A Bayesian Network model to identify suitable areas for offshore wave energy farms, in the framework of ecosystem approach to marine spatial planning

cioeconomic aspects should be taken into account to identify suitable areas for development of wave energy projects. In this research we provide a novel approach for suitable site identification for wave energy farms. To achieve this objective, we (i) developed a conceptual framework, considering technical, environmental and conflicts for space aspects that play a role on the development of those projects, and (ii) it was operationalized in a Bayesian Network, by building a spatially explicit model adopting the Spanish and Portuguese Economic Exclusive Zones as case study. The model results indicate that 1723 km2 and 17,409 km2 are highly suitable or suitable for the development of wave energy projects (i.e. low potential conflicts with other activities and low ecological risk). Suitable areas account for a total of 2.5 TWh center dot m-1 energy resource. These areas are placed between 82 and 111 m water depth, 18-30 km to the nearest port, 21-29 km to the nearest electrical substation onshore, with 143-170 MWh m-1 mean annual energy resource and having 124-150 of good weather windows per year for construction and maintenance work. The approach proposed supports scientists, managers and industry, reducing uncertainties during the consenting process, by identifying the most relevant technical, environmental and socioeconomic factors when authorising wave energy projects. The model and the suitability maps produced can be used during site identification processes, informing Strategic Environmental Assessment and ecosystem approach to marine spatial planning.

Automated summary

This research proposes a novel approach using Bayesian Network to identify suitable areas for wave energy projects. The results show that 1723 km2 and 17,409 km2 of areas within the Spanish and Portuguese Economic Exclusive Zones are highly suitable or suitable for wave energy development. This approach can assist decision-makers in considering relevant technical, environmental, and socioeconomic factors during the consenting process for wave energy projects.