For existing installations, actual metered data provides the most accurate maximum demand determination. This data should be averaged over appropriate demand intervals to eliminate transient effects.
Then came the era of Diversity.
VA (Single-Phase)=Voltage (V)×Current (A)VA (Single-Phase) equals Voltage (V) cross Current (A) maximum demand calculation
Elias pointed to a specific formula on the screen: $$ \textDiversity Factor = \frac\textSum of Individual Maximum Demands\textMaximum Demand on the Station $$
Approximate result: After applying allowed demand factors, the estimated maximum demand is roughly , far lower than the 24 kW connected load. For existing installations, actual metered data provides the
From a utility billing perspective, maximum demand is nearly always expressed in kVA (kilovolt‑amperes) because it reflects the total apparent power that the network must deliver, which is a function of both real power (kW) and power factor:
A customer with a 300 kW load at 0.6 PF presents a 500 kVA demand—a much heavier burden on the utility. Consequently, MD calculations increasingly incorporate power factor penalties or incentives. In practice, modern digital meters use methods
In practice, modern digital meters use methods. They sample current and voltage continuously, calculate instantaneous power, and then apply a thermal or averaging algorithm that mimics the heating effect of current in a conductor—since the true concern of maximum demand is thermal loading of transformers, cables, and switchgear. The most common algorithm is the block interval demand (sliding window), though thermal demand (exponential averaging) is also used for certain applications.
A decimal (e.g., 0.4 to 0.9) based on the type of load. For example, lighting has a high diversity factor (often 0.9) because many lights are on at once, while power outlets have a lower factor (0.4) because most are unused at any given time.
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