Norwegian offshore wind power—Spatial planning using multi‐criteria decision analysis
Abstract The Norwegian government recently agreed on the goal 30by40 , which involves opening Norwegian offshore areas to host 30 GW of installed wind power by 2040. We address this goal by presenting a first mapping of wind power suitability scores (WPSS) for the entire Norwegian economic zone (NEZ...
| Published in: | Wind Energy |
|---|---|
| Main Authors: | , |
| Other Authors: | , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
Wiley
2023
|
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1002/we.2871 https://onlinelibrary.wiley.com/doi/pdf/10.1002/we.2871 |
| Summary: | Abstract The Norwegian government recently agreed on the goal 30by40 , which involves opening Norwegian offshore areas to host 30 GW of installed wind power by 2040. We address this goal by presenting a first mapping of wind power suitability scores (WPSS) for the entire Norwegian economic zone (NEZ) using a multi‐criteria decision analysis framework (MCDA), namely, the analytical hierarchical process (AHP) approach. We obtain WPSS considering relevant criteria like wind resources, techno‐economic aspects, social acceptance, environmental considerations, and met‐ocean constraints such as wind and wave conditions. The results starts with a baseline scenario, where the criterion importance is pairwise compared in the context of balancing economic incentives and conflicting interests. Additionally, to reveal regions that are robust to changes in criterion importance, we carry out a sensitivity analysis by introducing three additional scenarios. These scenarios represent stereotypical actors with distinct preferences for siting of wind farms: the investor , the environmentalist , and the fisherman . The results show that the southern part of the NEZ is the most suitable and robust region for offshore wind power deployment. This region receives the highest suitability category (“very high” suitability for wind power application) throughout all the scenarios. Areas in the Norwegian part of the Barents Sea and the near‐coastal areas outside mid‐Norway are also well suited regions, but these are more sensitive to the choice of criterion importance. The use of AHP within the framework of MCDA is shown to be a promising tool for pinpointing the best Norwegian offshore areas for wind power application. |
|---|