Ni, Chenyixuan (2024). Design and modelling of the clean energy router with advanced adiabatic compressed air energy storage system. University of Birmingham. Ph.D.
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Ni2024PhD.pdf
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Abstract
The advanced adiabatic compressed air energy storage (AA-CAES) technology naturally has the flexibility of multi-energy storage and supply, which is discussed in this doctoral study as a demand for the current power system to provide more flexibility under the high proportion of sustainable consumption of renewable energy. The clean energy router (CER) can be suggested as a scheme based on the properties of AA-CAES. This thesis systematically studies the design, modelling, and operation methods of AA-CAES typical application forms, providing technical support for the operation control optimization planning of modern power systems (MPSs).
An overall architecture scheme of the CER based on AA-CAES is constructed to store and convert abandoned wind and solar energy to heating, cooling, and electricity, it offered a crucial technical solution for coordinating and fully utilizing a variety of clean energy sources. The thermodynamic model of AA-CAES can also be used to examine the CER scheme efficiency and transformation mechanism.
Based on the CER with high-temperature medium thermal storage and high-speed turbine power generation, a solar thermal collection and storage (STC) can be integrated to use the natural solar energy to further improve the overall efficiency. Combining the STC technology with AA-CAES, it can improve the capacity of multi-energy storage and supply. From the aspect of system design, it can ensure the flexible multi-energy storage joint supply capacity and high energy conversion efficiency of the system. Exergy efficiency can be applied to reflect the efficiency of the system to further analyze the performance of each subsystem and the overall system. For the economy of the system, an artificial intelligence algorithm – particle swarm optimization algorithm (PSO) is applied to obtain the minimum cost of the system through multi-objective optimization of heat and power supply units.
| Type of Work: | Thesis (Doctorates > Ph.D.) | |||||||||
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| Award Type: | Doctorates > Ph.D. | |||||||||
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| Licence: | All rights reserved | |||||||||
| College/Faculty: | Colleges (2008 onwards) > College of Engineering & Physical Sciences | |||||||||
| School or Department: | School of Engineering, Department of Electronic, Electrical and Systems Engineering | |||||||||
| Funders: | Engineering and Physical Sciences Research Council | |||||||||
| Subjects: | Q Science > Q Science (General) Q Science > QC Physics T Technology > TK Electrical engineering. Electronics Nuclear engineering |
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| URI: | http://etheses.bham.ac.uk/id/eprint/14445 |
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