What is an interval observation?
Interval data is a time series of quantities measured or assigned over specified steps, with units, timestamps, and a defined account or meter boundary.
The observation is not meaningful as a standalone number. A value of forty could mean forty kWh within an interval, forty kW of average power, or another documented quantity. The file’s definition determines the interpretation. Read units before sorting values or labeling the largest entry a demand peak.
The DOE utility-rate resource describes interval information and load magnitude versus shape. It also notes that such data may not be available for every site. Confirm what the hotel’s utility or meter system provides rather than assume every account has an identical export.
How does a load profile differ from the raw file?
A load profile is a representation of how energy demand or consumption varies over time for a stated account, group, or modeled case.
A profile can display actual intervals, an average weekday, seasonal patterns, a forecast, or an assigned shape. The label profile does not establish which method produced it. Ask whether values were measured, averaged, estimated, modeled, or allocated and retain that description with the chart.
The bills hub connects this distinction to invoice interpretation. A modeled profile can support an explicitly qualified analysis; it cannot be presented as proof that the hotel’s laundry or cooling plant was operating at a particular observed time.
| Field | What it establishes | Error it helps prevent |
|---|---|---|
| Units | Energy, power, or another quantity | kWh treated numerically as kW |
| Duration | Length of each observation | Incorrect power conversion |
| Timestamp convention | Start/end label and time basis | Price or peak aligned to the wrong interval |
| Meter boundary | Which equipment and accounts are included | Incomplete or duplicated property totals |
| Quality status | Actual, estimated, corrected, or missing | Unsupported certainty from incomplete records |
| Coverage period | Actual start and end of the dataset | Calendar-month totals compared with different billing dates |
How are kWh and kW related in an interval?
The EIA electricity-measurement explanation distinguishes power from energy over time. Average power equals energy divided by duration, using consistent units. The conversion does not establish instantaneous startup power or the tariff’s final billing demand.
For a hypothetical fifteen-minute interval containing 45 kWh, duration is 0.25 hours and average power is 45 ÷ 0.25 = 180 kW. If forty-five represented a documented kW average instead, the corresponding quarter-hour energy would be 45 × 0.25 = 11.25 kWh.
These are teaching observations, not actual hotel measurements. The different interpretations produce very different results. Preserve the source field definitions so another analyst can reproduce the calculation and identify whether the export already applied multipliers or conversions.
Why can aggregation hide a qualifying peak?
Assume four hypothetical fifteen-minute energy observations of 45, 30, 35, and 25 kWh. Their total over one hour is 135 kWh, making hourly average power 135 kW. The first quarter-hour averaged 180 kW, substantially above that hourly average.
If a relevant tariff uses a quarter-hour measurement, an hourly aggregation can lose information needed for that calculation. If the tariff uses another method, use its actual rule. The example does not establish a universal measurement interval or a billed peak for any particular hotel.
Retain raw observations before creating summaries. A daily chart can help communicate patterns, but accounting or engineering may need finer data. Do not discard the underlying file merely because a dashboard provides a convenient average-day visualization.
What timestamp conventions need to be checked?
Identify whether the timestamp marks interval start or interval end, whether time is local or another specified basis, and how daylight-saving changes are handled. Two files showing the same clock label may refer to different observations if their conventions differ.
For an assumed complete local day measured in fifteen-minute steps, a normal twenty-four-hour day contains ninety-six intervals. A local day with twenty-three or twenty-five hours under a daylight-saving convention can contain ninety-two or one hundred. Actual exports can use another convention, so verify documentation before calling extra or missing labels an error.
Price matching requires the same care. Read block-and-index and index pricing for calculations that depend on delivery periods or price observations. An off-by-one interval or time-zone mismatch can change the result without any error in the underlying meter measurement.
How should the hotel reconcile the file with an invoice?
Match meter identifiers and exact service dates first. Determine reading status and whether the invoice includes corrections, estimates, or documented adjustments. Sum only the applicable observations using the defined boundary, and record excluded or unavailable periods.
Check whether multiple exports cover the same meter and dates. A revised file may replace an earlier version rather than add new consumption. Keep a version history so combining records does not duplicate the same energy. Ask the utility or provider which version is authoritative for the review.
Use The Hotel Bill Teardown to preserve the reconciliation. Show the observed total, billed quantity, explained adjustments, and unresolved difference. A transparent residual is more useful than silently inserting data until the spreadsheet matches the invoice.
What should missing or estimated values look like?
Keep missing observations explicitly identified. A zero is a quantity, while missing describes absent information; they are not interchangeable. If the source estimates a value, preserve that status. If the analyst creates an estimate, identify its method and separate it from actual readings.
Assess whether the missing periods matter to the decision. A gap during a suspected peak can be consequential even if it represents a small share of annual hours. Likewise, a few missing high-price periods can affect an indexed calculation differently from a similar number of ordinary periods.
Do not present a filled or interpolated series as a complete measured record. It can be useful for a labeled model, but the uncertainty should remain visible in the output and any claimed result.
How can the profile connect to hotel operations?
Align intervals with room availability, occupied room-nights, weather, events, laundry, kitchens, cooling stages, and charging records. These observations can support a hypothesis about the profile. They do not prove a cause merely because two events occur around the same time.
Investigate representative weekdays, weekends, seasons, and unusual events. A hotel’s baseload and peak pattern can differ when rooms are offline or equipment changes. Label the operating period and avoid describing a renovation month as stabilized use without qualification.
The DOE measurement-and-verification guidelines describe using relevant interval information to evaluate load-management performance. The federal guidance supplies analytical context; it does not automatically prescribe a private hotel’s required method or establish its project result.
Which price and allocation calculations need more than a profile?
Interval data supplies quantities, but the agreement or tariff supplies the financial treatment. Pass-through charges can use other assigned quantities or cost records rather than raw meter values alone. A beautiful profile cannot establish a charge’s contractual authority.
Likewise, a lower observed peak is not automatically a lower capacity allocation or bill. Apply the relevant system hours, adjustment method, effective period, and supplier treatment where those mechanisms matter. Keep measured quantities separate from assigned billing quantities.
If a broker obtains data and compares supply offers, disclose its compensation method, including embedded adders or direct fees. The file supports the purchasing analysis; it does not establish that intermediary work is uncompensated or that a published energy price includes every retail component.
What should a reliable interval-data record preserve?
- Identify source, meter, account, coverage, and version.
- Record units, duration, multipliers, and timestamp conventions.
- Flag missing, estimated, and corrected observations.
- Reconcile quantities with matched service-period invoices.
- Keep raw data before aggregation or transformation.
- Document calculations and separate observed from modeled profiles.
- Retain operating context and unresolved limitations beside the result.
Interval data becomes useful when its meaning and quality are explicit. A load profile then becomes a defensible representation of that account or model, rather than a chart whose apparent precision exceeds the evidence behind it.