With Tailwinds Towards 30 GW: Strategic Spatial Planning of Offshore Wind Farms in Norwegian Waters - A Multi-Objective Optimization Approach

Abstract

To address the increasing electricity demand and incentivize new industrial development, the Norwegian government has set the ambitious target of facilitating the development of 30 Gigawatts of offshore wind power by 2040. The magnitude of this goal requires careful spatial planning that takes into account wind conditions, diversification, and the suitability of potential locations for offshore installations. The aim of this thesis is to provide strictly data-driven insights as to where the ideal sites for offshore wind farms are located in Norwegian waters. Building on Markowitz’ Modern Portfolio Theory, we develop a multi-objective optimization model that finds a portfolio of wind farms that minimizes portfolio covariance while maximizing average capacity factor, implemented using the weighted sum method. Our benchmark model identifies 12 wind farm sites with an average capacity factor of 66% at a standard deviation of 0.22. In addition, the dynamic set-up of our modeling allows us to demonstrate how the set of optimal locations is responsive to different conflicts of interest. Our results can be used to draw a tentative comparison to the 20 candidate locations put forward by the Norwegian Water And Energy Directorate in 2023. We find that locations like Sønnavind A and Vestavind A are consistently part of the optimal portfolio, while areas like Utsira Nord and Vestavind are shown to have limited importance. These insights contribute to strategic spatial planning for Norway’s offshore wind ambitions.

To address the increasing electricity demand and incentivize new industrial development, the Norwegian government has set the ambitious target of facilitating the development of 30 Gigawatts of offshore wind power by 2040. The magnitude of this goal requires careful spatial planning that takes into account wind conditions, diversification, and the suitability of potential locations for offshore installations. The aim of this thesis is to provide strictly data-driven insights as to where the ideal sites for offshore wind farms are located in Norwegian waters. Building on Markowitz’ Modern Portfolio Theory, we develop a multi-objective optimization model that finds a portfolio of wind farms that minimizes portfolio covariance while maximizing average capacity factor, implemented using the weighted sum method. Our benchmark model identifies 12 wind farm sites with an average capacity factor of 66% at a standard deviation of 0.22. In addition, the dynamic set-up of our modeling allows us to demonstrate how the set of optimal locations is responsive to different conflicts of interest. Our results can be used to draw a tentative comparison to the 20 candidate locations put forward by the Norwegian Water And Energy Directorate in 2023. We find that locations like Sønnavind A and Vestavind A are consistently part of the optimal portfolio, while areas like Utsira Nord and Vestavind are shown to have limited importance. These insights contribute to strategic spatial planning for Norway’s offshore wind ambitions.