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Title: Two-tiered meta-heuristic holistic optimisation of subsea electrical networks
Author: McKinstry, Gordon
ISNI:       0000 0004 7431 5160
Awarding Body: University of Strathclyde
Current Institution: University of Strathclyde
Date of Award: 2018
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Human thirst for energy shows no signs of abating; instead global demand for electricity is projected to increase in the coming decades. If this demand is to be supplied in a sustainable manner, a rapid uptake in renewable sourced electrical energy is required. One arena that offers significant scope for increased renewable sourced generation is the offshore domain, through the offshore wind, tidal, and wave vectors. While the energy potential of the marine domain is vast, there are a number of challenges associated with deploying machines offshore to generate electricity, and transporting this energy back to population centres where it may be utilised. The deployment of a subsea electrical network to facilitate the extraction of energy from offshore renewable energy projects can be both logistically difficult and expensive. Consequently, the optimisation of such networks takes on critical importance if the marine domain is to make a significantly increased contribution towards the global electricity demand. This thesis considers the application of a two-tiered meta-heuristic optimisation approach for the holistic design of subsea electrical networks for offshore renewable energy projects; accounting for in-service costs arising from electrical losses and no-service conditions, in addition to purchase and installation costs. One current offshore wind development, Horns-Rev 1 was assessed using the optimisation framework that has been developed as part of this work. These studies demonstrate that the in-situ network at Horns-Rev 1 could have been improved upon, in terms of through-life cost minimisation while using the same design parameters, by changing the network layout. By altering the selected design parameters (voltage and frequency) the network performance, against the lifecycle cost minimisation could be further reduced. Additionally, the optimisation framework is deployed to design an optimal network for the proposed East Anglia One offshore wind park where viable solutions were identified using the projected design parameters. Again, it is shown that by altering the voltage and frequency parameters selected in the design, the through-life cost of the network solution may be improved upon relative to the assumed parameters.
Supervisor: Galloway, Stuart ; Elders, Ian ; Burt, Graeme Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral