Underwrite a car wash’s electricity cost by separating energy consumption, billed demand, fixed fees and other tariff components. Reconcile invoices with meter data and the applicable rate schedule, then model the buyer’s actual operating assumptions. A lower kWh forecast does not establish lower demand charges, and equipment savings should remain scenarios until their billing effect is supported.
- Distinguish kWh consumption from kW demand and billed quantities.
- Match invoices to the actual service account and tariff version.
- Review demand windows and any applicable look-back provisions.
- Keep proposed savings separate from historical verified earnings.
Which electricity costs belong to the acquired wash?
Define the business being bought and the accounts that serve it. Record which meters cover the wash, other businesses or shared site loads, since a property account may include costs outside the business being valued.
The valuation hub links this cost review to earnings and cash needs. Set the review period and the buyer’s proposed service terms before changing the model. An unexplained adjustment can turn a records gap into unsupported earnings.
Collect bills, payment evidence, account history and service agreements. Keep service dates apart from ledger dates and identify credits, estimated readings or later true-ups. Check for supply bills booked elsewhere or paid through a separate account; one annual expense total may omit part of the cost.
List each meter and account in the worksheet. Record shared-load splits and who checked them. The forecast should show the wash’s supported share without quietly charging the buyer for another business or excluding a cost the buyer must bear.
How do bill components and the tariff fit together?
Separate energy use in kWh, demand in kW and fixed fees before applying rates. The DOE utility-rate overview explains these broad bill components in a federal-facility context, not this wash’s actual tariff or promised savings.
Energy charges relate to use; demand charges follow a defined peak or billing rule. Do not multiply a demand rate by monthly kWh or treat a peak reading as all the energy used that month. Fixed fees follow the rate schedule rather than simply falling with use.
Obtain the actual tariff and supply terms, including effective dates and service class. Check whether supply and delivery are billed together or apart. Match bills to avoid counting a combined charge twice or missing separate supply charges.
EIA’s tariff-data FAQ says it does not publish utility tariff or demand-charge data. Its pointers to rate sources and utilities do not make an average price the site’s tariff. Ask the provider or qualified adviser about unclear terms and buyer eligibility; a cheaper rate online does not prove eligibility.
What do meter data and demand rules establish?
Request available interval data for the relevant meter and dates, retaining units, timestamps and gaps. Match measured peaks to the actual tariff calculation rather than treating the largest value in a download as billed demand under every tariff.
Use logs to check which loads ran during a peak. Blowers, pumps, building services or another site’s load may contribute, but nameplate ratings alone do not prove the meter result. Separate a proposed cause from one supported by readings.
Check whether the tariff uses a defined time window, a maximum regardless of time, prior peaks or another rule. Retain its thresholds and periods. A look-back rule can make billed demand depend partly on earlier peaks, so a lower peak now may not reduce every related charge now.
Date the calculation worksheet and seek review of unexplained gaps. If interval data are missing, keep that limit clear: monthly bills can still support expense, but may not prove simultaneous equipment use or savings from shifting a load. Do not force a preferred cost per car.
What does the fictional cost example show?
These invented rates and quantities show separate bill components for one hypothetical month. They are not an actual tariff, regional benchmark or forecast for a real wash, and include only the charges shown with the stated billed quantities.
| Scenario | Energy at $0.10/kWh | Demand at $12/kW | Fixed fee | Illustrated total |
|---|---|---|---|---|
| Baseline | 20,000 kWh: $2,000 | 100 kW: $1,200 | $100 | $3,300 |
| Lower energy, unchanged demand | 18,000 kWh: $1,800 | 100 kW: $1,200 | $100 | $3,100 |
| Unchanged energy, lower billed demand | 20,000 kWh: $2,000 | 80 kW: $960 | $100 | $3,060 |
The first change saves $200 from the shown total; the second saves $240. Neither result proves that an equipment project will cause the assumed change. Actual rates and measured results determine which billing quantities can change and when.
A ten-percent cut in energy use leaves demand and fixed fees unchanged in the first case. Read each component rather than applying that percentage to the total bill. Taxes, other fees and any rate changes would need their own supported inputs in a real forecast.
How should historical electricity expense be reconciled?
Match bills to the ledger and payment records for the review period. Identify accrual timing, credits, shared cost splits and missing bills, keeping supported past expense apart from a forecast with different rates or operations.
The IRS recordkeeping guidance explains records that support financial statements and reported income. It supports keeping bills and calculations, not approval of a demand adjustment or a technical savings claim. Keep source links clear so reviewers can reproduce the bridge.
The quality-of-earnings guide uses the same approach to earnings. A demand spike warrants review, but calling it a one-time expense requires evidence of its cause, resolution and relevance to the buyer. An unusual month alone does not establish that its cost disappears after sale.
Track each correction to its source account and period. Keep reviewed costs, gaps and proposed changes distinct. This avoids presenting a guess about a missing bill as a confirmed reduction in the wash’s annual operating expense.
How do changes in buyer operations affect the forecast?
State proposed changes in hours, wash activity, equipment and other loads. Map them to the buyer’s actual service terms and tariff, since a busier wash may affect energy use and peak demand in different ways.
Do not apply one growth percentage to every bill component without support. Show which quantities change and why, keeping fixed fees and tariff rules visible. New hours can change load timing and amount used.
Have qualified staff review plans to shift loads or change controls. Those plans may affect wash throughput, equipment needs or other operating limits. The model should not assume lower peaks come without an effect on service or the operating plan.
Show a base case and labeled alternatives where results remain uncertain. State which inputs come from signed terms, measurements or proposals, and what proof is still needed. Keep implementation dates clear so savings do not start before the plan is in place and billing rules allow the benefit.
How should efficiency projects affect earnings and value?
Separate project cost, measured energy effect, possible demand effect and timing. The equipment reserve guide links capital needs to the forecast, so savings should not be added while the cost needed to obtain them is omitted.
The add-back guide distinguishes expense adjustments from unproven future benefits. An upgrade plan should not erase past electricity expense or appear as both an add-back and a future cost cut. Keep the historical earnings bridge and buyer scenario apart.
Use actual quotes and operating evidence to frame the scenario. A manufacturer’s broad efficiency claim does not establish this site’s payback period. Include supported costs and the benefit under the relevant tariff over the stated period, rather than applying a machine-level percentage to the whole invoice.
Keep proposed savings labeled until the operating changes and measured results support them. Review capacity effects and implementation cost separately. Do not count the same reduction in both earnings and extra cash in the forecast.
What should the final underwriting file contain?
Retain account and meter IDs, reviewed bills, tariffs, available interval data and the dated worksheet. Name who resolved billing questions and which assumptions remain open, updating the file when provider replies or new readings change the conclusion.
- Confirm the acquired load boundary and all relevant accounts.
- Separate invoice components and reconcile quantities to tariff terms.
- Review demand periods, look-back provisions and available meter data.
- Model buyer operating changes and capital requirements explicitly.
- Preserve verified costs separately from unproven savings scenarios.
Link each forecast line to its source bill or assumption. Keep the historical period and buyer scenario dates clear. A later tariff update should be dated rather than silently replacing the terms used to explain past charges.
Show verified costs and savings still needing proof. This gives the buyer a clearer view of affordability than multiplying wash volume by a blended electricity number that hides peak-demand rules. Keep originals and earlier worksheets so reviewers can follow changes, rather than an unexplained final total.