Abstract
In this study the case of the energy consumption profile of the Aristotle University of Thessaloniki, in Greece, is presented and statistically analyzed by clustering methods on the basis of seasonal daily load curves and load shape factors, using data from real-Time measurements. The results indicate that the categorization of active power demand in university buildings is an extremely useful tool for understanding and predicting the seasonal, hourly and daily energy consumption changes, which is the first step towards adopting energy efficiency policies in such scale premises as well as performing demand-side actions aiming to achieve a more economical and environmentally sustainable energy usage.
Original language | English |
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Title of host publication | 2015 Australasian Universities Power Engineering Conference (AUPEC) :$bWollongong, Australia, 27-30 September 2015 : AUPEC2015 : Challenges for Future Grids /$chosted by the Australian Power Quality and Reliability Centre, University of Wollongong, Australia |
Place of Publication | Piscataway |
Publisher | Institute of Electrical and Electronics Engineers |
Number of pages | 5 |
ISBN (Electronic) | 978-1-4799-8725-2 |
DOIs | |
Publication status | Published - 10 Nov 2015 |
Externally published | Yes |
Event | 25th Australasian Universities Power Engineering Conference (AUPEC 2015) - University of Wollongong, Wollongong, Australia Duration: 27 Sept 2015 → 30 Sept 2015 Conference number: 25 |
Conference
Conference | 25th Australasian Universities Power Engineering Conference (AUPEC 2015) |
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Abbreviated title | AUPEC 2015 |
Country/Territory | Australia |
City | Wollongong |
Period | 27/09/15 → 30/09/15 |
Keywords
- Energy Efficiency
- Load Profiling
- Statistical Analysis
- Time Domain Clustering