Energy
PyPSA v1.0: Introducing Modeling Under Uncertainty
<p><a href="https://pypsa.org/"><strong>PyPSA</strong></a> is an open-source Python framework for optimising and simulating modern power and energy systems, designed to scale well with large networks and long time series. It is made for researchers, planners and utilities with basic coding aptitude who need a fast, easy-to-use and transparent tool for power and energy system analysis.</p>
<p>The first public version was released in 2016 and has since gained many users and contributors from around the world, becoming one of the most <a href="https://docs.pypsa.org/latest/home/users/">widely used</a> energy system modeling tools. In October 2025, <a href="https://docs.pypsa.org/latest/user-guide/v1-guide/">version 1.0</a> was released, which now enables modeling under uncertainty with a two-stage stochastic programming framework. This allows for more realistic decision making by accounting for multiple possible futures with uncertain renewable generation, demand, and prices, rather than optimizing for a single expected scenario.</p>
<p>The talk will give a general overview of PyPSA and showcase the new stochastic programming functionality by solving an energy system planning problem under uncertainty. It is suitable for both experienced PyPSA users and newcomers to energy system modeling.</p>
Additional information
| Live Stream | https://live.fosdem.org/watch/aw1.126 |
|---|---|
| Type | devroom |
| Language | English |
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