Several decarbonisation scenarios indicate that renewable energy will be a key supply route to mitigate carbon emissions this century. To better represent the implications of such an energy transition, it is important that energy systems models (ESMs) can realistically characterise the technical and economic potential of renewable energy resources.
This thesis presents a temporally-explicit and geospatially-resolved methodology for estimating the global wind energy potential, i.e. the annual terawatt-hour (TWh/yr) production potential of wind farms, assuming that capacity could be built across the viable onshore and offshore areas of each country, globally. Further, a geospatially-resolved levelised cost of electricity (LCOE) model is developed to characterise the offshore cost potential, accounting for non-resource related cost factors.
Capacity potential is produced in tranches according to the average annual capacity factor and the capacity factor in each time slice. For offshore wind, capacity potential is also disaggregated by the distance to shore and water depth, which are the main cost drivers. A technology-rich description of fixed and floating foundation types allows LCOEs to be calculated for each grid cell across the globe, relative to location-specific annual energy production (AEP).
Results show that the global wind energy potential is vast, but severely diminished if areas far from electricity infrastructure are discounted. Nevertheless, for onshore wind the capacity potential for capacity factors above 15% is 267 TW, with a generation potential of 580,000 TWh/yr. The offshore potential is 329,600 TWh/yr with a relatively smaller deployment capacity of 85.6 TW, reflecting the access to higher capacity factors in offshore areas. Deployment potential is favourable for countries with large shallow water areas. However, recent cost developments have made access to transitional and deep water locations much more feasible as long as turbine size increases continue to offset the relatively higher foundation costs.