A plant design worked example
The key idea
A useful design comparison states what changed, what stayed fixed and why the result changed. This exercise follows that process for one constructed day.
This is a browser learning exercise with a small deterministic model. It is not a native Phasor engine run, a measured site or a validated plant design. Its downloadable JSON contains the assumptions and every hourly result so you can check the calculation. Use the plant design guide to apply the workflow in Phasor with your own supported inputs.
1. Declare the demand and resource
The load is 4 kW overnight, 8 kW during the working day and 14 kW in the evening. The precise hourly schedule uses nine hours at 4 kW, ten hours at 8 kW and five hours at 14 kW. That gives 186 kWh of daily demand and a 14 kW peak.
Solar resource is a constructed daylight curve, with a 900 W/m² noon peak. It is not associated with a location, time zone or weather year. Cell temperature is fixed at 40°C. The example uses the PV conversion model explained in solar PV output.
2. Simulate the baseline
The baseline has 24 kW DC solar, 40 kWh nominal battery energy, a 10 kW battery converter and a 12 kW backup generator. All scenarios start with 8 kWh stored energy. The battery operates between 10% and 90% SoC, with 95% one-way efficiency.
Before selecting the other cases, predict what the baseline will struggle with. The evening demand is larger than the generator rating. The battery must supply the difference, but its remaining energy also limits how long it can help.
24 kW DC solar · 40 kWh storage · 12 kW backup · 186 kWh daily demand
- Fuel used
- 30.23 L
- Unmet demand
- 2.56 kWh
- Final stored energy
- 4.00 kWh
- Demand
- Available solar
- Generator
Read the exact values
| Time / step | Demand | Available solar | Generator |
|---|---|---|---|
| 00:00 | 4.00 | 0.00 | 0.20 |
| 01:00 | 4.00 | 0.00 | 4.00 |
| 02:00 | 4.00 | 0.00 | 4.00 |
| 03:00 | 4.00 | 0.00 | 4.00 |
| 04:00 | 4.00 | 0.00 | 4.00 |
| 05:00 | 4.00 | 0.00 | 4.00 |
| 06:00 | 4.00 | 0.00 | 4.00 |
| 07:00 | 8.00 | 5.04 | 2.96 |
| 08:00 | 8.00 | 9.75 | 0.00 |
| 09:00 | 8.00 | 13.78 | 0.00 |
| 10:00 | 8.00 | 16.88 | 0.00 |
| 11:00 | 8.00 | 18.83 | 0.00 |
| 12:00 | 8.00 | 19.49 | 0.00 |
| 13:00 | 8.00 | 18.83 | 0.00 |
| 14:00 | 8.00 | 16.88 | 0.00 |
| 15:00 | 8.00 | 13.78 | 0.00 |
| 16:00 | 8.00 | 9.75 | 0.00 |
| 17:00 | 14.00 | 5.04 | 0.00 |
| 18:00 | 14.00 | 0.00 | 4.00 |
| 19:00 | 14.00 | 0.00 | 4.00 |
| 20:00 | 14.00 | 0.00 | 12.00 |
| 21:00 | 14.00 | 0.00 | 12.00 |
| 22:00 | 4.00 | 0.00 | 4.00 |
| 23:00 | 4.00 | 0.00 | 4.00 |
- Stored energy
Read the exact values
| Time / step | Stored energy |
|---|---|
| 0 h | 8.00 |
| 1 h | 4.00 |
| 2 h | 4.00 |
| 3 h | 4.00 |
| 4 h | 4.00 |
| 5 h | 4.00 |
| 6 h | 4.00 |
| 7 h | 4.00 |
| 8 h | 4.00 |
| 9 h | 5.66 |
| 10 h | 11.15 |
| 11 h | 19.59 |
| 12 h | 29.09 |
| 13 h | 36.00 |
| 14 h | 36.00 |
| 15 h | 36.00 |
| 16 h | 36.00 |
| 17 h | 36.00 |
| 18 h | 26.57 |
| 19 h | 16.05 |
| 20 h | 5.52 |
| 21 h | 4.00 |
| 22 h | 4.00 |
| 23 h | 4.00 |
| 24 h | 4.00 |
| Quantity | Baseline | More storage | More solar |
|---|---|---|---|
| PV rating · kW DC | 24.00 | 24.00 | 36.00 |
| Battery capacity · kWh | 40.00 | 80.00 | 80.00 |
| Fuel · L | 30.23 | 24.28 | 22.63 |
| Unmet demand · kWh | 2.56 | 0.00 | 0.00 |
| Curtailed solar · kWh | 32.28 | 3.15 | 67.58 |
| Final stored energy · kWh | 4.00 | 8.00 | 14.70 |
| Battery losses · kWh | 3.48 | 6.12 | 6.23 |
Model note · Constructed browser exercise, model teaching-2026-09-10-v1. Each scenario starts with 8 kWh stored. Full inputs, assumptions and hourly outputs are in the downloadable JSON. This is not a native Phasor simulation.
