ANDES Documentation#
Python Software for Symbolic Power System Modeling and Numerical Analysis
ANDES is an open-source Python library for power system modeling, computation, analysis, and control. It supports:
Power flow calculation
Time-domain simulation (transient stability)
Eigenvalue analysis (small-signal stability)
Symbolic-numeric framework for rapid model prototyping
Full second-generation renewable energy models
Complete learning path from installation through advanced analysis: power flow, time-domain simulation, eigenvalue analysis, parameter sweeps, and contingency studies.
Research-oriented application examples: forced oscillation analysis, frequency stability under low inertia, ML-based security assessment, and more.
Framework internals: inspect model equations, understand the symbolic-numeric framework, and create new device models.
Validated against commercial tools including PSS/E and TSAT. Side-by-side comparison results demonstrate numerical accuracy for algorithms and models.
CLI commands, configuration options, model reference (auto-generated), and API documentation.
Sponsors#
ANDES was initially developed at the CURENT Engineering Research Center at the University of Tennessee, Knoxville, and has been continually supported by startup funds and grants.
Useful Links#
Quick Install#
conda install -c conda-forge andes
pip install andes
uv pip install andes
git clone https://github.com/CURENT/andes
cd andes
pip install -e .[dev]
Quick Example#
import andes
# Load a test case and run power flow
ss = andes.load(andes.get_case('ieee14/ieee14_fault.xlsx'))
ss.PFlow.run()
# Run time-domain simulation
ss.TDS.run()
# Plot generator speeds
ss.TDS.plt.plot(ss.GENROU.omega)