Smart grid-demand side response model for optimization air conditioning
The growing demand of air-conditioning is one of the largest contributors to Australia's overall electricity consumption. This has started to create peak load supply problems for some electricity utilities particularly in Queensland. This research aimed to develop consumer demand side response...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference Paper |
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Institute of Electrical and Electronics Engineers ( IEEE )
2012
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| Online Access: | http://hdl.handle.net/20.500.11937/11312 |
| _version_ | 1848747772078981120 |
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| author | Marwan, M. Ledwich, G. Ghosh, Arindam |
| author2 | - |
| author_facet | - Marwan, M. Ledwich, G. Ghosh, Arindam |
| author_sort | Marwan, M. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | The growing demand of air-conditioning is one of the largest contributors to Australia's overall electricity consumption. This has started to create peak load supply problems for some electricity utilities particularly in Queensland. This research aimed to develop consumer demand side response model to assist electricity consumers to mitigate peak demand on the electrical network. The model developed demand side response model to allow consumers to manage and control air conditioning for every period, it is called intelligent control. This research investigates optimal response of end-user toward electricity price for several cases in the near future, such as: no spike, spike and probability spike price cases. The results indicate the potential of the scheme to achieve energy savings, reducing electricity bills (costs) to the consumer and targeting best economic performance for electrical generation distribution and transmission. |
| first_indexed | 2025-11-14T06:54:27Z |
| format | Conference Paper |
| id | curtin-20.500.11937-11312 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T06:54:27Z |
| publishDate | 2012 |
| publisher | Institute of Electrical and Electronics Engineers ( IEEE ) |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-113122017-02-28T01:33:30Z Smart grid-demand side response model for optimization air conditioning Marwan, M. Ledwich, G. Ghosh, Arindam - The growing demand of air-conditioning is one of the largest contributors to Australia's overall electricity consumption. This has started to create peak load supply problems for some electricity utilities particularly in Queensland. This research aimed to develop consumer demand side response model to assist electricity consumers to mitigate peak demand on the electrical network. The model developed demand side response model to allow consumers to manage and control air conditioning for every period, it is called intelligent control. This research investigates optimal response of end-user toward electricity price for several cases in the near future, such as: no spike, spike and probability spike price cases. The results indicate the potential of the scheme to achieve energy savings, reducing electricity bills (costs) to the consumer and targeting best economic performance for electrical generation distribution and transmission. 2012 Conference Paper http://hdl.handle.net/20.500.11937/11312 Institute of Electrical and Electronics Engineers ( IEEE ) restricted |
| spellingShingle | Marwan, M. Ledwich, G. Ghosh, Arindam Smart grid-demand side response model for optimization air conditioning |
| title | Smart grid-demand side response model for optimization air conditioning |
| title_full | Smart grid-demand side response model for optimization air conditioning |
| title_fullStr | Smart grid-demand side response model for optimization air conditioning |
| title_full_unstemmed | Smart grid-demand side response model for optimization air conditioning |
| title_short | Smart grid-demand side response model for optimization air conditioning |
| title_sort | smart grid-demand side response model for optimization air conditioning |
| url | http://hdl.handle.net/20.500.11937/11312 |