With an augmentation in energy needs from population-growth and digitalisation, and increasing global warming and climate change, the global energy mix needs to rely less on fossil resources and more on renewable energy sources. This thesis is dedicated to wave renewables which form part of marine renewable energies. A Wave Energy Converter (WEC) is a mechanical device used to harvest the energy from ocean waves. Due to the large variety of designs, properly assessing where each WEC works best and increasing its appeal to the market is challenging. Indeed, many approaches for WEC-location pairing have been developed but their integration is missing alongside misuse of optimisation methods and neglecting crucial aspects for WEC (and farm) assessments such as the wave direction (and period) and potential response to the actual energy demand, amongst others. Furthermore, too often studies reduce their area for assessing wave energy installation to high energy power/energy locations, whereas some studies have shown that WECs may work best in lower resource conditions, which need to be assessed further. This thesis develops an integrated method divided into a collection of six chapters assessing main aspects of the wave renewable energy WEC-location pairing by:

1. Developing the CapEx method for adjusted cost estimations of the technologies under different configurations (design, size, and dimensions) and locations’ characteristics,
2. Analysing optimisation methods for enhanced technology energy production and capacity factor assessment,
3. Investigating the annual energy production relationship with the farm costs based on the expansion of the CapEx method for various designs of technology,
4. Conducting a region and wave resource assessment for renewable energy farm installation based on indices and metrics analyses alongside geographical limitations of potential areas,
5. Developing a framework for pairing fixed-designed WECs and locations based on the capacity factor, the energy production and response to the energy demand, alongside area restrictions’ impacts, for mapping optimal WEC-location pairs,
6. Classifying the WEC wave power and efficiency to compensate for the current classifications that are not fully correlated with the actual WEC energy production potential, to help the pre-assessment of WEC-location pairing over larger areas. This method is less time-consuming and potentially represent all possible WEC power production potential compared to the five previous chapters that are based on more detailed levels of pairing. The wave direction is mostly neglected in the literature although almost 50% of the WECs are wave direction-dependent and wave direction may greatly impact the wave farm energy production. Consequently, this is investigated in the chapters associated with points 2 to 5. In particular, the chapters associated with 2 and 3 involve the Wavepiston technology that is siginificantly dependent on the wave direction to provide optimal energy production. Chapter 4 assesses the wave direction of the resource by including parameters based on circular statistics. Chapter 5 provides a solution to include wave direction in the energy production matrices provided by the WEC developers. Finally, two integrations of the six developed pieces of method are provided, into a synthetic and a detailed ensemble method-framework. It enables selecting suitable WEC(s) for wave farm installation in a given site or area, or finding potential farm installation hotspots for a given WEC. This framework is built on wave distribution climates for given places or areas, locations’ characteristics (energy demand, urban, fauna, and flora restrictions to name a few), WEC and associated farm characteristics (water depth, moorings, grid connection type, etc.) and economics. This study highlighted the need for several “checks” and possible adjustments (wave spectrum, wave direction-dependency, scaling possibilities, linearity, and presence of generator-related limitations) and to frame each WEC study to help clarify their contribution. Although costs are challenging to obtain for large databases of WECs and configurations, the CapEx method unlocks the possibilities to compute economical indicators to enhance WEC-location mapping for wave farm analyses. Optimisations over the generator are encouraged in any case, but WEC configuration optimisations should be conducted carefully. In contrast, the new classes should be used for a higher reach by representing the majority of WECs. Furthermore, the method to pre-select locations based on high wave power (and unidirectional wave climate) is proven misleading and should no longer be considered; but instead, a fairer wave resource approach is provided. It should always be compared with the WEC-location pairs’ cartography (carefully discussing area restrictions) to conclude on wave farm installation and design.