Supervisor: Prof. Ian Bryden (University of Edinburgh)
Sponsor Company: Iberdrola/Scottish Power Renewables
PhD Student: Andy MacGillivary
This student has graduated and the project is complete.
Marine renewable energy has been receiving increasing attention in both political and industrial circles. There has been limited deployment to date, and the industry is only now entering the development phase of the Research, Development, Demonstration and Deployment (RDD&D) process.
The current cost of energy for demonstrator marine energy converters is substantial - potentially prohibitive for large scale deployment and utility scale projects. Significant focus is being given to cost reduction.
The successful growth of the wind industry may have set unhelpful precedents on the scale required for deployment of tidal energy converters at this early stage of the industry. The starting scale of marine devices could significantly impact the potential for "up-scaling" at a device level, and so we are unlikely to see up-scaling in a similar manner to wind technology. Component modularity and innovative mooring and foundations will be needed to maximise the potential for energy capture, as several factors will limit the rotor size such as water depth and structural loading limits in the harsh marine environment.
The aim of this project is to investigate the applications for learning by searching (research) and by doing (deploying), and how the complex interactions between learning rates, learning type, device starting scale, device starting cost and the scale at which "learning" effects are seen through sustained cost reduction can be applied in deployment scenarios.