Two-stage joint planning enabled reliability enhancement of offshore wind farm collection system

This is the authors' abstract. We don't add key points for this paper.

Floating offshore wind farms are characterized by long offshore distances and poor transportation accessibility, which result in higher failure loss cost under fault conditions in existing radial networks. Therefore, it is urgent to propose a more reliable ring topology planning scheme for the collection system. To solve the problem, a two-stage joint planning method (TJPM) is proposed for floating offshore wind farm collection system to enhance the operational reliability and reduce the full life cycle cost. In the first stage, the offshore substation location is optimized by the covariance matrix adaptation evolution strategy (CMA-ES), which performs an adaptive search by continuously and dynamically adjusting its probability distribution parameters. The optimal offshore substation location obtained in the first stage can be jointed as the constraints of the relationship optimization between wind turbines (WTs) and offshore substation areas in the second stage. In the second stage, the relationship is optimized based on a Tabu search algorithm, which is customized by integrating neighborhood operations such as reallocation and swapping on key WTs. The continuous Hopfield neural network is used for cable topology planning by linearizing the full life cycle cost of floating offshore wind farms, thereby improving the computational speed in the whole topology process of the collection system. Case studies demonstrate the superiority of the proposed joint planning method for floating offshore wind farms in operational reliability and economic performance.