/fremskrivninger-analyser-modeller/teknologikataloger/teknologikatalog-produktion-af-el-og

add CO2, NH3, LH2 and H2 transport and CO2 storage costs from DEA

In the new data cataloque for energy transport from DEA from March 2021 costs for

• CO2 transport (pipe, terminal, ship, road)
• H2, LH2, NH3 (pipe, ship, road)

are included and should be added to the technology-data base.
@euronion maybe this new data is interesting for you as well?

selection of alternative solar costs

https://github.com/lisazeyen/technology_data/blob/4eed4ea01938d1118d27d2dd0732082102652f64/compile_cost_assumptions.py#L18

This line indicates that cost from Vartiaine should be used but then the next line avoid doing so.
Do we need the two lines?

Check technology data for all technologies on low voltage level in pypsa-eur-sec

Currently, the same costs for e.g. home battery and utility battery are assumed in pypsa-eur-sec. The technology assumptions should be checked, if in DEA exists e.g. large and small-scale

Add option to choose upper/lower uncertainty for 2050 estimates

In many cases, the tables from the Danish Energy Agency include two columns "Uncertainty (2050) - Lower" and "Uncertainty (2050) - Upper". These are supposed to represent 90%-quantiles. It would be useful to have a configuration option in config.yaml to choose between {lower, upper, expectation}, such that it is for instance possible to automatically choose the more conservative cost assumptions.

Would that be tricky to implement?

Can you point me to locations in the code where changes would be necessary?

names for hydrogen storage tanks

More consistent syntax for hydrogen storage

costs for green Ammonia production

in the DEA technology data for renewable fuels green Ammonia production is added and could be included into the technology-database

Change currency base_year to 2020 or later

Currently 2015 . Should update this...

Properly license repository: MIT for code, CC-BY-4.0 for outputs

use REUSE

Add technology conversion efficiencies

https://github.com/euronion/trace/blob/main/data/efficiencies.csv Contains a number of technology efficiencies (energy and material inputs to output mappings).

• Integrate them into technology data.
• Start with methanolisation

LNG regasification investment cost seems low

Investment cost for LNG regasification ("CH4 evaporation") is given at 0.28 EUR/kW_CH4 with the explanation "Calculated, based on Fasihi et al 2017, table 1, https://www.mdpi.com/2071-1050/9/2/306".

Tracing the source leads to the paper https://doi.org/10.1016/j.enpol.2008.12.012), which calculates to approximately 20 euro/kW, assuming 2000 load hours/year. Prior constructions (https://www.gem.wiki/Gate_LNG_Terminal) suggest the same order of magnitude.

Anyone who is aware of more recent numbers? @martavp @fneum

Include cost estimates for lines based on NEP 2030

The cost estimates for the Netzentwicklungsplan rae publicly available:

https://www.netzentwicklungsplan.de/de/kos-ten-schaet-zun-gen-zu-ka-pi-tel-531-und-536

We should compare and incoporate these numbers.

Uniform framework for the estimation of future values of the techno-economic parameters

The reduction of the future investments costs (e.g. 2050 vs 2020) don't seem to follow common logic. Some mature technologies with a high marginal cost (when the CO2-cost is included) have major cost reductions and other technologies with a low marginal cost and exponential growth have no cost reductions.

A similar remark for the projected lifetimes (which can only be retroactively determined and cost reductions may lead to shorter lifetimes instead of longer lifetimes).

A similar remark for the projected efficiencies. Efficiencies tend to stabilize once a technology has been matured. Higher projected efficiencies are often related to the difference between theoretical and practical efficiencies.

The differences may be the result of the different sources that have been used. The non-uniform techno-economic parameters may cause the results will be steered to certain technologies. A uniform framework for the estimation of future values of the techno-economic parameters is needed.

Add `.bib` file for reference management and column for bibtex keys

this will facilitate converting the .csv tables to .tex

Unit for methanation is wrong

The unit for methanation investment cost in the cost output is "EUR/MW_CH4; and EUR/kW_CH4" but should be "EUR/kW_CH4".

North Sea Wind Power Hub datasets

We could think about using some of the cost data from North Sea Wind Power Hub datasets found at https://zenodo.org/records/10101328. I think especially for the electrolysis cost and the power transmission cost, we could take their cost assumptions.

update individual heating to DEA release June 2021

update technology data for individual heating to new DEA release (June 2021).

heating technology assumptions (house type, existing/new, decentral gas boilers)

for many technologies there are different assumptions in DEA depending on the house type (e.g one family house/apartment complex) and for new and existing buildings.
Currently the assumptions for existing one family houses are assumed (I have checked for some technologies the investment costs per MW, they don't change much between one family houses and apartment complexes). In general, one could assume a certain percentage of new buildings for the cost assumptions.

For decentral gas boilers there are investment costs and possible additional investments which apply for grid connection if the house is not connected yet
those costs are currently excluded with the assumption that there are no new
decentral gas boilers build in houses with no gas grid connection. This results in high FOM of 10.5% which should be discussed.

update on renewable fuels April 2022

Update to new technology assumptions for renewable fuels from April 2022

new released data

Consider NREL ATB cost database

as complement to DEA technology database

https://atb.nrel.gov/

h/t @euronion

convert everything to 2020-Euro

Convert everything into 2020-Euro instead of 2015-Euro

technology-catalogue-commercial-freight-and

https://ens.dk/en/our-services/projections-and-models/technology-data/technology-catalogue-commercial-freight-and

H2 storage and compressors: Costs and efficiencies

The DEA technology data on H2 storage technologies (Technology Data Catalogue for Energy Storage) contains assumptions for H2 tanks (compressed, <= 200bar) and H2 underground (cavern, compressed <= 200bar). The data reported on these two storage types is not consistent:

a.) data for "hydrogen storage tank" (DEA excel: "151a Hydrogen Storage - Tanks") reports cost and efficiency for the full system, including piping and compressors.
b.) data for "hydrogen underground storage" (DEA excel: "151c Hydrogen Storage - Caverns") only covers the costs and efficiencies of the cavern storage.

The text (DEA pdf) is more clear on this: The storage efficiency of both storage types is similar (>99%), efficiency losses are due to the energy demand of the compressors (4 kWh_el/kg_H2 for compression to 200bar), which is taken 1:1 from the hydrogen LHV of 33 1/3 kWh_LHV/kg_H2 .

For a.) Investment costs for the system without compressors are reported, but FOM is only reported for the full system. Also no cost assumptions for compressors (per MW, only per MWh of storage system capacity) are reported.

Two options:

• separate compressor costs from storage costs
• include compressor costs and efficiency in the H2 underground storage

Pipeline costs

The costs of different pipelines can be compared by converting different units to the same unit which refers to the volume of gas that is transported per hour.

Based on this common unit, the costs of hydrogen pipelines seem too low taken into account:

• far less experience with hydrogen pipelines in comparison with NG gas pipelines
• hydrogen needs bigger and more compression stations
• hydrogen is a very small molecule and can leak easily
• hydrogen causes hydrogen embrittlement which requires different materials and will reduce the lifetime

Furthermore, the techno-economic parameters of repurposed pipelines don't seem correct since the cost should be based on the NG pipeline cost combined with the conversion cost.

c_b and c_v coefficient

currently the old pypsa assumptions for the c_b and c_v values are assumed, since they are very different in the DEA datasheet. This should be checked again.