Open-Source Techno-Economic Assessment Python-Toolkit¶
OpenPyTEA: An open-source python toolkit for techno-economic assessment of chemical process plants and energy systems with economic sensitivity and uncertainty evaluation. It bridges process simulation tools — which provide mass and energy balances — with rigorous economic evaluation, covering capital expenditure (CAPEX), operating expenses (OPEX), and key financial metrics. Source code, issue tracker, and contributions: github.com/pbtamarona/OpenPyTEA.
🎓 Upcoming Workshop — Register Now!
Open-Science Techno-Economic Assessment with OpenPyTEA: From Process Design to Economic Insights
We are hosting a one-day workshop covering the full workflow from process design and simulation to economic evaluation, with lectures, a hands-on OpenPyTEA session, and an industry talk by Shell. It closes with a community discussion on establishing shared TEA standards.
📅 Date: November 6, 2026 | 09:30 – 18:00
📍 Location: Process & Energy, TU Delft, Delft, The Netherlands
📝 Registration: aanmelder.nl/openpytea2026
Lunch, snacks, coffee, and drinks will be provided!
Set up OpenPyTEA using pip, uv, or from source.
Run your first techno-economic assessment in minutes.
In-depth guides for equipment costing, plant TEA, analysis, and more.
Complete autodoc reference for all classes and functions.
Worked Jupyter notebooks covering hydrogen, geothermal, and other case studies with full TEA workflows.
Walkthrough notebook and step-by-step video tutorials covering the full OpenPyTEA workflow.
Run TEA interactively without writing code. Still in active development — not all features are available yet.
Key features¶
Modular architecture — equipment costing, plant economics, and analysis are cleanly separated
Transparent methodology — every formula is open and documented
Extensive financial metrics — NPV, IRR, ROI, levelized cost, payback time, and full cash-flow tables
Multiple depreciation methods — straight-line, declining-balance, MACRS
Sensitivity & uncertainty — one-way sensitivity, tornado diagrams, Monte Carlo simulation
Interactive web GUI — React + FastAPI front-end for no-code analysis (work in progress)*
Reproducible workflows — JSON-based configuration files and result export
Research-oriented design — easy integration with other frameworks (optimization, LCA, etc.)
Contents¶
Getting Started
API Reference