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Engineering Study of Tidal Stream Renewable Energy Generation and Visualization: Issues of Process Modelling and Implementation

Harrison, John and Uhomoibhi, James (2016) Engineering Study of Tidal Stream Renewable Energy Generation and Visualization: Issues of Process Modelling and Implementation. In: AVI 2016, International Conference Workshop: “Road Mapping Infrastructures for Advanced Visual Interfaces Supporting Big Data Applications in Virtual Research Environments”, Bari, Italy. ACM. 5 pp. [Conference contribution]

[img] Text - Accepted Version


Tidal stream energy has the potential to make a significant contribution to the UK energy mix over the coming years. Accurate modelling and visualisation of both tidal resource and array layout will enhance understanding of in stream tidal behaviour leading to improvements in site identification and optimal positioning of individual turbines, and a realistic representation of blade loading conditions will aid designers and manufacturers in creating more robust devices and improve survivability.The main barriers to large scale deployments of tidal arrays are the costs associated with manufacturing, installation and maintenance, therefore presently tidal energy is not competitive on cost with more established renewable technologies. Opportunities do exist to reduce costs and this technology can become competitive in the long term, however improved understanding of both environmental conditions and device behaviour is need to achieve this.The ability to visual represent realistic behaviours will assist both industry and academics during resource modelling, site selection, selecting optimal array configurations and the design and manufacture of devices. It is in the interest of all practitioners involved in tidal stream energy to develop robust models which can reliably simulate real world conditions and enhance understanding of tidal processes, flow regimes and device survivability issues.

Item Type:Conference contribution (Paper)
Keywords:Tidal stream energy, tidal turbines, tidal resource, visualisation, modelling
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Engineering
ID Code:36573
Deposited By: Dr James Uhomoibhi
Deposited On:16 Jan 2017 16:57
Last Modified:16 Jan 2017 16:57

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