Development of Modelling Tool to Predict Carbon Credits for Biomass Co-fired Boilers
Co-firing is a well-known technology and biomass is a successful alternative to blend with coal, resulting in an effective reduction of emissions (carbon credits) in conventional coal power plants. The present work is focused on developing a comprehensive predictive tool to estimate carbon credits r...
| Main Author: | |
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| Format: | Thesis |
| Published: |
Curtin University
2016
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| Online Access: | http://hdl.handle.net/20.500.11937/48462 |
| _version_ | 1848758104370446336 |
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| author | Karunarathna, Harshani Manjula |
| author_facet | Karunarathna, Harshani Manjula |
| author_sort | Karunarathna, Harshani Manjula |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Co-firing is a well-known technology and biomass is a successful alternative to blend with coal, resulting in an effective reduction of emissions (carbon credits) in conventional coal power plants. The present work is focused on developing a comprehensive predictive tool to estimate carbon credits relevant to co-firing systems (non-existent in literature). In nutshell our model approach indicates, conventional boilers utilising low rank coals are best suited for co-firing with biomass to mitigate GHG emissions. |
| first_indexed | 2025-11-14T09:38:41Z |
| format | Thesis |
| id | curtin-20.500.11937-48462 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:38:41Z |
| publishDate | 2016 |
| publisher | Curtin University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-484622018-07-02T13:51:24Z Development of Modelling Tool to Predict Carbon Credits for Biomass Co-fired Boilers Karunarathna, Harshani Manjula Co-firing is a well-known technology and biomass is a successful alternative to blend with coal, resulting in an effective reduction of emissions (carbon credits) in conventional coal power plants. The present work is focused on developing a comprehensive predictive tool to estimate carbon credits relevant to co-firing systems (non-existent in literature). In nutshell our model approach indicates, conventional boilers utilising low rank coals are best suited for co-firing with biomass to mitigate GHG emissions. 2016 Thesis http://hdl.handle.net/20.500.11937/48462 Curtin University fulltext |
| spellingShingle | Karunarathna, Harshani Manjula Development of Modelling Tool to Predict Carbon Credits for Biomass Co-fired Boilers |
| title | Development of Modelling Tool to Predict Carbon Credits for Biomass Co-fired Boilers |
| title_full | Development of Modelling Tool to Predict Carbon Credits for Biomass Co-fired Boilers |
| title_fullStr | Development of Modelling Tool to Predict Carbon Credits for Biomass Co-fired Boilers |
| title_full_unstemmed | Development of Modelling Tool to Predict Carbon Credits for Biomass Co-fired Boilers |
| title_short | Development of Modelling Tool to Predict Carbon Credits for Biomass Co-fired Boilers |
| title_sort | development of modelling tool to predict carbon credits for biomass co-fired boilers |
| url | http://hdl.handle.net/20.500.11937/48462 |