Chen, Peipei;
(2024)
Data-driven approaches to carbon emissions and mitigation strategies: a granular analysis of global power generation sector.
Doctoral thesis (Ph.D), UCL (University College London).
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Abstract
Addressing the climate crisis demands a focused push for a net-zero emissions energy transition, particularly through transforming the global power generation sector. This thesis contributes significantly to the discourse by offering a more detailed research perspective on the carbon emissions and mitigation strategies in the global power generation sector, with a particular focus on the level of individual power plant units. First, it characterised the unit-based carbon emissions of 223,789 global power plant units, examining generation units in both temporal and spatial dimensions. This granular examination facilitates a deeper understanding of emissions sources and patterns. Second, this thesis employs machine learning techniques to predict the future operational status of global power generation units across all technologies, thereby forecasting the future power generation structure of various countries. It notably identifies coalfired power plants as possessing the greatest stranded asset risk. Third, focusing on coal-fired power plants, this thesis provides specific decarbonisation strategies for improving the energy efficiency of each coalfired power plant unit using artificial neural networks and optimisation techniques based on the efficiency and engineering characteristics of the plant units. Finally, taking the emerging economies in the Asia-Pacific region as a case study, this thesis quantifies the contribution of their energy policies to aspects such as electricity access, energy intensity, renewable energy installed capacity, and the role of different energy types in the energy transition progress. These findings have valuable theoretical and practical implications. The data-driven approaches, coupled with detailed power plant unit features, provide a robust foundation for policy implication. Furthermore, the thesis explores emission mitigation strategies at the plant unit level, providing practical and nuanced measures for carbon emission reduction.
Type: | Thesis (Doctoral) |
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Qualification: | Ph.D |
Title: | Data-driven approaches to carbon emissions and mitigation strategies: a granular analysis of global power generation sector |
Language: | English |
Additional information: | Copyright © The Author 2024. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request. |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment |
URI: | https://discovery.ucl.ac.uk/id/eprint/10193067 |
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