Microgrid Power Flow 3D Simulator — Dispatch, Curtailment & Utility Exchange Interactive

Interactive 3D grid-tied microgrid dispatch simulator with a supply-and-demand workbench (utility/PCC, solar array, wind generation, battery storage, critical loads and flexible loads), a battery dispatch-policy selector (self-consumption, peak shaving, manual battery power), controls for available solar and wind power, critical and flexible demand, manual battery request, utility import/export limits, battery state of charge, a utility-connected toggle, a battery grid-forming-available toggle and a flexible-load-shed toggle, time-stepped playback with real-time to 60× fast-forward, live solar/wind/battery/grid/served-load/SOC readouts, power and energy-balance charts, model equations, six guided experiments (self-consumption, peak shaving, full battery/zero export, capacity shortfall, utility separation, no island reference), a built-in model-verification bench (checks.js), a timestamped event log with trial-report export, guided lessons and a knowledge-check quiz.

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About this tool — how it works & FAQOpen ▾Close ▴

About the Microgrid Power Flow Simulator

This simulator models the everyday, normally grid-tied dispatch problem in a microgrid: balancing solar, wind, battery storage and utility exchange against critical and flexible demand under an import/export limit. Unlike the separate Islanded Microgrid lab, which focuses specifically on frequency, synchronization and battery grid-forming behavior after the utility connection is lost, this simulator is a quasi-steady real-power balance-and-dispatch model — the utility-disconnect scenario here is one exercise among several, not the model's central subject.

What the simulator shows

• A real-time 3D supply-and-demand workbench — utility/point-of-common-coupling, solar array, wind generation, battery storage, critical loads and flexible loads — with a toggleable enclosure, auto-rotate, expand, hideable labels and selectable components with callouts. • A battery dispatch-policy selector: self-consumption, peak shaving and manual battery power, plus sliders for available solar AC power (0–180 kW), available wind AC power (0–100 kW), critical demand (10–180 kW), flexible demand (0–120 kW), manual battery request (−100 to 100 kW), utility import/peak target (0–150 kW), utility export limit (0–150 kW) and battery state of charge override, with checkboxes for utility connected, battery grid-forming available, and disconnect flexible loads (load shed). • Playback controls: pause/resume, advance 0.1 s, advance 1 s, and a speed selector from 10× slow motion through real time to 60× faster, plus a reset-protection button and full laboratory reset. • Live readouts for solar delivered, wind delivered, battery power (signed, + is discharge), utility power (signed, + is import), served load and battery state of charge, an operating-sequence narrative, and a status badge. • A Power & energy balance analysis tab with two charts, the underlying model equations, an analysis-scope note and snapshot measurements. • An Experiments tab with six guided scenarios (self-consumption, peak shaving, full battery with zero export, capacity shortfall, utility separation, no island reference), a Model verification bench running independent deterministic checks against a fresh model instance, and a timestamped event log with trial-report export. • A Learn & assess tab with guided lessons, a knowledge-check quiz and a scope/references section.

How dispatch, curtailment and unserved energy interact

The three dispatch policies decide what the battery does: self-consumption uses storage to soak up the gap between renewable generation and demand and minimize utility exchange; peak shaving specifically targets keeping utility import at or below a chosen target by discharging the battery to cover demand above that target; manual mode lets you request battery charge or discharge power directly. Whatever the policy decides, power balance must close exactly — solar plus wind plus battery plus utility power always equals served load, with any demand that cannot be met reported explicitly as unserved energy rather than silently exceeding equipment ratings.

Energy limits often bind before power limits do: a battery can sit well within its ±100 kW power rating and still run out of usable kWh, which is why accelerated playback speeds are useful for watching SOC and cumulative import/export evolve. When the battery is full and the utility export limit caps how much can leave the site, surplus renewable generation has nowhere to go and must be curtailed — solar and wind share proportional curtailment in this model, so maximum available renewable power doesn't guarantee maximum delivered power.

Scope and what this model excludes

This is a quasi-steady, balanced real-power dispatch model. Import limits and source shortages are modeled as immediate service-capacity limits rather than a solved voltage-collapse problem, battery round-trip efficiency is fixed at 95% in each direction, and source powers are treated as AC-side fixtures. Frequency, reactive power, network impedance, synchronization transients, protection delays and line losses are explicitly excluded here — the model's own scope note directs you to the separate Islanded Microgrid lab for that frequency/synchronization experiment, since this simulator's utility-separation exercises only test whether power balance closes locally, not how the bus re-synchronizes or forms frequency after disconnection.

Frequently asked questions

How is this different from the standalone Islanded Microgrid lab?

This Microgrid Power Flow lab is a normally grid-tied dispatch model — it is about deciding how solar, wind, battery and utility exchange should balance against demand under import/export limits, including a couple of utility-separation exercises to check that local power balance still closes. The separate Islanded Microgrid lab is specifically about the frequency, synchronization and grid-forming behavior a microgrid needs to survive and operate after it loses its utility connection, which is a different, narrower physical problem than this lab's dispatch focus.

What is the difference between the three dispatch policies?

Self-consumption uses the battery to absorb the mismatch between renewable generation and demand and minimize net utility exchange. Peak shaving specifically targets a utility import ceiling, discharging the battery to keep import at or below that target. Manual mode lets you set the battery's charge or discharge power directly, overriding automatic dispatch logic.

Why does the simulator curtail renewable generation instead of using all of it?

Generated power has to go somewhere: to load, to battery charging, or to utility export. Once the battery is full and the utility export limit is reached, any remaining solar or wind output cannot be absorbed, so the model curtails it proportionally across both renewable sources rather than allowing power balance to be violated.

What does the model verification bench check?

The Experiments tab includes a Model verification bench that runs independent deterministic checks — covering the source-capacity limit on charging, the power-balance closure across all sources, peak-shaving import targets, curtailment under a full battery with no export allowance, zero generation with no grid or forming reference, and SOC boundary enforcement — against a freshly constructed model, leaving your live experiment state untouched.

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