A model to map levelised cost of energy for wave energy projects. (1st February 2018)

• Record Type: Journal Article
• Authors: Frost, Ciaran; Findlay, David; Macpherson, Ewen; Sayer, Philip; Johanning, Lars
• Is Part Of: Ocean engineering. Volume 149(2018)
• Page Start: 438
• Page End: 451
• Publication Date: 2018-02-01
• Subjects: Wave energy -- Economic modelling -- Levelised cost of energy -- Spatial analysis -- Economic mapping -- GIS; Ocean engineering -- Periodicals; Ocean engineering; Periodicals; 620.4162
• DOI: 10.1016/j.oceaneng.2017.09.063
• Languages: English
• ISSNs: 0029-8018

Abstract

Abstract: An economic model has been developed which allows the spatial dependence of wave energy levelised cost of energy (LCOE) to be calculated and mapped in graphical information system (GIS) software. Calculation is performed across a domain of points which define hindcast wave data; these data are obtained from wave propagation models like Simulating WAves Nearshore (SWAN). Time series of metocean data are interpolated across a device power matrix, obtaining energy production at every location. Spatial costs are calculated using Dijkstra's algorithm, to find distances between points from which costs are inferred. These include the export cable and operations, the latter also calculated by statistically estimating weather window waiting time. A case study is presented, considering the Scottish Western Isles and using real data from a device developer. Results indicate that, for the small scale device examined, the lowest LCOE hotspots occur in the Minches. This area is relatively sheltered, showing that performance is device specific and does not always correspond to the areas of highest energy resource. Sensitivity studies are performed, examining the effects of cut-in and cut-out significant wave height on LCOE, and month on installation cost. The results show that the impact of these parameters is highly location-specific. Highlights: A model to map Levelised Cost Of Energy (LCOE) for wave energy is presented. Spatial methodology allows identification of device specific LCOE "hotspots". Dijkstra's algorithm is used for spatial cost estimation. Installation weather windows are estimated using the NMI statistical method. LCOE sensitivity to cut-in and cut-out sea state and installation season presented.