Optimization of the offshore wind power grid-connected structure based on an improved genetic algorithm

Li, Haibo and Jiang, Keteng and Lu, Zongxiang and Hou, Junhao and Xu, Sixuan and Qi, Wanchun and Cai, Hui (2023) Optimization of the offshore wind power grid-connected structure based on an improved genetic algorithm. Frontiers in Energy Research, 11. ISSN 2296-598X

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Abstract

Large-scale offshore wind power generation has become one of the research hotspots in the development of new energy in the world. However, the planning of far-reaching offshore wind power is faced with many technical difficulties, such as the need to consider the optimization of line transmission capacity caused by the truncation effect in combination with the wind power output probability, and solve the problem that traditional algorithms cannot solve the dynamic programming problem, and the greedy algorithm for solving the dynamic programming problem cannot solve the global optimal solution. Therefore, in order to solve the above problems, based on the full life cycle (FLC) investment calculation of the collecting and transmission system, the topology optimization model of the offshore wind power system is established. In addition, in order to solve the grid-connection problem of offshore wind farms, an improved topology optimization algorithm based on greedy idea is proposed. The optimization results show that the critical values of economic transmission distance of HVAC, FFTS and HVDC are usually 50 km and 170 km respectively. Finally, the collection scheme of the wind farm cluster including three far-reaching offshore wind farms are analyzed, and the results show that the total cost of the optimized point-to-point scheme is reduced by 5.6% and 10.2% respectively compared with the star topology and the circular collection topology, with significant economic benefits.

Item Type: Article
Subjects: OA Digital Library > Energy
Depositing User: Unnamed user with email support@oadigitallib.org
Date Deposited: 24 Apr 2023 05:17
Last Modified: 20 Jul 2024 09:18
URI: http://library.thepustakas.com/id/eprint/1024

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