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Christchurch which has its own residential feeder. There are no retail, commercial or
industrial load on this feeder. It was selected to make it possible to compare the
modelling results with the actual load measured by the utility.
F 1 F 2 F 3 F 4 Lateral Line 1
Residential
Feeders
Lateral Line 2
Distribution
Transformer
Customers/
H 1 H 2 H 3 ... H N
Households
A 1 A 2 A n Appliances
A 1 A 2 A n A 1 A 2 An
Figure 2: Illustration of the modelling approach for a group of customers
Table 1: Maximum 30 minutes average diversified demand per customers (kW) for
given number (n) of appliance [Gönen, 2008].
Appliances n=1 n=5 n=10 n=20 n=40 n=80 n=100
Direct Water Heater 1.1 0.37 0.22 0.18 0.14 0.1 0.1
Heat Pump 4.50 3.00 3.00 2.80 2.80 2.80 2.80
Electric Heater 7.00 4.00 3.50 3.20 3.20 3.20 3.20
Cloth Dryer 4.30 1.80 1.50 1.20 1.00 1.00 1.00
Home Freezer 0.30 0.13 0.10 0.08 0.08 0.08 0.08
Refrigerator 0.18 0.07 0.06 0.05 0.05 0.05 0.05
Range 2.30 0.90 0.70 0.60 0.50 0.50 0.50
Lighting & Misc. 1.10 0.65 0.60 0.55 0.52 0.52 0.52
The total number of each appliance category (n i ) was determined by multiplying the
total number of households (m = 400 in this case) by the appliance saturation rates
(s i ). The appliance saturation rates for New Zealand [Electricity-Commission, 2007]
were used for the location. The saturation rate of heat pumps was taken from a recent
BRANZ study [French, 2008] . The saturation rate of electric heaters was adjusted to
reflect the situation at the Halswell area. Halswell is a relatively new suburb in
Christchurch with high penetration of heat pumps. The saturation rate of electric
heater is expected to be lower than the New Zealand average as space heating is done
mainly with heat pumps. Table 2 Shows the average maximum diversified demand
estimated for 400 households in Halswell, neighbourhood in Christchurch.
Estimation of the hourly variation factor, fi(t)
The hourly variation factors, fi(t) reveal the behaviour characteristics of appliance
usage and depends on the living habits of the individuals in a particular location.
These living habits in turn are affected by the socio-economic factors such as the
number of occupants in the individual households, their age and income. The hourly
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