Thesis Topic Details

Topic ID:
3448
Title:
What does a dishwasher's power consumption actually look like?
Supervisor:
Salil Kanhere
Research Area:
Sensor Networks, Embedded Systems, Machine Learning
Associated Staff
Assessor:
Andreas Reinhardt
Topic Details
Status:
Active
Type:
R & D
Programs:
CS CE SE
Group Suitable:
Yes
Industrial:
Pre-requisites:
good understanding of computer networks and basic programming skills
Description:
Ongoing initiatives towards sustainability have led to an increased awareness of people about their electric energy consumption. As a result, people have begun to actively control the operation of certain appliances in their homes and workplaces in order to preserve energy. Still, energy consumptions of a large majority of devices go unnoticed, because people are not aware if and how these devices contribute to their overall energy consumption. In certain scenarios, deactivating electric devices may even lead to a larger energy consumption because the energy required to turn them on again significantly exceeds their continuous operating power, e.g. in the case of fluorescent lamps.

The objective of this topic is the collection and modelling of electric power consumption data for numerous appliances present in households and business environments, e.g. UNSW. The student(s) will therefore be provided with means to measure the power consumption, e.g. Plugwise Sting sensors (depicted above) or ammeters with computer interface. Further data will be made available from the Tracebase repository. Data should be collected for many different representative appliances during their activity phases. After collection, the data must be stored in a way such that it can be re-used easily at later times. In order to ensure the reliability of the data and avoid erroneous outliers, multiple activity peri-ods must be monitored for each appliance. As a side effect, students may use the sensor devices in their homes and gain insights on their personal energy consumption as well.

In the second part of the task at hand, the collected data shall be analysed with regard to the typical operating power characteristics of the monitored devices. This includes modelling the characteristics of the initial inrush power as well as during their steady-state operation. The approximation models should be optimised such that the discrepancy between actual and modelled consumption becomes minimal. A tool like MATLAB or GNU octave should be used to this end, but the student(s) can alternatively implement a similar functionality in Java. The outcome of this second part will be a compilation of appliance models, which describe their typical operating power consumptions. These descriptions have to be modelled in a way such that artificial traces can be generated based on these data.

The models created within the scope of this project will be used to create artificial power consumption traces for complete households for simulation purposes later. These traces will then be analysed, e.g. with regard to their energy optimisation potential and the possibility to detect individual appliances from aggregated power consumption data.
Comments:
Students should be eager to work on cutting-edge research topics and have a fundamental understanding of electric units and measurement techniques. Moreover, programming skills in MATLAB and/or Java are highly beneficial in order to complete the assigned task.

Creativity is very helpful for the selection of relevant parameters on which the models will be based. Furthermore, students should be open-minded and actively interested in talking to other researchers about possible solutions to their problem before starting to implement so-lutions. Interaction with facilities management will be necessary in order to attach sensors to larger appliances.
Past Student Reports
 
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