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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.
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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.
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.
Creates, analyzes, and visualizes complex networks and graphs in Python. Use for graph algorithms, centrality, shortest paths, community detection, and network generation.
Creates, manipulates, and analyzes graphs and networks using NetworkX Python library. Supports graph types, algorithms like shortest paths and centrality, community detection, I/O, and visualization.
Share bugs, ideas, or general feedback.
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).