Examples & Case Studies

OpenPyTEA ships with three fully worked case studies in the examples/ directory of the repository. Each is a self-contained Jupyter notebook that demonstrates the library’s capabilities on a real-world engineering scenario.

Running the examples

git clone https://github.com/PBTamarona/OpenPyTEA.git
cd OpenPyTEA
pip install "OpenPyTEA[ipython]"
jupyter notebook examples/

Case Study 1 — Hydrogen Production Pathways

File: examples/case_study_1.ipynb

Compares the techno-economics of three hydrogen production routes:

Scenario

Technology

SMR

Steam Methane Reforming (incumbent)

Pyrolysis

Methane Pyrolysis (solid carbon by-product)

Electrolysis

Water Electrolysis (green hydrogen)

The notebook covers equipment selection, CAPEX and OPEX breakdowns, sensitivity to natural gas and electricity prices, and a side-by-side Monte Carlo comparison of the levelized cost of hydrogen (LCOH) across all three pathways.

Key topics demonstrated

  • Creating multiple Equipment objects per scenario

  • Using both cost correlations and direct supply quotes for equipment purchased costs

  • Modelling byproduct revenues and mid-project additional_capex for equipment replacement

  • Running the same analysis on three Plant instances

  • Using plot_multiple_monte_carlo() for cross-scenario comparison

  • Interpreting tornado diagrams to identify cost drivers

Case Study 2 — Hydrogen Liquefaction Precooling

File: examples/case_study_2.ipynb

Techno-economic assessment of a precooling process of hydrogen liquefaction. This case study builds on the a multi-objective optimization study to minimize specific energy consumption and levelized cost in mixed-refrigerant systems.

Key topics demonstrated

  • Integrating OpenPyTEA into an optimization workflow to evaluate techno-economic

trade-offs across candidate plant configurations (a stepping stone toward full process-optimization coupling) * Using breakdown charts to compare CAPEX and OPEX structure between plant configurations * Evaluating the impact of process design choices on both specific energy consumption and levelized cost * Copying and modifying an existing Plant instance to create a new scenario with different equipment and cost structure

Case Study 3 — Geothermal Energy Systems

File: examples/case_study_3.ipynb

Compares two geothermal applications:

Scenario

System

District heating

Heat pump for residential heating

Power generation

Organic Rankine Cycle (ORC)

Key features: 30-year project lifetime, full MACRS depreciation, and Monte Carlo uncertainty analysis for both scenarios.

Key topics demonstrated

  • Modelling pre-production CAPEX (geothermal site exploration and drilling) using the additional cost configuration

  • Configuring MACRS depreciation for long-lifetime assets

  • Comparing levelized cost of heat (LCOH) against levelized cost of electricity (LCOE) across scenarios

For a step-by-step walkthrough of every main feature, see the Tutorials page.