Interactive Dashboards

GDM-Flow can generate rich interactive HTML dashboards using Plotly. Dashboards visualise solver results across multiple dimensions and are useful for presentations, reports, and exploratory analysis.

Quick Start¶

# Generate a dashboard with all four solvers
gdm-flow plot examples/models/p5r.json

# Select specific solvers
gdm-flow plot examples/models/p5r.json -s ac -s pf

# Custom output path
gdm-flow plot examples/models/p5r.json -o my_dashboard.html

The dashboard is saved as a self-contained HTML file that can be opened in any browser.

Installation¶

Dashboards require the plotting extra:

pip install -e ".[plotting]"

This installs plotly>=5.0.

Dashboard Panels¶

Voltage-Distance Profile¶

Shows per-unit voltage magnitude along feeder distance from the source bus. Each phase gets its own subplot. The radial tree topology is preserved — branching points fork naturally so the feeder structure is visible.

Each solver’s results are overlaid with distinct colors:

AC OPF — blue
AC PF — purple
DC OPF — green (voltage shown as nominal since DC OPF solves for angles, not magnitudes)
LinDistFlow — orange

Branch Power Flow¶

Active and reactive power flow per branch, broken down by phase.

Branch Loading¶

Apparent power loading compared against equipment ampacity limits. Branches exceeding their thermal limit are highlighted.

Line Losses¶

Per-branch $I^2R$ loss breakdown, useful for identifying the costliest segments.

Equipment State¶

Tables summarising the state of:

Capacitors — on/off state, banks on/total, rated and effective kvar
Regulators — voltage setpoint, min/max limits, PT ratio
Transformers — winding voltages, tap positions, service status

Programmatic Usage¶

You can also generate dashboards from Python:

from gdm.distribution import DistributionSystem
from gdm_flow import optimize_ac_power_flow_from_components
from gdm_flow.ac_pf import solve_ac_power_flow_from_components
from gdm_flow.dashboard import generate_dashboard

system = DistributionSystem.from_json("model.json")

# Run solvers (results dict maps solver name to result dict)
results = {}

ac_result = optimize_ac_power_flow_from_components(system)
results["AC OPF"] = {
    "solver": "AC OPF",
    "success": ac_result.success,
    "result": ac_result,
    # ... additional fields
}

pf_result = solve_ac_power_flow_from_components(system)
results["AC PF"] = {
    "solver": "AC PF",
    "success": pf_result.success,
    "result": pf_result,
    # ... additional fields
}

generate_dashboard(system, results, "dashboard.html", model_name="my_model")

Comparison HTML (via `gdm-flow compare`)¶

The gdm-flow compare command can also export a simpler comparison HTML file:

gdm-flow compare examples/models/p5r.json -o comparison.html

This generates a multi-panel Plotly figure focused on voltage comparison across solvers, rather than the full dashboard produced by gdm-flow plot.