PyPSA/PyPSA
Feb 2026 – Feb 2026
1 Month active
Languages Used
Python
Technical Skills
backend developmentdata analysisoptimization algorithms
Michael Lindner
PROFILE
Michael Lindner
Developed a secant-based transmission loss approximation with error control for the PyPSA/PyPSA repository, focusing on enhancing the accuracy of power flow optimization. This feature introduced a numerical method to estimate transmission losses more precisely, supporting cost-aware dispatch decisions and improved model fidelity. The implementation involved backend development in Python, integration of optimization algorithms, and the addition of internal constraints to stabilize the new loss model. Documentation was updated to facilitate user adoption and contributor understanding. The work emphasized robust engineering practices, collaborative code contributions, and a focus on data analysis to support more reliable and efficient power system simulations.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
679
Activity Months1
Your Network
45 peopleSame Organization
@tu-berlin.de25
Work History
February 2026
1 Commits • 1 Features
Feb 1, 2026February 2026 (PyPSA/PyPSA) monthly summary: - Key features delivered include a Secant-based Transmission Loss Approximation with error control for power flow optimization, increasing loss estimation accuracy used in dispatch. Internal constraints were added to support the new loss model, and documentation was updated to reflect the new capabilities. - Major bugs fixed: none reported this month; focus was on feature delivery and documentation improvements. - Overall impact: enhances model fidelity and optimization robustness, enabling more cost-aware dispatch decisions and potential fuel/transmission cost reductions through improved loss estimation. - Technologies/skills demonstrated: numerical methods (secant-based error control), integration with optimization workflow, documentation practices, and collaborative code contributions (commit 391870d643cfc2f8655e56d96e013d1aa076f437; Line losses with error control #1495).
1 Commits • 1 Features
Feb 1, 2026February 2026 (PyPSA/PyPSA) monthly summary: - Key features delivered include a Secant-based Transmission Loss Approximation with error control for power flow optimization, increasing loss estimation accuracy used in dispatch. Internal constraints were added to support the new loss model, and documentation was updated to reflect the new capabilities. - Major bugs fixed: none reported this month; focus was on feature delivery and documentation improvements. - Overall impact: enhances model fidelity and optimization robustness, enabling more cost-aware dispatch decisions and potential fuel/transmission cost reductions through improved loss estimation. - Technologies/skills demonstrated: numerical methods (secant-based error control), integration with optimization workflow, documentation practices, and collaborative code contributions (commit 391870d643cfc2f8655e56d96e013d1aa076f437; Line losses with error control #1495).
February 2026
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage40.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
backend developmentdata analysisoptimization algorithms
Repositories Contributed To
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