15-Minute Electricity Interval Data Analyzer

Analyze quarter-hourly business electricity data from CSV or XLSX. Check how timestamps, units and intervals have been interpreted before reviewing load profile, peak demand, data quality and what-if scenarios.

CSV & XLSX
kW or kWh
No account
Meter file processed in your browser

Analyze 15-minute data

What 15-minute interval data tells you

A monthly bill shows how much electricity a site used. 15-minute interval data shows when it was used: every quarter hour, around the clock, so you can see daily patterns, short peaks and how long high demand lasts.

A standard 24-hour day contains 96 fifteen-minute intervals. On daylight-saving clock-change days, the number of real elapsed 15-minute intervals can differ—for example, 92 or 100 where the clock shifts by one hour.

What a 15-minute file looks like

A typical export from a metering portal has, per row:

a timestamp — either one combined column or separate date and time columns
a value — kW average interval demand, or kWh per interval

CSV and XLSX files are supported. You confirm which columns hold the timestamp and the value, and how they should be read, before any figure is calculated. See interpreting intervals.

kW vs kWh in a 15-minute interval

15 minutes is 0.25 hours, so energy and average demand convert with a factor of four.

25 kWh ÷ 0.25 h = 100 kW average demand

100 kW × 0.25 h = 25 kWh energy

100 kW is the average demand during the interval, not necessarily the highest instantaneous demand inside that interval. See demand and energy.

Before you trust the chart, check the file

A chart can look plausible even when the file has been read wrongly. These are the points the analyzer checks and reports before showing results:

kW or kWh: A 15-minute kWh value is four times smaller than the equivalent kW average. Mapping the wrong unit scales every figure by four.
Start- or end-stamped: A reading stamped 00:15 can describe 00:00–00:15 or 00:15–00:30. The choice shifts every interval and can move a peak into a different day or month.
Missing intervals: Gaps are reported and left empty. Missing readings are never interpolated, so totals cover only the intervals actually present.
Exact duplicates: Rows repeated with an identical value are removed and reported.
Conflicting duplicates: The same timestamp with different values blocks analysis. The analyzer will not guess which reading is correct.
Malformed rows: A small number of unreadable timestamps or values can be excluded and reported; sufficiently high failure rates block analysis.
Cadence changes: If the file switches from 15-minute to another reading interval part-way through, analysis is blocked until you select one cadence segment.
Timezone: Local timestamps are interpreted in the meter timezone you select, including UTC.
Daylight-saving clock changes: Repeated local times during a fall-back transition are resolved automatically only when the sequence supports a unique cadence-consistent interpretation. Otherwise, the analyzer asks you to choose how the ambiguous readings should be handled rather than guessing. Local times that do not exist in a spring-forward gap are excluded rather than shifted.
Explicit UTC offsets: Timestamps that carry their own offset, such as +01:00, are treated as exact instants.

Precise rules are documented under data quality, timezones and daylight saving time and cadence changes, and the behaviour is covered by the validation cases.

What you can analyze

Total energy
Maximum interval demand
Average demand
Load factor
P95 and P99 demand
Peak-to-average ratio
Chronological load profile
Load duration curve
Monthly maximum interval demand
Weekday and time-of-day pattern
Top-demand intervals

The normalized intervals can also be exported as CSV. See summary metrics and percentiles and the load duration curve.

Peak-demand questions

The Peak Limit simulator compares every 15-minute interval with a demand limit you choose and answers:

How many intervals exceed the limit?
On how many days?
What is the largest overshoot?
How much energy occurs above the limit?
How many exceedance events occur, and how long is the longest?

It reports demand and energy only; it does not calculate tariffs or savings. See peak-limit analysis.

Testing a planned additional load

The Additional Load simulator adds a recurring kW load during local times and weekdays you select — for example EV charging, new equipment, a compressor, a process load or an electrification project — and shows the resulting demand and energy alongside the original data.

It is not an electrical load-flow study, network capacity certification, tariff calculation or battery sizing. See additional-load scenarios.

Limitations

Interval-average demand is not instantaneous demand.
Missing intervals are not invented.
No tariff or bill calculation.
No solar sizing, battery sizing or power-factor analysis.
No connection to utility APIs; you supply the file.
Green Button XML, NEM12 and cumulative meter-register readings are not supported.

See interpretation limits.

Frequently asked questions

What is 15-minute electricity interval data?

A meter export with one reading for every quarter hour: a timestamp and either the average demand in kW or the energy in kWh for that interval. A standard day has 96 readings.

Is a 15-minute kW value instantaneous power?

No. It is the average demand over the 15 minutes. Demand inside the interval may have been higher or lower at any moment.

How do I convert 15-minute kWh to kW?

Divide by 0.25 hours, which is the same as multiplying by four: 25 kWh in 15 minutes is an average of 100 kW.

Can the analyzer use end-stamped 15-minute readings?

Yes. You choose whether timestamps mark the start or the end of each interval when mapping the file.

What happens during daylight-saving clock changes?

Spring-forward gaps are excluded, not shifted. Repeated fall-back times are resolved automatically only when a unique cadence-consistent reading exists; otherwise you are asked how to handle them.