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GP-EE-1WUEPVTElectricalOpen for request

pandapower distribution-network simulation

A pandapower study for analysing load flow, voltage limits, losses, contingencies, and distributed-generation scenarios in a selected distribution network.

  • pandapower
  • Python
  • NumPy
  • Pandas
  • Plotly
  • Docker

Software compatibility

pandapower only

The network models and studies are delivered for a pinned pandapower environment. ETAP, DIgSILENT PowerFactory, PSS/E, and PSCAD project files are not included.

Project definition

Problem statement

Distribution voltage, loading, and losses change with demand, transformer settings, topology, conductor data, distributed generation, and outages, while an unconverged solution has no engineering meaning.

Project objectives

  • Model a selected balanced radial or weakly meshed distribution network.
  • Verify bus, line, transformer, switch, load, and generation data and units.
  • Run baseline load flow and selected time-series or scenario cases.
  • Evaluate voltage, loading, losses, reverse flow, and N-minus-one contingencies.
  • Compare mitigation options such as tap changes, reactive support, or network reconfiguration.

System design

System modules

01

Network builder

Creates buses, branches, transformers, switches, loads, generators, and standard types.

02

Power-flow runner

Executes balanced load flow with convergence and result validation.

03

Scenario engine

Applies load levels, distributed generation, outages, taps, and reactive-power cases.

04

Violation analyser

Finds voltage, thermal, convergence, reverse-flow, and loss conditions.

05

Mitigation comparison

Tests selected corrective actions under the same scenarios and limits.

Methodology

System workflow

  1. 01
    Verify network

    Connectivity, ratings, impedances, units, and source conditions are checked.

  2. 02
    Run baseline

    A reference load flow establishes voltage and loading profiles.

  3. 03
    Apply scenarios

    Demand, generation, topology, and outage changes are simulated.

  4. 04
    Detect violations

    The system records buses, branches, cause, severity, and convergence.

  5. 05
    Compare mitigation

    Selected network actions are tested against the same cases.

Demonstration scenario

A prepared radial feeder runs at evening peak, then receives increasing rooftop-solar generation and one branch outage. The study compares voltage, line loading, losses, reverse flow, and two mitigation cases.

Engineering

Technical architecture

Environment
Pinned pandapower and Python environment with network and scenario files.
Network model
Balanced steady-state equivalent circuits with documented base values and component data.
Studies
Power flow, selected time series, contingency loops, and sensitivity calculations.
Verification
Small hand-calculated cases, result bounds, balance checks, and a prepared reference feeder.

Testing

Evaluation

Evaluation measures

  • Power-balance and convergence checks
  • Bus-voltage and branch-loading agreement with reference cases
  • Network losses and reverse-flow calculations
  • Contingency violation detection
  • Sensitivity to load, generation, impedance, and tap assumptions
  • Runtime across network and scenario sizes

System boundaries

  • Only the pinned pandapower environment is delivered.
  • The first scope uses balanced steady-state network models.
  • Protection coordination, electromagnetic transients, detailed grounding, and live control are excluded.
  • Utility studies require verified asset data, applicable standards, and qualified power-system engineers.

Included

  1. 01Versioned distribution-network model
  2. 02pandapower load-flow, contingency, and scenario scripts
  3. 03Voltage, loading, loss, and sensitivity visualisations
  4. 04Prepared load, generation, outage, and benchmark cases
  5. 05Complete source code in a private GitHub repository
  6. 06Complete project documentation with synopsis, abstract, methodology, single-line diagrams, power-flow results, screenshots, and conclusion
  7. 07Setup and usage guide

Project record

No buyer information is collected on this page.

Permanent project ID
GP-EE-1WUEPVT
Catalogued
22 Aug 2026
Completed
Pending
Verified
Pending
Demonstration
Added when ready

Handover

After purchase

  1. 01
    Payment is confirmed

    The project is marked unavailable and cannot be purchased again.

  2. 02
    Repository access is granted

    The buyer's submitted GitHub account receives access to the private repository.

  3. 03
    The purchase record is delivered

    The certification sheet is prepared from the reviewed buyer details and sent privately by email.