From pandapower
Analyzes electric power networks with pandapower v3.4.0: builds models (buses, lines, transformers, loads, generators), runs AC/DC power flow, OPF, short circuit (IEC 60909), state estimation, time series, topology, plotting.
How this skill is triggered — by the user, by Claude, or both
Slash command
/pandapower:pandapowerThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
pandapower is an open-source Python library for automated analysis and optimization of power systems. It stores network data as pandas DataFrames, provides Newton-Raphson and other power flow solvers (including C++ backends via lightsim2grid and PowerGridModel), and supports advanced studies including OPF, short circuit (IEC 60909), three-phase unbalanced flow, and state estimation.
pandapower is an open-source Python library for automated analysis and optimization of power systems. It stores network data as pandas DataFrames, provides Newton-Raphson and other power flow solvers (including C++ backends via lightsim2grid and PowerGridModel), and supports advanced studies including OPF, short circuit (IEC 60909), three-phase unbalanced flow, and state estimation.
Version: v3.4.0 Language: Python License: BSD 3-Clause Authors: University of Kassel (e2n) and Fraunhofer IEE
import pandapower as pp
# Create network
net = pp.create_empty_network(f_hz=50.)
# Add buses
b_hv = pp.create_bus(net, vn_kv=110., name="HV Bus")
b_mv = pp.create_bus(net, vn_kv=20., name="MV Bus")
# Add external grid (slack/reference)
pp.create_ext_grid(net, bus=b_hv, vm_pu=1.02)
# Add transformer (uses built-in standard type library)
pp.create_transformer(net, hv_bus=b_hv, lv_bus=b_mv, std_type="25 MVA 110/20 kV")
# Add load
pp.create_load(net, bus=b_mv, p_mw=10.0, q_mvar=2.0)
# Run AC power flow
pp.runpp(net)
# Inspect results (stored in net.res_* DataFrames)
print(net.res_bus[["vm_pu", "va_degree"]])
print(net.res_trafo[["loading_percent"]])
print(f"Converged: {net.converged}")
net.bus, net.line, net.load, etc.); results in net.res_* tables after power flow.p_mw means consumption for loads; positive p_mw means generation for generators/sgens.create_std_type().sn_mva as base; power in MW/Mvar; impedances in ohm/km.runpp() and other solvers write results to net.res_* tables; check net.converged after each run.pandapower.topology, pandapower.plotting, pandapower.shortcircuit, pandapower.estimation, pandapower.timeseries, pandapower.control are separate namespaces.| Domain | File | Description |
|---|---|---|
| Network Creation | api-network.md | Buses, lines, transformers, loads, generators, switches, standard types, predefined networks |
| Power Flow | api-powerflow.md | AC/DC power flow, OPF, 3-phase flow, short circuit, state estimation, result tables |
| Topology | api-topology.md | Graph creation, connectivity, distance, island detection |
| Plotting | api-plotting.md | Matplotlib simple plot, custom collections, Plotly interactive, geodata |
| Toolbox | api-toolbox.md | Element selection, network modification, file I/O, comparison, time series |
| Workflows | workflows.md | Complete working examples for common studies |
pp.runpp(net) — See api-powerflow.mdpp.runopp(net) — See workflows.mdpp.shortcircuit.calc_sc(net, fault="3ph") — See api-powerflow.mdpp.plotting.simple_plot(net) — See api-plotting.mdpp.networks.case14(), pp.networks.mv_oberrhein() — See api-network.mdnet.converged after running power flow. Non-convergence often indicates voltage angle issues — try init="dc" or algorithm="iwamoto_nr".bus_geodata/line_geodata DataFrames; run pp.plotting.geo.convert_geodata_to_geojson(net) to upgrade.runopp() will fail without at least one cost function (create_poly_cost or create_pwl_cost); all controlled elements need min_p_mw/max_p_mw limits.lightsim2grid or power-grid-model for 10-100x speedup on large networks; pandapower uses them automatically when available (pip install pandapower[pgm]).runpp_3ph() is imported from pandapower.pf.runpp_3ph, not the top-level namespace.calc_sc() lives in pandapower.shortcircuit; single-phase faults require transformer zero-sequence parameters (vk0_percent, vkr0_percent).npx claudepluginhub datathings/marketplace --plugin pandapowerGuides PyPSA power system studies: load/create networks, inspect components, run power flow, solve operational OPF, and perform capacity-expansion optimization with progressive disclosure.
Performs steady-state distribution power system analysis including power flow, state estimation, short-circuit calculations, and batch simulations using power-grid-model library with numpy structured arrays.
Diagnoses and resolves power-flow convergence failures in PSS/E, PSLF, PowerWorld, pandapower, PyPSA, surge, and OpenDSS. Separates data errors from numerical fragility from physical infeasibility.