Interactive Feeder Control Lab

Switch Strategy. Move Through the Day. Watch the Grid React.

This page is the visual core of the site. Pick a control strategy, scrub the day, and compare voltage envelope, bus heatmap, reactive dispatch, curtailment, and violation count on the same feeder.

Live scenario switching Real QSTS data Chart-first analysis
Baseline
355
Violation minutes with no DERMS intervention.
Heuristic
205
Violation minutes after rule-based Volt-VAR plus curtailment.
Optimization
0
Violation minutes with coordinated optimization.
Battery
4th
Alternative path that preserves energy by shifting it in time.
Choose the strategy you want to visualize.
0 - 24h
Zoom
Violation Minutes
--
Time above 1.05 p.u.
Max Voltage
--
Highest voltage on feeder
Curtailment
--
Total energy curtailed
Avg Q Dispatch
--
Reactive power absorption
Current Scenario

Heuristic Control uses rule-based Volt-VAR control. When voltage exceeds 1.03 p.u., inverters absorb reactive power. If voltage reaches 1.05 p.u., active power is curtailed.

This approach reduces violations by 42% compared to baseline but still requires significant curtailment.

Primary View
Voltage Envelope
Read this first: it shows whether the feeder stays inside the ANSI band as the day evolves.
Spatial View
Voltage Heatmap
Which buses run hottest, and when?
Control Signal
Reactive Power Dispatch
Q support is usually the first line of defense.
Cost of Control
Active Power Curtailment
If Q support is insufficient, solar output gets reduced.
Compliance Timeline
Violation Timeline
Count of buses above the upper limit over time.
How to Read the Screen
  • 1
    Start with the KPI row to benchmark the selected strategy.
  • 2
    Use the voltage envelope to see whether the feeder is compliant.
  • 3
    Use the heatmap and dispatch curves to explain why the envelope changed.
Compare Strategies Visually
Teaching Prompt

Switch from Heuristic to Optimization and compare all five visuals. The improvement is not just lower max voltage, but also lower Q demand and dramatically lower curtailment.

Baseline = problem Heuristic = local rules Optimization = coordinated dispatch Battery = energy shifting