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	<updated>2026-04-24T11:15:13Z</updated>
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		<id>https://projectswiki.eleceng.adelaide.edu.au/projects/index.php?title=Projects:2020s1-2522_Real-Time_Electricity_Greenness_Map_for_U-City_Building&amp;diff=14096</id>
		<title>Projects:2020s1-2522 Real-Time Electricity Greenness Map for U-City Building</title>
		<link rel="alternate" type="text/html" href="https://projectswiki.eleceng.adelaide.edu.au/projects/index.php?title=Projects:2020s1-2522_Real-Time_Electricity_Greenness_Map_for_U-City_Building&amp;diff=14096"/>
		<updated>2020-04-22T05:31:48Z</updated>

		<summary type="html">&lt;p&gt;A1226603: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;== Introduction == &lt;br /&gt;
&lt;br /&gt;
Electricity is a unique product that is consumed by the end-users in real-time without any awareness of the cost incurred and the impact it leaves behind. This has major consequences in terms of electricity prices and greenhouse gas emissions (GHG) both short-term and long-term. To that end, real-time information about the situation of the grid (financial and environmental) combined with the electricity consumption of the end-users might encourage consumers to adjust themselves to be more green or to help the grid to reduce electricity prices. This can be significant for a big community such as U-City. In this project, we will create a “real-time greenness map of electricity consumption” that will be displayed on public screens in U-City building. To create a meaningful and truthful greenness map, we design algorithms to learn the consumers’ electricity consumption patterns based on the data obtained from the U-City building management system. We also fetch real-time GHG emission data from the Australian Energy Market Operator and/or other reliable resources. In addition to a single greenness map for the building, specialised greenness maps will be created for the major appliances to provide a directive yet optional information to save GHG by altering electricity consumption. The performance of the greenness map on altering end-users’ consumption will be quantified based on historical data.&lt;br /&gt;
&lt;br /&gt;
== Project Team ==&lt;br /&gt;
&amp;#039;&amp;#039;&amp;#039;Students&amp;#039;&amp;#039;&amp;#039;&lt;br /&gt;
&lt;br /&gt;
* Thomas Lancione&lt;br /&gt;
* Langran Xie&lt;br /&gt;
&lt;br /&gt;
&amp;#039;&amp;#039;&amp;#039;Supervisors&amp;#039;&amp;#039;&amp;#039;&lt;br /&gt;
&lt;br /&gt;
* Ali Pourmousavi Kani&lt;br /&gt;
* Wen Soong&lt;br /&gt;
* Christoph Treude&lt;/div&gt;</summary>
		<author><name>A1226603</name></author>
		
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