MCE Introduction, general description and overview of our 3 MCE and their components:

Siting a new renewable energy project is a complex process which needs to holistically take into account its effects on multiple factors relating to the environment, local economy and existing social and cultural dynamics in order to achieve the best outcome. Especially on remote island environments such as Haida Gwaii, choosing an optimal location for renewable energy generation is simply not just a matter of finding an area with the highest relative generation potential. Numerous proposed renewable energy projects on Haida Gwaii have been canceled due to public opposition: a Hecate Strait wind farm proposal was abandoned in 2009 because community members opposed construction on sacred sites (Hume, 2009). Thus, if these factors are not respected, any renewable energy project, no matter how sustainable or clean that project is, will face enormous public backlash and will likely be canceled.

Throughout Haida Gwaii, environmental factors such as the presence of endemic species, biological conservation zones, established federal and provincial protected parks, and protected marine areas need to be taken into account. These are clearly set boundaries which are easily recognized. Economic factors that are important to the Haida Gwaii region, including commercial fishing areas and transport routes, have less established boundaries but must be respected nonetheless. Additionally, social factors such as the presence of culturally significant areas, recreational fishing zones and tourism hubs must also be factored in to any decision relating to the establishment of new energy facilities on Haida Gwaii.

In order to simultaneously meet Haida Gwaii’s North Grid electricity needs while limiting the disturbances to the local environmental, social and economic activities, we have designed three multi-criteria evaluation (MCE) models (for wind, wave and solar energy), which takes these factors and constraints into account.

As with any MCE model, our first step was to identify the relevant factors for each type of renewable energy before normalizing their associated raster layers to values of one. Next, we used the analytical hierarchy process in order to determine their weights for the subsequent weighted overlay. We also had to identify our MCE constraints: the areas on Haida Gwaii which we will completely avoid. These constraints were compiled as polygon layers, and then merged into one polygon shapefile. The results from our weighted overlays were converted from raster to polygon, and then using the erase tool, the constraints layer’s polygons were erased from the weighted overlay results to give us our final MCE results for each type of renewable energy.