Analysis of Energy Behaviour Profiles of Prosumers
dc.contributor.author | Potdar, Vidyasagar | |
dc.contributor.author | Rathnayaka, A. | |
dc.contributor.author | Dillon, Tharam S. | |
dc.contributor.author | Hussain, Omar | |
dc.contributor.author | Kuruppu, S. | |
dc.contributor.editor | IEEE | |
dc.date.accessioned | 2017-01-30T13:46:55Z | |
dc.date.available | 2017-01-30T13:46:55Z | |
dc.date.created | 2013-01-03T20:00:26Z | |
dc.date.issued | 2012 | |
dc.identifier.citation | Rathnayaka, A.J.D. and Potdar, V.M. and Dillon, T. and Hussain, O. and Kuruppu, S. 2012. Analysis of Energy Behaviour Profiles of Prosumers, in 10th IEEE International Conference on Industrial Informatics (INDIN), Jul 25-27 2012, pp. 236-241. Beijing, China: Institute of Electrical and Electronics Engineers (IEEE). | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/34985 | |
dc.identifier.doi | 10.1109/INDIN.2012.6301138 | |
dc.description.abstract |
Smart Grid (SG) achieves bidirectional energy and information flow between the energy user and the utility grid, allowing energy users not only to consume energy, but also to generate the energy and share the excess energy with the utility grid or with other energy consumers. This type of energy user iscalled the “prosumer”. In current society, a massive number of energy-users have transformed into prosumers due to many reasons such as the strong society attitude with respect toalleviation of negative climate impacts, desires to decrease electricity costs, and various government regulations, including generous feed-in tariff schemes. This leads much attention withinthe research community on investigating the aspects of prosumers connected to SG. However most researchers find it challenges to find a large dataset of prosumers for performing the experiments. This leads the necessity of identifying the generic prosumers’ realistic energy behaviors, and accordingly generates a synthetic dataset. In this research paper, we present prosumers’ realistic energy behavior profiles during summer and winter periods in Australia and present its application in generating a synthetic dataset. The new researchers can use the identified energy profiles as a benchmark to generate a synthetic dataset for their experiments. | |
dc.publisher | Institute of Electrical and Electronics Engineers ( IEEE ) | |
dc.subject | smart grid | |
dc.subject | prosumer | |
dc.subject | feed-in tariff | |
dc.subject | energy profile | |
dc.title | Analysis of Energy Behaviour Profiles of Prosumers | |
dc.type | Conference Paper | |
dcterms.source.startPage | 236 | |
dcterms.source.endPage | 241 | |
dcterms.source.title | 10th IEEE International Conference on Industrial Informatics | |
dcterms.source.series | 10th IEEE International Conference on Industrial Informatics | |
dcterms.source.isbn | 978-1-4673-0312-5 | |
dcterms.source.conference | INDIN 2012 | |
dcterms.source.conference-start-date | Jul 25 2012 | |
dcterms.source.conferencelocation | Beijing China | |
dcterms.source.place | China | |
curtin.department | ||
curtin.accessStatus | Fulltext not available |