Paste a scope narrative, a schedule summary, or a temporary-facilities section. The extraction step reads it for duration, phasing, shift pattern, equipment, and site constraints, then builds the electrical load profile a microgrid can be modelled against — flagging every value it had to infer or assume.
Project narrative
More detail produces a better profile, but a paragraph is enough to start. Schedules, phase durations, equipment lists, and fuel logistics are the highest-value things to include.
Start from
Known inputs Optional
Anything entered here is treated as fact and will not be overridden by inference. Leave blank to let the extraction step infer it from the narrative.
Coordinates are looked up from the site name. You can also paste them directly.
Power profile
Every value carries its confidence. Adjust anything you know better than the model did — the load figures drive the whole design, so an hour spent here is worth more than any amount of equipment tuning downstream.
Scenario Lab
Drag assets from the library onto the bus and watch the day run. The demand is the profile you just reviewed — fixed, and unchanged by anything you build here. Every change re-dispatches the full performance period against a right-sized diesel-only baseline.
Report
Dispatch simulated in two-minute steps across the full performance period.
Modelled estimate — not a validated measurement
This report is the output of a simulation. Every figure in it is a modelled estimate produced from stated assumptions about site loads, weather, equipment behaviour, controller logic and fuel logistics, and actual performance will differ. Except where an asset or configuration is explicitly marked Measured, nothing here is derived from metered performance of this project.
It is not an engineering certification, a performance guarantee, or a warranty of fuel consumption, emissions or availability, and it is not a substitute for design by a licensed professional engineer. Do not use it as the sole basis for final equipment selection, procurement, or a contractual commitment without independent verification. Assumptions and their consequences are set out in full under Assumptions & Method.
Tethra Systems · Power RECON ·
Assumptions & Method
Where the line sits between what is measured and what is modelled. Read this before citing any figure from this tool in a deliverable.
What is measured
One configuration in the asset catalog is backed by field telemetry: two Viridi RPS150 battery units with a Multiquip DCA70USI generator, DEIF-controlled, on a real construction deployment at Kalaeloa between 31 March and 20 April 2026. Metered consumption fell from a documented 816 gallon diesel-only baseline to 118 gallons — an 86% reduction. The dispatch logic, generator staging, and fuel-curve treatment in this tool are the same model validated against that record.
What is modelled
Everything else. Your project's loads, the solar contribution, the weather, and any asset not marked Measured in the catalog are best-engineering estimates. They are grounded in published data and stated construction norms, but they are not telemetry. The confidence chips throughout the tool mark exactly which is which.
Dispatch and merit order
Each two-minute step serves load in the order solar → grid → generator → battery, and charges the battery from solar surplus → grid → generator. Grid sits ahead of the diesel everywhere it appears, for both serving and recharging, so wherever firm utility capacity exists it is used before a set fires.
The generator starts only when grid and battery together cannot meet demand, or when the pack hits its floor and the grid cannot recharge it. Once running it serves load directly and charges the pack toward its ceiling in one sustained block, then shuts down — matching real charge-controller behaviour and preventing short-cycling. On systems carrying solar the controller will not burn diesel to charge the pack while the sun is up.
Generators stage independently. The controller brings on only the fewest units — or, for mixed sizes, the size-appropriate combination — needed for the moment's demand, each loaded on its own fuel curve. Lumping N generators onto a single curve under-counts partial-load fuel; staging each unit separately is less optimistic and more defensible.
Staging carries hysteresis, because real switchgear does. A unit is added only after demand has been sustained above a share of online capacity, and shed only after demand has sat below a lower share for longer. The gap between those two thresholds is deadband, and it exists to stop a controller hunting between sets. This matters far more at a two-minute step than at fifteen: at fifteen minutes the texture that provokes hunting was averaged away, so ideal per-step staging looked plausible. At two minutes it is visible, and a model without hysteresis would credit the fleet with tracking demand more perfectly than any real switchgear can. Load is never left unserved for the sake of a timer — when online capacity is genuinely short, the next set blocks in immediately.
Duty limits are checked, not just fuel. Two published thresholds are reported against. Below roughly 30% of nameplate a set accumulates damage the fuel figure alone does not show, and the Lab flags time spent there; manufacturer guidance puts the recommended minimum at 30% with a hard floor near 10%. At the other end, ISO 8528-1 limits a prime rating to a 70% average load factor over 24 hours, so a fleet averaging above that is being worked at a standby duty and is flagged as wanting another set or a larger one. A design can be cheap on fuel and still wrong on duty.
