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Durham e-Theses
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Offshore Transmission Systems Planning Under Severe Uncertainty

BAINS, HENNA (2021) Offshore Transmission Systems Planning Under Severe Uncertainty. Doctoral thesis, Durham University.

Full text not available from this repository.
Author-imposed embargo until 28 May 2024.

Abstract

The offshore wind industry will make investment decisions regarding the electrical transmission infrastructure required to connect offshore wind farms to the onshore grid. Unfortunately, many policy, planning and operational decisions will be made under severe uncertainty due to limited data, knowledge, and expertise. There is insufficient information due to the assets' short operational history, data is usually project-specific, and future projects include advancing technologies. In particular, these uncertainties make it challenging to assign probability distributions to inputs required to assess an offshore transmission system economically. Therefore, methods based on classical probability theory may not be justified under severe uncertainty. Nevertheless, solutions must be found to handle severe uncertainty when planning future projects.

The work of this thesis designs (by setting up the methodology), tests (through applications) and validates (by comparing to conventional methods) new offshore transmission planning techniques. The main original research contributions are the development of an economic model to support offshore transmission planning, and the application of advanced statistical techniques to handle severe uncertainty in long-term decision making. This thesis presents three in-depth practical applications.

Advanced statistical methods, such as imprecise probability, are used to handle uncertainty in the input parameters. We demonstrate how to implement the techniques, as well as find and overcome challenges that may arise when applying these techniques to practical problems. Additionally, we show the benefits of these methods and, in particular, the ability to handle severe uncertainty in the input parameters more robustly than conventional methods.

Overall, the original contribution of this thesis demonstrates a framework for decision makers to handle severe uncertainty within the offshore transmission space and in the broader energy context. This enables decisions on key offshore transmission assets to take into account severe uncertainties. Ultimately, this research supports the integration of renewable technologies in a cost-effective way.

Item Type:Thesis (Doctoral)
Award:Doctor of Philosophy
Faculty and Department:Faculty of Science > Engineering, Department of
Thesis Date:2021
Copyright:Copyright of this thesis is held by the author
Deposited On:28 May 2021 14:20

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