A neural approach for estimation of per capita electricity consumption due to age and income

Electricity consumption is influenced by number of adults and children and their relationship at household level. Household income also plays a critical role on expenditure on electricity. Accordingly, this article presents a joint probability model of electricity demand based on occupants’ age grades and household income levels. A bottom-up strategy is developed using a micro level database of 70 Australian households. A neural regression-generalization technique is devised to estimate electricity demand using back-propagation and cognitive mapping. The aggregated result is then validated against 2012 Australian national census. Accordingly, the model is improved based on a top-down review. The results show per capita electricity demand by adult and child at 0.408 kW (69 kWh/week) and 0.226 kW (38 kWh/week), respectively. The equivalent dollar values are $13.6/week and $7.6/week in 2012. At macro level, the model reveals per capita demand by all individuals at 0.324 kW (54.35 kWh/week) equivalent to dollar value of $10.87/week, across Australia. The results also show higher percentage of per capita demand for adults in high and medium income classes, and the otherwise for low income class. Ratio of child’s demand over adult’s demand is highest among the low income households, and lowset among the middle income households, while best balance between adult and child per capita demand belongs to the high income.