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) 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.

Scenarios for offshore wind co-existence opportunities and trade-offs

“…Optimization applied to siting of offshore wind considers objectives related to energy production [33][34][35][36][37][38][39][40], variability and intermittency challenges [33,34], and cost minimization/profit maximization [35][36][37][38]. When optimizing offshore wind, availability of space, considerations of other users, physical characteristics impacting technical feasibility [5,6], and avoidance of ecologically sensitive areas [29][30][31][32] are often seen as constraints.…”

“…By handling societal and environmental issues as goals rather than constraints, their method was able to find economically profitable solutions that compromised social and environmental factor to a very small degree. Solbrekke et al [39] used the analytical hierarchy process to model the decision-making problem arising when there are several actors like offshore wind investors, fishermen, and environmentalists with partially conflicting preferences regarding the siting of wind farms offshore. They constructed a hierarchical suitability score around wind resource attractiveness, techno-economical aspects, metocean constraints, social acceptance, and environmental considerations.…”

“…Several of the approaches listed earlier also have an element of participatory modelling, particularly GIS-contributions [28-30, 36, 37] and multi-objective methods [38][39][40]. However, these are often not temporally explicit scenarios, but focus on scenarios based on impacts of decisions made at one point in time.…”

Optimal allocation of 30GW offshore wind power in the Norwegian Economic Zone

“…NVE suggests 20 areas in the NEZ for further consideration in a subsequent impact assessment. Our second set of candidate locations is based on the study by Solbrekke and Sorteberg (2023), who use multicriteria decision analysis to point out suitable and robust offshore areas for wind power deployment.…”

“…Instead of placing wind power by grid cell (Tejeda et al, 2018), we find the optimal number of turbines on a wind farm unit represented by the wind resources from one grid cell in NORA3-WP. Our study, therefore, builds naturally on recent developments in the identification of suitable locations for wind power generation (Solbrekke and Sorteberg, 2023) and methodology for distributing resources between them (Tejeda et al, 2018). We develop the procedure for wind power distribution further by incorporating the Norwegian government's sequential development plan, "30by40", and introducing a maximum number of wind farms constraint (see Section 3).…”