PowerGridModel/power-grid-model
Mar 2026 – Apr 2026
2 Months active
Languages Used
C++CMakeJSONMarkdownShellYAML
Technical Skills
C++CMakeContinuous IntegrationGitPythonalgorithm development
marc van raalte
PROFILE
Marc Van Raalte
Worked on the PowerGridModel/power-grid-model repository, focusing on enhancing the performance and maintainability of power grid simulation tools. Over two months, delivered three features centered on optimizing the link solver and internal loads computation using C++ and CMake, with an emphasis on algorithm development and validation. Refactored the Gauss-elimination based solver for improved throughput and expanded test coverage to validate correctness on larger systems. Introduced a new compute_internal_loads function with a 15x15 matrix for higher accuracy and addressed configuration readability and compatibility issues. These efforts enabled faster, more robust simulations and improved scalability for complex power grid analyses.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
12Total
Bugs
0
Commits
12
Features
3
Lines of code
193,117
Activity Months2
Your Network
59 peopleWork History
April 2026
10 Commits • 2 Features
Apr 1, 2026April 2026 performance summary for PowerGridModel/power-grid-model. Delivered key enhancements to the link solver and internal loads computation, improving accuracy, robustness, and scalability for grid analysis. The work enables larger models and faster, more reliable results for planning and operation.
10 Commits • 2 Features
Apr 1, 2026April 2026 performance summary for PowerGridModel/power-grid-model. Delivered key enhancements to the link solver and internal loads computation, improving accuracy, robustness, and scalability for grid analysis. The work enables larger models and faster, more reliable results for planning and operation.
April 2026
March 2026
2 Commits • 1 Features
Mar 1, 2026Month: 2026-03. This period focused on performance optimization and readability improvements for the Power Grid Model. Primary work centered on optimizing the link solver and set_projection_system to reduce redundant calculations, complemented by comprehensive formatting and readability improvements across configuration files and scripts. These changes deliver faster simulation runs, improved maintainability, and clearer configuration management, enabling more reliable and scalable power grid analyses.
March 2026
2 Commits • 1 Features
Mar 1, 2026Month: 2026-03. This period focused on performance optimization and readability improvements for the Power Grid Model. Primary work centered on optimizing the link solver and set_projection_system to reduce redundant calculations, complemented by comprehensive formatting and readability improvements across configuration files and scripts. These changes deliver faster simulation runs, improved maintainability, and clearer configuration management, enabling more reliable and scalable power grid analyses.
Activity
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Quality Metrics
Correctness91.6%
Maintainability88.4%
Architecture88.4%
Performance86.6%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++CMakeJSONMarkdownShellYAML
Technical Skills
C++C++ developmentC++ programmingCMakeContinuous IntegrationGitPythonalgorithm designalgorithm developmentalgorithm optimizationalgorithm validationdata structuresnumerical methodssoftware debuggingunit testing
Repositories Contributed To
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