The baseline we compare against
A right-sized conventional diesel fleet: the smallest installed capacity that covers project peak demand at an 80% load factor, plus one spare unit, load-following but never running below its minimum load fraction. That floor is what makes a lightly loaded diesel burn fuel it does not need to.
This is deliberately conservative. Real sites are routinely fed by sets far larger than the load requires, which idle worse than the model assumes — so a right-sized baseline understates the real diesel case rather than inflating it. You can override the baseline fleet on the equipment step.
Solar
Output is solved from site latitude and day of year rather than fitted to one region: solar declination and hour angle give the beam component, the Erbs correlation splits diffuse off the global horizontal, and an isotropic transposition puts it on a fixed array tilted toward the equator at latitude (capped at 40°). Cell temperature derates output from the plane-of-array irradiance and the site's ambient profile.
The report shows this working for your own site. Its solar section reports specific yield and capacity factor month by month against the clearness index each month was solved from, so the prediction can be checked against experience rather than taken on trust. Site coordinates are resolved from the site name by gazetteer lookup at intake, not inferred, so the climatology is fetched for the actual pad wherever the name resolves.
Clearness index comes from the site's own NASA POWER climatology where coordinates are known, and from a monthly regional preset otherwise — the report and the Lab both say which. Hour angle is solar time: no correction is made for the offset between local clock time and solar noon, worth at most a few percent of daily energy and far smaller than the clearness assumption.
Passing clouds are modelled, and a construction array is treated as a point sensor. At this scale that is the defensible choice: the dispersion factor for a 50–200 m array at a two-minute step and realistic cloud speeds is far below unity, so there is effectively no spatial smoothing, and a 200 kW array dilutes a measured irradiance peak by only about 2% against a point pyranometer. Utility-scale variability-reduction factors do not apply here and are not used.
Transient depth survives the two-minute step. The 99.7th-percentile swing in clear-sky index at a single site is 0.58 at one minute, 0.59 at ten, and 0.60 at sixty (Mills & Wiser, LBNL-3884E, 23 synchronized sites). A cloud edge completes its swing in well under a minute, so a two-minute step loses the shape of a transient but keeps almost all of its depth. That is the evidence that two minutes is an honest resolution for dispatch, and equally the reason it is the wrong resolution for a ramp-rate or frequency-response study.
Variability peaks at intermediate-to-high clearness, not at the cloudiest weather (Stein, Hansen & Reno, SAND2012-3464C). Broken cumulus is the worst case: a clear sky has nothing to pass in front of the sun, and an overcast one is diffuse-dominated and steady, merely low. Because that relationship is an upper bound rather than a value, the day's intensity is sampled beneath the envelope — a given clearness can produce a calm day or a wild one, as the measurements show.
Shadow durations follow a power law, exponent −1.64, from ten years of one-second irradiance at Cabauw (Mol et al., JGR Atmospheres, 2023) — within a percent of Kolmogorov's −5/3. This matters more than any average: a memoryless spell length makes nearly every shadow span a full step, which overshot the measured frequency of large steps threefold. The power law puts most shadows below the step length, where they dim a step partially rather than halving it.
Depth puts the shaded floor at 15–30% of clear sky. Diffuse light is why output does not fall to zero under cumulus.
The factor is mean-preserving. The monthly clearness already encodes average cloudiness, so a cloud model that only subtracted would double-count it and quietly under-produce against the site's own climatology. Clear gaps rise above 1 and shaded spells fall below it, capped at the clear sky plus the modest cloud-edge enhancement that survives two-minute averaging.
Calibration check: the modelled distribution of two-minute step changes gives 11.3% of steps above 0.10, 4.9% above 0.25, and 1.0% above 0.50, against a full year of one-second San Diego data block-averaged to comparable intervals (Lave, Kleissl & Arias-Castro, Solar Energy 86(8), 2012). Its standard deviation of 0.096 sits inside the published two-to-three-minute range across sites, from 0.074 in Japan to 0.184 at Oahu (IEA PVPS Task 14).
