PyPSA / PyPSA/technology-data

H2 storage and compressors: Costs and efficiencies

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Python
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Description

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

Contributor guide

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First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by comparing the DEA Excel entries “151a Hydrogen Storage - Tanks” and “151c Hydrogen Storage - Caverns” with the DEA PDF guidance on compressor energy and storage efficiency. Review the repository’s hydrogen storage data assumptions, then resolve and document one consistent treatment of compressor costs, FOM, and efficiency for both storage types.

Written by the indexing model from the issue text.

Assessment

Domain
data
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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