Simulation outputs and result data for: Boosters or Building Renovations? An evaluation of 4th Generation District Heating Strategies

This deposit contains the simulation outputs and intermediate result data accompanying the paper:

  Casamassima, L. et al. (2026). Boosters or Building Renovations? An evaluation of 4th Generation District Heating Strategies.

  Published on: Energy Conversion and Management: X (under review).

  The companion source code is available on GitHub:  https://github.com/Tyler-lc/4th_gen_dh — release casamassima2026-ecmx.

https://github.com/Tyler-lc/4th_gen_dh/releases/tag/casamassima2026-ecmx  

  Together this deposit and that release constitute the full paper-citable artifact.

 Contents

  A 5.7 GB compressed archive (~20 GB extracted) containing the gitignored output trees of the analysis pipeline that cannot ship with the source repository due to size:

  - `building_analysis/results/` — per-building hourly energy demand outputs, scenario aggregate parquets (high-temperature DH, low-temperature DH with renovation, booster heat pump), and the booster sensitivity sub-tree across ten grid temperatures (25–70 °C).  - `building_analysis/dhw_profiles/` — per-building domestic hot water demand profiles.  - `sensitivity_analysis/` — sensitivity-analysis outputs across electricity/gas price, investment-cost multipliers, discount rate, and renovation-cost reduction factors.  - `plots/` — publication figure assets and per-figure data exports.  - `grid_calculation/cache/` — Pyomo/Gurobi district-heating network optimisation cache.

  54,802 entries total. Compressed: 5.7 GB. Extracted: ~20 GB.

  ## How to use

  ```bash  git clone https://github.com/Tyler-lc/4th_gen_dh  cd 4th_gen_dh  git checkout casamassima2026-ecmx  conda env create -f environment.yml  conda activate dh_sim  pip install -e .  python scripts/restore_paper_data.py    # downloads this archive, verifies SHA256, extracts  pytest -m regression                    # 29 regression tests pass against paper-aligned baseline

  Full step-by-step instructions in docs/PAPER_DATA_ARCHIVE.md of the release.

  Reproducibility note

  The data in this archive was produced by the codebase as it existed at git tag paper-submission-v1. The post-submission paper-ecmx-2026 snapshot contains a hardened deterministic-seeding refactor that draws a different sample of the same stochastic process. Re-running   the pipeline from the snapshot code reproduces the methodology but not the bit-for-bit numbers. Directional drift between the two regimes is documented in docs/baseline_comparison_2026-04-20.md on the snapshot branch.

  To reproduce the paper's exact numerical results, use this archive together with the snapshot's git-tracked outputs.

  Integrity verification

  SHA256 of 4th_gen_dh_paper_data_2026-04-29.tar.gz:  18d00e3431460e08ba068ef47d9266abe6d8ec051915d519a18bdf2f0a78f01e

  Verify after download:  shasum -a 256 4th_gen_dh_paper_data_2026-04-29.tar.gz