An Alterable Weight Minimum Spanning Tree Method for Electrical Collector System Planning in Tidal Current Generation Farms

Abstract

This paper proposes an alterable weight minimum spanning tree (AW-MST) method to plan electrical collector systems (ECSs) in tidal current generation farms (TCGFs) toward economic objectives. First, a sector-division-based fuzzy c-means (FCM) grouping algorithm is proposed. The tidal current turbines (TCTs) in the TCGF are divided into several sectors by the improved FCM algorithm to relieve the computational burden. Meanwhile, trans-region crossings and overloads of submarine cables can be simultaneously avoided. Second, an ECS planning model is established which fully considers the tidal current velocity (TCV) characteristics and ECS investment and operating costs. Since the variable factors cannot be considered by the common minimum spanning tree algorithms, alterable weights are used in the AW-MST to optimize the variable factors, including power losses and cable types. Finally, the two different TCGFs and the measured TCV datasets collected from North of Orkney, Scotland, were used to verify the effectiveness and adaptability of the proposed method.