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Use cases#

Globi produces detailed building energy outputs (for example EnergyAndPeak.pq parquets and related artifacts). Those results can support many kinds of analysis: policy and retrofit comparisons, adoption and willingness-to-pay modeling, emissions accounting, and other workflows that build on fleet-scale simulation.

Why this is a separate repository#

The willingness-to-pay workflow in particular depends on a large set of inputs that globi does not generate: retrofit cost and incentive tables, energy prices, adoption curves, emissions-factor trajectories, census- or survey-backed demographics for propensity models, Monte Carlo settings, and other configuration. Keeping that stack in globi-use-cases avoids bloating the core globi install, keeps simulation and visualization boundaries clear, and lets those analyses evolve on their own release cycle and data layout.

Other downstream use cases (beyond WTP) share that repo so analysis tooling, sample data/inputs/, and Streamlit apps stay in one place. Start here:

github.com/daryaguettler/globi-use-cases

What you will find there#

The globi-use-cases repo includes tools and a Streamlit app for:

  1. Energy and policy impacts - Compare baseline vs retrofit scenario parquets (per year) for energy and peak differences.
  2. Propensity - Per-building acceptance probabilities (residential logit with census-backed demographics; commercial NPV threshold).
  3. Uptake - Adoption curves from JSON so buildings adopt over time from propensity and curve targets.
  4. Emissions - Adopted floor area and fuel mix with editable emissions-factor trajectories.

The main UI covers upload, configuration, curve selection, emissions editing, and a full pipeline run with charts and tables. Bundled sample inputs under data/inputs/ let you explore the app without new globi runs.

For the full feature list, scenario editor, Docker, data layout table, and split_scenarios.py usage, see that repository's README.

Download the repository#

Clone with Git (recommended so you can pull updates):

git clone https://github.com/daryaguettler/globi-use-cases.git
cd globi-use-cases

Alternatively, download a ZIP from the repo's Code menu on GitHub and extract it, then cd into the extracted folder.

Requirements#

  • Python 3.11+
  • uv as the package manager

Set up the environment#

From the repository root:

uv sync

The project's Makefile sets PYTHONPATH=src for local runs so app and use_cases imports resolve; prefer the Make targets below unless you set PYTHONPATH yourself.

Run the analysis app#

make run

Equivalent:

PYTHONPATH=src uv run streamlit run src/app/wtp_app.py

Open the URL Streamlit prints (by default http://localhost:8501).

High-level flow in the app: upload baseline and scenario EnergyAndPeak.pq pairs, configure costs and options in the sidebar, choose adoption curves and emissions trajectories, then run the pipeline and review results.

Optional: a separate scenario editor UI is available with make editor. For Docker, use make docker-build and make docker-run as described in the upstream README.