Storage
Round-trip efficiency is split evenly across charge and discharge. Each unit's charge power caps how fast the pack absorbs — which is why an undersized pack curtails midday solar it has no room to hold, and why night operations drive storage sizing harder than daytime demand does. Standby and thermal-management draw is applied continuously.
The pack always soaks surplus toward 100%. The asset's "ceiling" is the constant-voltage taper knee, not an absorption cap: above it, acceptance ramps linearly toward zero at full, which is what makes the last tenth of the pack slow to fill, exactly as the hardware behaves. The operator setpoints on the battery node govern called charge only — the gen-on SOC is the call-for-charge floor, and the charge ceiling is where grid and generator stop charging deliberately rather than burning fuel for trickle absorption in the taper region. Turning generator charging off couples the pack to solar entirely: the set still serves load, but never starts merely to top the pack up, and both SOC setpoints go inactive because they only ever bounded deliberate charging — solar was never subject to them. One exception, and it is engine protection rather than charge policy: a set already running to serve load will push surplus into the pack rather than sit below its minimum load fraction and wet-stack, so a small amount of generator-to-battery flow can appear with the toggle off.
Load model
A representative demand shape built from the profile's discrete loads — rated power, quantity, duty cycle, and diversity factor — not a per-device simulation. On non-work days only continuously-scheduled loads run at full, plus non-continuous critical loads at a 25% site-care level.
Demand varies at three timescales, and the variability moves energy without creating it. Each day's total is the scheduled total times a crew-intensity factor; within the day, a mean-reverting texture and short start transients redistribute that energy. The load-weighted mean of the deviation is removed, so a day's kilowatt-hours remain the profile you reviewed in step 2 while its peaks, load factors, and ramp rates show the movement a real site has.
Where the numbers come from, and where they do not:
Day to day — 8.5% coefficient of variation on working-day energy within a phase. This is the one clean measured figure in the literature: 1,113 ± 94.8 kWh/day across submetered weekdays at an Irish construction site (Hickey et al., Proceedings of the ICE — Engineering Sustainability 179(2), 2026, 15-minute data over 30 months). Seasonal and phase-to-phase swings are far larger and are carried by the profile's own phase structure, not by this factor.
There is no lunch dip. This is the obvious thing to model and the metered evidence says it does not exist. The same Irish submetering shows demand flat across working hours with no midday reduction, and instrumented Norwegian sites (Sweco for Klimaetaten Oslo, 2024, twelve sites) put the day's maximum at 11:00–12:00, because that is when electric plant goes on charge over the break. Crews stagger their breaks, and the equipment that dominates a site's demand does not eat lunch.
Shift ramps are an assumption, not a measurement. At 15-minute resolution the published profiles read as a step, so the ramp is kept to roughly half an hour — long enough to be physical, short enough not to invent energy movement the data does not show.
Short transients are modest by design. Modern tower-crane hoists are inverter-driven and do not draw locked-rotor current; the published sizing factor is 1.4–2× running power, not the 6–8× of a direct-on-line start. Measured crane peaks last on the order of ten seconds, so at a two-minute step they are largely averaged away rather than dominating.
A sanity check on the result: going from hourly to 10-minute metering raised observed site peaks by about 15% in the Oslo study, and the authors expect finer resolution to raise them further. The two-minute model puts the modelled peak roughly 20% above the scheduled peak, which is consistent with that direction and magnitude. The load-zone readout shows both figures so the difference is never hidden.
Sub-minute behaviour is still not resolved. Motor inrush and the instant of a welding strike live inside the two-minute step, so this model shows energy balance and staging, not instantaneous adequacy against real starting current. Equipment adequacy against inrush remains a separate calculation.
Reliability
"Load served" is a model output. Maintenance, derate, fuel contamination, and equipment failure are not modelled. It is not an uptime or availability guarantee.
Carbon
Diesel at 22.4 lb CO₂ per gallon, which cross-checks against the industry figure of 2.6 kg CO₂/L. Grid carbon defaults to 1.49 lb/kWh (eGRID HIOA) and should be set per site. Operational emissions only — equipment lifecycle carbon is not counted.
Asset Catalog
Every asset available to the planning tool, with the provenance of its numbers. Assets are JSON files validated against a published schema — adding a generator or BESS is a data change, not a code change.
