Modelling and optimisation of energy systems with thermal energy storage
Item statusRestricted Access
Embargo end date04/07/2019
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One of the main challenges in the implementation of renewable energy is the mismatch between supply and demand. Energy storage has been identified as one of the solutions to the mismatch problem. Among various storage technologies, thermal energy storage (TES) is foreseen to have a significant role to achieve a low carbon energy systems because of the large share of thermal energy demand and its relatively low cost. However, integrating TES into energy systems requires careful design and implementation since otherwise potential financial and environmental savings may not be achieved. Computational-based design tools are ubiquitous in the design process of modern energy systems and can be broadly categorised into two methodologies: optimisation and simulation. In both cases, designing an energy system with storage technology is significantly more complicated than those without, mainly due to the coupling of variables between time steps. This thesis is concerned with two facets of the application of TES in energy systems. First, the role of TES in improving the performance of renewable-based domestic heating systems. Second, the implementation of optimisation and simulation tools in the design of energy systems with integrated TES. They are addressed by examining two case studies that illustrate the spatial and temporal variance of energy systems: a single dwelling heat pump system with a hot water tank, and a solar district heating system with a borehole thermal energy storage. In the single dwelling case study, the technical and financial benefits of TES installation in a heat pump system are illustrated by the optimisation model. A simulation model which utilises the optimisation results is developed to assess the accuracy of the optimisation results and the potential interaction between the two methodologies. The solar district heating case study is utilised to highlight the potential of a time decomposition technique, the multiple time grids method, in reducing the computational time in the operational optimisation of the system. Furthermore, the case study is also employed to illustrate the potential of installing a similar system in the UK. The latter study was performed by developing a validated simulation model of the solar district heating system. The findings of the analyses reported in this thesis exemplify the potential of TES in a domestic and community-level heating system in the UK. They also provide a basis for recommendations on the improved use of optimisation and simulation tools in the design process of energy systems.