Business Electricity Interval Data Analyzer
Analyze business electricity interval data directly in your browser — load profiles, peak demand, data quality, load duration and what-if load scenarios.
CSV & XLSXNo uploadNo accountBrowser-only
kW or kWh · 5, 10, 15, 30 and 60-minute intervals · timezone- and DST-aware timestamps
Analyze your interval data
- 1 Map data
- 2 Check quality
- 3 Review analysis
- 4 Test scenarios
Drop a CSV or XLSX interval file here
Load a CSV or XLSX file, or try the sample dataset. You map the columns before analysis begins.
Files are read in your browser. Your meter file is not uploaded or sent to a server.
A built-in synthetic half-hourly year (Europe/London, 2024), read through exactly the same pipeline as your own file.
What this analyzer does
It reads a meter export of electricity interval readings, works out which columns hold the timestamp and the value, resolves those timestamps in the meter's timezone, and reports what the data actually contains before any figure is shown. See how to analyze your interval data.
From the normalized intervals it derives demand and energy summaries, chronological and sorted demand views, weekday and time-of-day patterns, and two what-if scenarios. The normalized intervals can be exported as CSV.
What you can analyze
- Load profile
- Average demand in kW for every metering interval, in chronological order.
- Maximum interval demand
- The highest interval average in the dataset, with the interval it occurred in.
- Load duration curve
- Interval demand sorted from highest to lowest, showing how long high demand persists.
- Weekday and time-of-day patterns
- A heatmap of demand by day of week and time of day, plus the highest intervals.
- Data quality
- Missing intervals, duplicate readings, cadence changes and ambiguous local timestamps.
- Demand-limit exposure
- How often and by how much demand exceeds a limit you choose, and the energy above it.
- Additional-load scenarios
- The effect of an extra load in kW over a chosen weekday and time window on demand and energy.
How interval calculations work
An interval kW figure is the average demand over that metering interval, not an instantaneous reading. Where a file holds kWh per interval, the energy is interpreted using the interval duration to give the equivalent average demand.
Intervals that are absent from the file stay absent: they are never interpolated or filled in. Local timestamps that are ambiguous or non-existent because of a daylight saving transition are never guessed — the analyzer reports them and asks how they should be resolved.
Supported data
- CSV and XLSX files
- A combined timestamp column or separate date and time columns
- kW average interval demand or kWh per interval
- 5, 10, 15, 30 and 60-minute intervals
- Start-stamped or end-stamped intervals
- Timezone-aware and DST-aware timestamps
- Explicit UTC offsets in the timestamp
Use cases
- Reviewing a site's demand profile before capacity planning.
- Checking how often demand would exceed a given limit.
- Testing the effect of an added electrical load such as a charger or a compressor.
- Checking interval-data completeness before using the data elsewhere.
Processing in your browser
Meter files are processed locally in your browser. The analyzer does not upload the meter file or the analysis results to a server, and normalized CSV exports are generated locally.
Loading this website itself still involves ordinary web requests for the page and its assets, as with any site.
Limitations
The analyzer does not provide electricity prices, tariff comparison, bill estimation, supplier comparison, solar sizing, battery sizing or demand forecasting.
Every figure reflects the meter data you supply, so results are only as accurate and complete as that file. Because all processing happens on your own machine, the speed of an analysis depends on your device.
Important behaviours are covered by the project's own regression cases — see the validation cases.