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### Key features ### Key features
* **High numerical robustness.** Backed by the SAS approach, the PowerSAS tool provides much better convergence than the tools using traditional Newton-type algebraic equation solvers when solving algebraic equations (AE)/ordinary differential equations (ODE)/differential-algebraic equations(DAE). * **High numerical robustness.** Backed by the SAS approach, the PowerSAS tool provides much better convergence than the tools using traditional Newton-type algebraic equation solvers when solving algebraic equations (AE)/ordinary differential equations (ODE)/differential-algebraic equations(DAE).
* **Enhanced computational performance.** Due to the analytical nature, PowerSAS provides model-adaptive high-accuracy approximation, which brings significantly extended effective range and much larger steps for steady-state/dynamic analysis. PowerSAS has been used to solve large-scale system cases with 200,000+ buses. * **Enhanced computational performance.** Due to the analytical nature, PowerSAS provides model-adaptive high-accuracy approximation, which brings significantly extended effective range and much larger steps for steady-state/dynamic analysis. PowerSAS has been used to solve large-scale system cases with 200,000+ buses.
* **Customizable and extensible.** PowerSAS supports flexible customization of grid analysis scenarios, including complex event sequences in extended simulation term. * **Customizable and extensible.** PowerSAS supports flexible customization of grid analysis scenarios, including complex event sequences in extended simulation term.
### Citing
If you are using **PowerSAS.m** in research work to be published, please include explicit citation of our work in your publication. Please place the following entries in your bibliography:
[1]. J. Liu, R. Yao, F. Qiu, Y. Liu and K. Sun, "PowerSAS.m – An Open-Source Power System Simulation Toolbox Based on Semi-Analytical Solution Technologies," in IEEE Open Access Journal of Power and Energy, doi: 10.1109/OAJPE.2023.3245040.
The corresponding BiBTex citations are given below:
@ARTICLE{powersas,
author={Liu, Jianzhe and Yao, Rui and Qiu, Feng and Liu, Yang and Sun, Kai},
journal={IEEE Open Access Journal of Power and Energy},
title={PowerSAS.m – An Open-Source Power System Simulation Toolbox Based on Semi-Analytical Solution Technologies},
year={2023},
doi={10.1109/OAJPE.2023.3245040}
}