Review of Design Schemes and AI Optimization Algorithms for High-Efficiency Offshore Wind Farm Collection Systems

Yuchen Wang, Dongran Song (), Li Wang, Chaoneng Huang, Qian Huang, Jian Yang and Solomin Evgeny
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Yuchen Wang: School of Automation, Central South University, Changsha 410083, China
Dongran Song: School of Automation, Central South University, Changsha 410083, China
Li Wang: School of Automation, Central South University, Changsha 410083, China
Chaoneng Huang: School of Automation, Central South University, Changsha 410083, China
Qian Huang: School of Automation, Central South University, Changsha 410083, China
Jian Yang: School of Automation, Central South University, Changsha 410083, China
Solomin Evgeny: Department of Electric Stations, Grids and Power, Supply Systems, South Ural State University, 76 Prospekt Lenina, 454080 Chelyabinsk, Russia

Energies, 2025, vol. 18, issue 3, 1-27

Abstract: The offshore wind power sector has witnessed exponential growth over the past decade, with large-scale offshore wind farms grappling with the challenge of elevated construction and maintenance expenses. Given that the collector system constitutes a substantial part of the investment cost in wind farms, the design and optimization of this system are pivotal to enhancing the economic viability of offshore wind farms. A thorough examination of collector system design and optimization methodologies is essential to elucidate the critical aspects of collector system design and to assess the comparative merits and drawbacks of various optimization techniques, thereby facilitating the development of collector systems that offer superior economic performance and heightened reliability. This paper conducts a review of the evolving trends in collector system research, with a particular emphasis on topology optimization models and algorithms. It juxtaposes the economic and reliability aspects of collector systems with varying topologies and voltage levels. Building on this foundation, the paper delves into the optimization objectives and variables within optimization models. Furthermore, it provides a comprehensive overview and synthesis of AI-driven optimization algorithms employed to address the optimization challenges inherent in offshore wind farm collector systems. The paper concludes by summarizing the existing research limitations pertaining to offshore wind farm collector systems and proposes innovative directions for future investigative endeavors. The overarching goal of this paper is to enhance the comprehension of offshore wind farm collector system design and optimization through a systematic analysis, thereby fostering the continued advancement of offshore wind power technology.

Keywords: offshore wind; collector system; topology; optimization algorithm; reliability (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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