Immune algorithm-based optimal design of collector system topology for offshore wind farm

Abstract

During the construction of offshore wind farms (OWFs), the capital cost associated with the collector system topology (CST) constitutes a significant proportion of the overall investment. A more efficient solution for connecting submarine cables can lead to substantial cost savings. To address this challenge, this paper introduces a novel approach that divides wind turbines into groups by polar coordinates to satisfy the no cross constraint. Subsequently, meta-heuristic algorithms are employed to optimize the grouping arrangement through iterative processes. In this way, the complex high-dimensional and multi-parameter problem will be decomposed into multiple parts for resolution. This paper evaluates four optimization algorithms to compare their effectiveness in optimizing the grouping results. Two different OWF scenarios are considered in the case studies to assess the performance of the proposed algorithms. Through extensive simulations and case studies, the results demonstrate the effectiveness and robustness of proposed approaches in achieving high-quality solutions while satisfying the constraints imposed by OWF operations and environmental conditions. Among the four algorithms, the immune algorithm stands out for its superior ability to provide more cost-effective solutions, which suggest that the immune algorithm-based optimization method can significantly contribute to the design and development of efficient CST for OWFs.