30-minute interval data records the electricity used in each half-hour — 48 readings per day, 17,520 per year. Each interval’s kWh multiplied by two gives the average kW in that half-hour. From this profile you can see base load (what runs at night), peak demand (which often drives demand charges on South African business tariffs), time-of-use cost, and waste such as equipment left on after hours.
What the data looks like
Each row is a timestamp and the energy used during that interval, usually with reactive energy as well:
| Interval ending | kWh | kvarh | Average kW | Average kVA |
|---|---|---|---|---|
| 08:00 | 42.5 | 18.0 | 85.0 | 92.3 |
| 08:30 | 61.0 | 24.5 | 122.0 | 131.5 |
| 09:00 | 64.5 | 26.0 | 129.0 | 139.1 |
Average kW is kWh ÷ 0.5 h. Average kVA combines active and reactive power: kVA = √(kW² + kvar²). Power factor is kW ÷ kVA — in the example, about 0.93.
Five things to look for
- Base load — consumption in the quietest hours (for example 01:00–04:00). A high base load in an office or shop usually means equipment, lighting or HVAC left running.
- Peak demand — the highest half-hour kVA or kW in the month. On many large-power business tariffs, demand charges are based on this single worst interval.
- Time-of-use split — how much energy falls in peak, standard and off-peak periods. Shifting flexible loads (pumping, charging, batch processes) out of peak reduces cost.
- Weekday vs weekend — weekend consumption close to weekday levels points to unnecessary running.
- Load factor — average demand ÷ peak demand. A low load factor means short, sharp peaks that are worth managing.
Common data problems
- Missing intervals from communication outages — they must be flagged or filled, never silently treated as zero.
- Spikes from counter resets or meter replacements.
- Daylight-saving shifts on imported data from other systems (not an issue for South African time, but common in international software).
- Wrong CT ratios, which scale every reading by the same wrong factor.
Turning data into action
The value comes from regular review and alerts: a weekly report of base load and peak demand per site, alerts when after-hours consumption exceeds a threshold, and a monthly comparison against the utility bill. Our energy monitoring platform automates these checks.