The baseline leaves 2.56 kWh of demand unmet, curtails 32.28 kWh of available solar and uses 30.23 litres of generator fuel. It finishes with 4.00 kWh stored. The coexistence of unused midday energy and evening shortage is the reason to examine storage.
3. Increase storage, keeping solar fixed
Select More storage. Battery capacity rises to 80 kWh, while PV rating and converter power stay fixed. Initial stored energy remains 8 kWh: the comparison does not give the larger battery extra starting energy. Its initial SoC is therefore 10%, rather than the baseline's 20%.
The larger store captures more of the daytime surplus. Unmet energy falls to zero for this constructed day. Curtailment falls to 3.15 kWh, fuel is 24.28 litres, and the battery ends with 8.00 kWh stored.
This is a result for this input day and control model. It does not establish year-round reliability or a least-cost battery size. The converter still has the same 10 kW limit.
4. Add solar to the larger battery
Select More solar. PV capacity rises from 24 to 36 kW DC; storage remains 80 kWh. Fuel falls to 22.63 litres, while curtailment rises to 67.58 kWh. The battery ends with 14.70 kWh stored, more than in the previous case.
The extra PV increases potential output, but the load, charging limits and storage headroom determine how much can be used. A larger array does not produce an equal percentage reduction in fuel. This case also retains more energy for a later period, so fuel alone does not describe the full comparison.
5. Check the accounting before the conclusion
The math, if you want itOptional — the page reads completely without it
Every hour, the bus balances:
hourly power balance
Psolar + Pgen + Pdischarge = Pserved + Pcharge + Pcurtailed
with demand equal to served load plus unmet demand. Over the day, the initial stored energy joins the sources and the final stored energy joins the destinations:
daily energy balance
Esolar + Egen + Estored,0 = Eserved + Ecurtailed + Estored,24 + Elosses
For the baseline both sides total 223.21 kWh. The calculation tests this identity at full precision before rounding the totals for display.
The generator uses the illustrative affine fuel curve from diesel dispatch strategies. There is no cost model in this exercise. Multiplying one-day fuel by 365 would hide weather variation, changing demand and unequal ending storage states.
Reproduce the exercise
Download the JSON above. Its receipt names teaching-2026-09-10-v1, the model source, all assumptions, each scenario's capacity and the complete 24-hour output tables. The model is deterministic; it uses no random numbers or external data fetch. Reset returns the explorer to the baseline.
The JSON is a teaching data file, not a .phasor project. It cannot be imported as a native project. The native app demonstration and its screenshots are separate evidence of the product workflow.
What this model leaves out
The exercise has no electrical network, voltage, reactive power, faults or protection. It omits battery ageing, temperature-dependent storage behaviour, generator minimum-load constraints, minimum run times, start fuel, maintenance and reserve control. It uses a simplified load-following rule rather than the full Phasor dispatch implementation. There is no annual weather variation, cyclic end-state requirement, tariff or financial calculation.
See it in Phasor
Prepare location, demand and resource evidence. Save a design version, simulate the year, compare feasible alternatives and review the assumptions. Check network behaviour and finances using their own appropriate models.
Continue learning
Return to hybrid plant energy balance to inspect a single hour, or plant cost and LCOE to understand the separate economic calculation. The generation plant design path keeps the full sequence together.