pandapower-sim

name	pandapower-sim
description	Use when driving pandapower (Python power-system analysis library combining pandas data tables with PYPOWER-style solvers, from Fraunhofer IEE) via Python scripts — load flow, optimal power flow (OPF), short-circuit, time-series, contingency analysis on transmission / distribution networks — through sim runtime one-shot execution.

pandapower-sim

You are connected to pandapower via sim-cli.

pandapower (Thurner et al., IEEE Trans. Power Systems 2018) is the standard Python library for power-system analysis. Pure Python + pandas + numpy/scipy (with optional Numba for speedup). Pip-installable (pip install pandapower).

Scripts are plain .py:

import pandapower as pp
net = pp.create_empty_network()
b1 = pp.create_bus(net, vn_kv=20.0); b2 = pp.create_bus(net, vn_kv=20.0)
pp.create_ext_grid(net, b1)
pp.create_line(net, b1, b2, length_km=10, std_type='NAYY 4x150 SE')
pp.create_load(net, b2, p_mw=0.5)
pp.runpp(net)
print(net.res_bus.vm_pu)            # bus voltage magnitudes (p.u.)

Same subprocess driver mode as PyBaMM.

---

base/ — always relevant

Path	What's there
base/reference/workflow.md	Empty net → buses → branches → injections → run.
base/reference/elements.md	Bus / Line / Trafo / Load / Gen / SGen / ExtGrid / Storage / Switch.
base/reference/solvers.md	runpp (PF), runopp (OPF), runsc (short-circuit), runts (time-series).
base/reference/standard_libs.md	Built-in line types, transformer types, IEEE benchmark networks.
base/snippets/01_pf.py	Verified 2-bus power flow E2E.
base/known_issues.md	numpy bool serialization, AC vs DC PF, slack bus required.

sdk/2/ — pandapower 2.x

• sdk/2/notes.md — version-specific surface notes.

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Hard constraints

1. Every network needs an ext_grid (slack bus) for AC power flow, else runpp raises. For islanded systems use a gen with slack=True.
2. Bus voltages set by vn_kv — must match the line / transformer ratings on each side. Mismatched voltages silently cause convergence failures.
3. Default runpp is AC Newton-Raphson. For approximate / DC use runpp(net, algorithm='dc'). For three-phase: runpp_3ph.
4. Acceptance != "ran without error". Always check that PF converged and bus voltages are within plausible bounds (typically 0.95-1.05 p.u.) and line loadings < 100%.
5. Result tables live on net.res_* AFTER running. Empty before.
6. Print results as JSON on the last stdout line. Cast pandas floats: float(net.res_bus.vm_pu[b]).

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Required protocol

1. Gather inputs:
   • Category A: network topology (bus / line / trafo data), load and generation profiles, slack reference, acceptance.
   • Category B: PF algorithm, tolerance, max iterations.
2. sim check pandapower.
3. Write .py per base/reference/workflow.md.
4. sim lint script.py.
5. sim run script.py --solver pandapower.
6. Validate JSON.