Random Finite Sets Based Very Short-Term Solar Power Forecasting Through Cloud Tracking
Tracking clouds with a sky camera within a very short horizon below thirty seconds can be a solution to mitigate the effects of sunlight disruptions. A Probability Hypothesis Density (PHD) filter and a Cardinalised Probability Hypothesis Density (CPHD) filter were used on a set of pre-processed sky...
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| Format: | Thesis |
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Curtin University
2019
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| Online Access: | http://hdl.handle.net/20.500.11937/77126 |
| _version_ | 1848763818779344896 |
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| author | Barbieri, Florian Benjamin Eric |
| author_facet | Barbieri, Florian Benjamin Eric |
| author_sort | Barbieri, Florian Benjamin Eric |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Tracking clouds with a sky camera within a very short horizon below thirty seconds can be a solution to mitigate the effects of sunlight disruptions. A Probability Hypothesis Density (PHD) filter and a Cardinalised Probability Hypothesis Density (CPHD) filter were used on a set of pre-processed sky images. Both filters have been compared with the state-of-the-art methods for performance. It was found that both filters are suitable to perform very-short term irradiance forecasting. |
| first_indexed | 2025-11-14T11:09:30Z |
| format | Thesis |
| id | curtin-20.500.11937-77126 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:09:30Z |
| publishDate | 2019 |
| publisher | Curtin University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-771262019-12-05T05:36:15Z Random Finite Sets Based Very Short-Term Solar Power Forecasting Through Cloud Tracking Barbieri, Florian Benjamin Eric Tracking clouds with a sky camera within a very short horizon below thirty seconds can be a solution to mitigate the effects of sunlight disruptions. A Probability Hypothesis Density (PHD) filter and a Cardinalised Probability Hypothesis Density (CPHD) filter were used on a set of pre-processed sky images. Both filters have been compared with the state-of-the-art methods for performance. It was found that both filters are suitable to perform very-short term irradiance forecasting. 2019 Thesis http://hdl.handle.net/20.500.11937/77126 Curtin University fulltext |
| spellingShingle | Barbieri, Florian Benjamin Eric Random Finite Sets Based Very Short-Term Solar Power Forecasting Through Cloud Tracking |
| title | Random Finite Sets Based Very Short-Term Solar Power Forecasting Through Cloud Tracking |
| title_full | Random Finite Sets Based Very Short-Term Solar Power Forecasting Through Cloud Tracking |
| title_fullStr | Random Finite Sets Based Very Short-Term Solar Power Forecasting Through Cloud Tracking |
| title_full_unstemmed | Random Finite Sets Based Very Short-Term Solar Power Forecasting Through Cloud Tracking |
| title_short | Random Finite Sets Based Very Short-Term Solar Power Forecasting Through Cloud Tracking |
| title_sort | random finite sets based very short-term solar power forecasting through cloud tracking |
| url | http://hdl.handle.net/20.500.11937/77126 |