• Energy Research

Offshore wind energy, as one of the featured rich renewable energy sources, is getting more and more attention. The cable connection layout has a significant impact on the economic performance of offshore wind farms. To make better use of the wind resources of a given sea area, a new method for optimal construction of offshore wind farms with different types of wind turbines has emerged in recent years. In such a wind farm, the capacities of wind turbines are not identical which brings new challenges for the cable connection layout optimization. In this work, an optimization model named CCLOP is proposed for such wind farms. The model incorporates both the cable capital cost and the cost of power losses associated with the cables in its objective function. To get an optimized result, a Voronoi diagram based adaptive particle swarm optimization with local search is proposed and applied. The simulation results show that the proposed method can help find a solution that is 12.74% outperformed than a benchmark.

Green hydrogen plays a pivotal role in decarbonizing our energy system and achieving the Net-Zero Emissions goal by 2050. Offshore wind farms (OWFs) dedicated to green hydrogen production are currently recognized as the most feasible solution for scaling up the production of cost-effective electrolytic hydrogen. However, the cost associated with distribution and transmission systems constitute a significant portion of the total cost in the large-scale wind-hydrogen system. This study pioneers the simultaneous optimization of the inter-array cable routing of OWFs and the location and capacity of offshore hydrogen production platforms (OHPPs), aiming to minimize the total cost of distribution and transmission systems. Considering the characteristics of hydrogen production efficiency, this paper constructs a novel mathematical model for OHPPs across diverse wind scenarios. Subsequently, we formulate the joint planning problem as a relaxed mixed-integer second-order cone programming (MISOCP) model and employ the Benders decomposition algorithm for the solution, introducing three valid inequalities to expedite convergence. Through validation on real-world large-scale OWFs, we demonstrate the validity and rapid convergence of our approach. Moreover, we identify hydrogen production efficiency as a major bottleneck cost factor for the joint planning problem, it decreases by 1.01% of total cost for every 1% increase in hydrogen production efficiency.