Marine Renewable Energy
Marine Renewable Energy 2022-23
School of Ocean Sciences
Module - Semester 2
Context of marine energy (global/UK context, intermittency, energy roadmaps)
Key energy concepts (kinetic energy, potential energy, wave energy, tidal energy, power)
Wave energy conversion (wave resource, wave devices, practical resource)
Marine current conversion (tidal resource, tidal devices, practical resource)
Multiple resource exploitation
Multiple resource interactions
Arrays of devices
Practical constraints and cabling
Environmental impacts (non-physical, physical)
Case studies (NW European shelf seas, Orkney & Pentland Firth, Wales)
Future of the industry
'Other' forms of ocean renewable energy
Pass - A partial understanding of marine renewable energy concepts and principles; demonstrate some ability to handle and draw conclusions from large spatial and time-series datasets.
Merit - A good knowledge of marine renewable energy concepts and principles; demonstrate good ability to handle and draw conclusions from large spatial and time-series datasets. Demonstrate some ability to solve energy problems independently.
Distinction - Excellent knowledge of marine renewable energy concepts and principles; demonstrate excellent ability to handle, critically analyse, and to draw conclusions from large spatial and time-series datasets. Ability to critically analyse and solve energy problems independently
- A critical understanding of the marine renewable energy industry, including current status and challenges facing the industry.
- An ability to characterise the wave and tidal energy resources over a variety of timescales.
- An extensive knowledge of the principals of energy and how kinetic and potential energy can be converted into electricity using wave and tidal energy devices.
- An understanding of the environmental impacts of marine renewable energy extraction, including feedbacks between energy extraction and the resource, and impacts on sedimentary systems.
- Knowledge of how oceanographic models can be used in resource assessment and environmental impact studies.
- Knowledge of time series and spatial analysis of large (multi-variable) datasets.
SWAN wave impact