A Techno-Economic Approach to Predicting Future Offshore Wind Farm Networks in the Baltic Sea Region

Abstract

Transitioning to renewable energy is essential for mitigating climate change and ensuring long-term energy security. Offshore wind farms offer a promising solution by harnessing strong and consistent wind resources at sea while minimizing land use conflicts. However, developing cost-effective offshore wind farm networks in the Baltic Sea—due to its unique geographical and environmental conditions—presents significant challenges.

This study addresses these challenges by developing a techno-economic optimization model to identify the most cost-effective offshore wind farm network configurations in the Baltic Sea Region. The model evaluates various configurations, including national (limited to domestic connections) and international networks (allowing cross-border connections), as well as single-stage (planning the entire network at once) and multi-stage (developing the network in phases) development plans. It optimizes the placement and capacities of wind farms, energy hubs, and export cables to minimize total system costs while adhering to technical and capacity constraints. Key geographical factors—such as water depth, ice cover, and proximity to ports—are integrated into the spatial data processing method to accurately assess infrastructure costs. The model also explores different network designs, including hub-and-spoke configurations that utilize energy hubs to consolidate and distribute power from multiple wind farms. The incorporation of single-stage and multi-stage optimization approaches allows for holistic and phased network developments, providing flexibility in planning and implementation.

The findings reveal that international networks are more cost-effective, totaling €28.5 billion, compared to national-only networks. This cost advantage is primarily due to enhanced flexibility in wind farm placement and power distribution. Specifically, national networks are 1.51% more expensive due to less optimized wind farm locations and localized grid overloading. Additionally, single-stage optimization outperforms multi-stage approaches by reducing costs by 1.71%, highlighting the benefits of a holistic planning strategy. While energy hubs can lower export cable costs by consolidating power transmission, they introduce higher overall expenses due to the additional costs associated with the hubs themselves. Specifically, the hub-and-spoke network is 1.15% more expensive than connecting wind farms directly to the onshore grid, suggesting a need for improved network optimization strategies. The study further identifies potential cost savings by positioning wind farms closer to shore in ice-covered areas when additional costs resulting from sea ice adaptation are minimized. This adjustment results in savings on export cables, as wind farms positioned closer to shore within these regions prove more economical due to their proximity and positioning in relatively shallow waters.

Ultimately, this research enhances the efficiency and economic viability of offshore wind infrastructure by optimizing design and cost estimation processes. The study provides actionable strategies for effective planning and investment in renewable energy infrastructure, offering valuable insights for policymakers and investors. By addressing the spatial, technical, and economic challenges associated with large-scale renewable energy deployment, the findings contribute significantly to academic knowledge and practical applications. The research emphasizes the importance of strategic long-term planning and international collaboration in developing sustainable and cost-efficient offshore wind energy infrastructures.