Johanning, Lars

Ingram, David

Sayer, Phillip

Frost, Ciaran

other

2019-07-26T10:41:24Z

2019-07-26T10:41:24Z

2019-03-13

In recent times there has been a surge in renewable energy investment, as costs fall and the full danger of global warming is realised by policymakers. As well as more established industries, like wind and solar power, there is also high interest in pre-commercial technologies with significant potential. Wave energy fits into this category and has a number of advantages that make it a subject of ongoing research and industrial activity. An energy dense resource, it is easier to forecast than wind and fits the seasonal demand profile well. A global capacity of the order of hundreds of gigawatts has been estimated, with a particularly strong resource in the UK. Despite these characteristics the industry has yet to reach a commercial level. No company has been able to demonstrate consistent energy production at a cost effective rate. Viable project locations must balance an energetic resource with conditions that allow devices to be accessed for maintenance, while also trying to minimise system costs. While utility scale farms are seen as the long term future for the technology, off-grid hybrid systems could supply cheaper and dispatchable energy at local levels. This market, while smaller, is made up of more costly forms of energy so provides a better entry market. Conventional economic analyses for both types of systems tend to be performed for single locations at a time. While useful for benchmarking the technology, these methods are of limited use for site scoping as energy production and costs can show large variation over relatively short distances (<10 km). This research thesis describes a geospatial economic model that has been created to address the above issues. It was developed in collaboration with Albatern, a wave energy developer, who provided their expertise and helped to guide the research activities. The targeted application was to allow economic assessment of Albatern's "WaveNET" device, either as a power station for grid connection or an off-grid hybrid solution for aquaculture applications. The model has a number of aspects that are of significant interest to the industry. These include computational model design and geographic calculation of energy production, costs and Levelised Cost of Energy (LCOE). The spatial approach is valuable as a whole area can be evaluated at a time, indicating deployment locations particularly suitable for the technology at hand. Sensitivity analysis is also easily carried out, to build understanding of the cost drivers at specific locations. The theory underpinning the model and its implementation is described. It is then demonstrated with two representative case studies: considering grid-connected and off-grid WaveNET device demonstrators on the West Coast of Scotland. The results show the strengths of the approach as a way of identifying economically viable hotspots and the main cost drivers. For the grid-connected case, examining an area of 150 by 250 km, the model was able to identify a significant LCOE hotspot between the Isle of Skye and the Outer Hebrides. The potential for the device to power a fish farm, when combined with a battery bank and diesel generator, was then analysed. Two regions were examined and real fish farm locations considered. The output results allow easy comparison between the two system types, emphasising the advantages of investigating both to inform business activity.

http://hdl.handle.net/1842/35896

en

The University of Edinburgh

C. Frost, D. Findlay, E. Macpherson, P. Sayer, and L. Johanning, A model to map levelised cost of energy for wave energy projects, Ocean Engineering, vol. 149, pp. 438-451, 2018.

C. Frost, D. Findlay, E. Macpherson, P. Sayer, and L. Johanning, Mapping Economic Performance of Wave Energy in Proceedings of Renew2016, 2016.

C. Frost, D. Findlay, E. Macpherson, P. Sayer, and L. Johanning, Global market potential for small scale wave energy. Presentation at the International Conference on Ocean Energy (ICOE), Edinburgh, 2015.

wave energy

wave energy array

lcoe

renewable energy

gis

hybrid energy

off-grid

off grid

energy

Mapping the economic potential of wave energy: grid connected and off-grid systems

Thesis or Dissertation

Doctoral

PhD Doctor of Philosophy