Abstract
Tidal stream energy has the potential to make a significant contributionto energy mix in the future. Accurate modelling and visualisation of bothtidal resource and array layout enhances understanding of in-stream tidal behaviourleading to improvements in site identification and optimal positioning ofindividual turbines. A realistic representation of blade loading conditions will aiddesigners and manufacturers in creating more robust devices and improve survivability.The main barriers to large scale deployments of tidal arrays are the costsassociated with manufacturing, installation and maintenance. Therefore, presentlytidal energy is not competitive on cost with more established renewabletechnologies. The current position paper investigates and reports on resourcemodelling, site selection, selecting optimal array configurations and the designand manufacture of devices for tidal stream renewable energy generation. This isaimed at developing models to reliably simulate real conditions, enhance understandingof tidal processes, flow regimes and device survivability issues.
Original language | English |
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Title of host publication | Advanced Visual Interfaces Supporting Big Data, AVI 2016 Workshop, AVI-BDA 2016, Bari, Italy, June 7–10, 2016, Revised Selected Papers, Lecture Notes in Computer Science, LNCS 10084 |
Place of Publication | Switzerland |
Publisher | Springer |
Pages | 19-34 |
ISBN (Print) | 978-3-319-50069-0 |
DOIs | |
Publication status | Published (in print/issue) - Dec 2016 |
Keywords
- Tidal stream energy · Tidal turbines · Tidal resource · Visualisation · Modelling
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James Uhomoibhi
- School of Engineering - Lecturer in Engineering
- Faculty Of Computing, Eng. & Built Env. - Lecturer
Person: Academic