基于蜉蝣算法的变间距规则排布海上风电场微观选址优化方法

doi:10.20145/j.32.1894.20250104

《新能源科技》杂志社 ›› 2025, Vol. 6 ›› Issue (1): 28-34.doi: 10.20145/j.32.1894.20250104

基于蜉蝣算法的变间距规则排布海上风电场微观选址优化方法

孙宇¹, 许昌^2*, 韩星星², 蒋小雪², 谭康辉²

1.山东电力设计咨询院有限公司,山东济南 250013;
2.河海大学新能源学院,江苏常州 213200

发布日期:2025-03-21
通讯作者: *许昌(1972—),男,教授,博士;研究方向:太阳能和风能利用。zhuifengxu@163.com。许昌,1972年10月生,博士,河海大学新能源学院副院长,博士生导师,教授,可再生能源发电技术教育部工程研究中心副主任。长期从事复杂流体流动与先进控制理论及其在风力发电、水力发电和综合能源系统中的应用研究。江苏省新能源领域六大人才高峰人才,担任国家新能源专业教育联盟副理事长、中国可再生能源学会理事、中国工程热物理学会流体机械专业委员会委员、中国可再生能源学会风能专业委员会委员。任《太阳能学报》《可再生能源》《新能源科技》等期刊编委,Renewable Energy,Energy,Wind Energy等20余种国内外重点期刊审稿专家。以第一完成人获得江苏省科技进步一等奖、江苏省可再生能源能源学会科技进步一等奖、中国可再生能源学会科技进步二等奖、2023江苏省可再生能源学会突出贡献奖等多个奖项,发表论文约200篇,其中80余篇被SCI、EI检索收录,负责“国家自然科学基金项目”“国家重点研发项目”“国家高新技术重点项目(863)”等在内的纵向项目课题20余项,横向项目80余项。
作者简介:孙宇(1995—),女,工程师,硕士;研究方向:新能源发电技术。sunyu@sdepci.com
基金资助:
国家自然基金(52106238);中国博士后科学基金资助项目(2024M760739);中央高校基本科研业务费专项资金资助(B240201171)。

Optimization method for micro-siting of offshore wind farms based on the mayfly algorithm with variable spacing rules

SUN Yu¹, XU Chang^2*, HAN Xingxing², JIANG Xiaoxue², TAN Kanghui²

1. Shandong Electric Power Engineering Consulting Institute Co., Ltd., Jinan 250013, China;
2. College of New Energy, Hohai University, Changzhou 213200, China

Published:2025-03-21

摘要/Abstract

摘要： 我国海上风电正处于快速发展阶段,但如何进一步提升机组能效和降低开发成本仍然是当前的关键规划问题。文章提出了一种基于七参数的非等间距规则排布优化方法,通过引入群体优化算法——蜉蝣算法,对该布局方法的关键参数进行优化,从而实现对海上风电场规则布局的整体优化。通过案例验证了所提优化方法的有效性。文章研究的微观选址规则布局优化方法为大型风电基地的规划设计提供了有价值的参考,能够在风电基地场址划分和布局设计等工作中发挥指导作用。

关键词: 海上风电场, 微观选址优化, 蜉蝣算法, 规则排布

Abstract: China’s offshore wind power is currently in a rapid development stage, but improving turbine efficiency and reducing development costs remain key planning challenges. This paper proposes a non-equidistant rule-based layout optimization method based on seven parameters. By introducing a group optimization algorithm—the Mayfly Algorithm—key parameters of the layout method are optimized to achieve overall optimization of the offshore wind farm’s regular layout. The effectiveness of the proposed optimization method is verified through case studies. The micro-siting rule-based layout optimization method studied in this paper provides valuable insights for the planning and design of large-scale wind farm bases and can serve as a guide in tasks such as site division and layout design for wind power projects.

Key words: offshore wind farm, micro-siting optimization, mayfly algorithm, regular layout arrangement

中图分类号:

TK89

孙宇, 许昌, 韩星星, 蒋小雪, 谭康辉. 基于蜉蝣算法的变间距规则排布海上风电场微观选址优化方法[J]. 《新能源科技》杂志社, 2025, 6(1): 28-34.

SUN Yu, XU Chang, HAN Xingxing, JIANG Xiaoxue, TAN Kanghui. Optimization method for micro-siting of offshore wind farms based on the mayfly algorithm with variable spacing rules[J]. New Energy Technology Magazine Agency, 2025, 6(1): 28-34.

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《新能源科技》杂志社
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基于蜉蝣算法的变间距规则排布海上风电场微观选址优化方法

Optimization method for micro-siting of offshore wind farms based on the mayfly algorithm with variable spacing rules

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基于蜉蝣算法的变间距规则排布海上风电场微观选址优化方法

Optimization method for micro-siting of offshore wind farms based on the mayfly algorithm with variable spacing rules

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