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S Bhasker Nair, Purusothmn Nair (2022) Optimal deployment of negative emissions technologies for sustainable energy planning with process integration techniques. PhD thesis, University of Nottingham Malaysia.

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Abstract

It is critical to limit global warming to within 1.5 °C by year 2100 to minimise catastrophic impacts. The increased deployment of renewable energy sources, alongside CO2 capture and storage (CCS) in energy planning, remains a key mitigation technique in minimising climate change impacts. Although the generation of renewable energy sources approaches the state of a carbon-neutral system, other processes such as fossil fuel-based generation, manufacturing, and transportation are net-carbon positive. Additionally, renewable energy sources pose challenges such as their sensitivity to environmental conditions, geographical locations, and seasonal changes. On the other hand, CCS systems entail a high capital expenditure, as well as additional operating costs due to parasitic power losses. Therefore, the deployment of negative emissions technologies (NETs) as a carbon management option is imperative. The generation of electricity from power plants with the installation of NETs can offset positive emissions from elsewhere in a system. Despite the lack of technological maturity of NETs, their full-scale deployment is expected to take place within the next few decades. Potential interactions with energy infrastructures need to be considered during scale-up. Therefore, this research focuses on the optimal deployment of NETs alongside renewable energy sources and CCS in efforts to mitigate climate change impacts. In this thesis, several techniques based on Carbon Emissions Pinch Analysis (CEPA) are developed for carbon-constrained energy planning (CCEP). Initially, an extended graphical targeting technique is developed for the deployment of energy-producing NETs (EP-NETs) during energy planning. The graphical targeting technique that was originally developed for the planning of CCS deployment in power plants is now extended to determine the minimum deployment of EP-NETs during energy planning. Next, a graphical targeting technique is developed for the deployment of energy-consuming NETs (EC-NETs) for sustainable energy planning. This graphical targeting technique demonstrates the usefulness of EC-NETs for an effective carbon management strategy. However, the energy demand of EC-NETs requires compensation from additional renewable energy sources. This compensation can be reduced with the deployment of CCS. On the other hand, the deployment of EC-NETs coupled with EP-NETs eliminates the need for renewable energy sources as compensatory power, as the latter is supplied by EP-NETs. Besides, a generic algebraic targeting technique is developed for the deployment of renewable energy sources, CCS and NETs, to eliminate the iterative procedure of the graphical targeting technique. Lastly, a multiperiod energy planning model making use of the combined automated targeting model (ATM) and superstructural models is developed to determine the optimum deployment of energy sources for CO2-intensive industries other than the power generation sector. This research demonstrated the importance of NETs, CCS, and renewable energy sources in mitigating climate change impacts. The systematic methodology developed in this research can assist the future decarbonisation of various CO2-intensive processes.

Item Type:	Thesis (University of Nottingham only) (PhD)
Supervisors:	Foo, Dominic Chwan Yee Chemmangattuvalappil, Nishanth G. Tan, Raymond R.
Keywords:	carbon-constrained energy planning, negative emissions technologies, carbon dioxide removal, pinch analysis, automated targeting model, superstructural model, mathematical optimisation
Subjects:	T Technology > TD Environmental technology. Sanitary engineering
Faculties/Schools:	University of Nottingham, Malaysia > Faculty of Science and Engineering — Engineering > Department of Chemical and Environmental Engineering
Item ID:	69460
Depositing User:	S Bhasker Nair, Purusothmn
Date Deposited:	24 Jul 2022 04:40
Last Modified:	31 Dec 2022 04:30
URI:	https://eprints.nottingham.ac.uk/id/eprint/69460

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