P r o m o t i n g E n e r g y C o n s c i o u s B e h a v i o u r
175
Summary and discussion
According to hourly, daily, weekly energy usage patterns, we can obtain the overall
energy consumption profiles and derive the occupants’ lifestyle as follows:
•
The energy consumptions for electricity between working days and non-working days
(public holidays but not school holidays) have different patterns. The energy
consumption during working days is much less than that of public holidays but is very
close to the usage in school holidays. This demonstrates that the children were not at
home or only used low power electricity appliances at home. The gas consumption is
affected by the season (e.g. winter or cold weather) rather than whether it is working
days or non-working days. During the winter, the gas consumption is higher than that
of other seasons. The gas consumption has less correlation with working days or non-
working days. There is not much difference on water consumption between working
days and non-working days.
•
From hourly energy analysis, the family gets up at 7:00am and sleeps about 11:00pm.
There is a peak usage around 9:00am-10:00am in their working days, which could
reflect the couple’s working time is slightly later than other people’s normal working
time (e.g., 8:30 am -9:00 am). The electricity and water consumptions during public
holidays between 11:00am-15:00pm are higher than other time. Especially, the
electricity consumption keeps high until 24:00pm. This shows the family stays at
home during the public holidays.
•
The predictions of energy consumption based on ANN could provide the guidance for
their future energy usage.
This information above could be fed to the family and make them aware of what the
energy usage patterns are and how they could use the current usage patterns and
predictions to make adjustment about their lifestyles.
To provide more detail feedbacks to users, it is necessary to survey the behaviours of
the occupants, for example, whether they leave their appliances standby even if without
using them, etc. Additionally, it is also necessary to have more households’ energy
consumption monitored, which could provide a more general guidance in promoting
energy conscious behaviours. This has been put in our future plan.
Conclusion and Future work
In this paper, we have performed analysis of energy usage patterns collected from a real
household from Scotland where a real time monitoring system for electricity, water and
gas consumption has been installed. The results of analysis demonstrate that the energy
usage patterns have correlation with occupants’ lifestyles (such as presence and
behaviours). In this study, the electricity and water consumptions are closely linked with
whether occupants present or not. While gas consumption is highly related to the
seasons and is affected by outdoor temperatures. We have also identified peak usage
patterns and used neural networks to illustrate the predictions in working days and
holidays. This could be fed to the family for creating an energy saving plan and
promoting their energy conscious behaviours.
Our future work will use the analysis of energy consumption in this work as a benchmark
and compare it against the energy usage in the new ZEMCH house to understand how
sustainable the new build is. Additionally, we will also collect the data related to human
behaviours in order to provide depth insights about promotion of energy conscious
behaviours for the whole society.
