Clustered Offshore Wind Power Topology Structure Optimization Method Based on FCM and GA

This study focuses on offshore wind farm configurations, constructing a mathematical topology model to conduct comprehensive economic and reliability assessments. A novel topology optimization framework is developed for wind farm power collection systems, employing an enhanced genetic algorithm methodology. Furthermore, the research introduces a regional optimization approach utilizing optimal paradigm distance metrics for clustered wind farm configurations comprising multiple individual facilities. Computational experiments with an 100 MW capacity offshore wind farm demonstrate that the proposed model achieves superior convergence characteristics and optimization performance compared to conventional genetic algorithms, while simultaneously addressing both economic and reliability objectives. The methodology's flexibility is evidenced through parametric analysis of weight assignments between economic and reliability factors, yielding differentiated topological configurations. These findings provide valuable theoretical foundations and practical guidelines for the design optimization of power collection systems in large-scale wind energy clusters.