基于改进人工蜂群算法的海上风电场柔直并网系统次同步振荡特性分析与抑制

魏书荣; 冯启睿; 何方; 刘阳

doi:10.19725/j.cnki.1007-2322.2024.0070

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基于改进人工蜂群算法的海上风电场柔直并网系统次同步振荡特性分析与抑制

新能源电力系统 | 更新时间：2026-06-02

- 基于改进人工蜂群算法的海上风电场柔直并网系统次同步振荡特性分析与抑制
- Characterization and Suppression of Sub-synchronous Oscillations in Flexible Grid-connected Offshore Wind Farm Systems Equipped With SVGs Based Improved Artificial Bee Colony Algorithm
- 现代电力 2026年43卷第3期页码：492-498
- 作者机构：
  
  教育部海上风电技术工程中心(上海电力大学), 上海市杨浦区,200093
- 作者简介：
  
  魏书荣(1980)，女，博士，教授，研究方向为海上风电优化规划与故障诊断，E-mail： wsrmail@163.com
  冯启睿(1997)，男，硕士研究生，研究方向为海上风电小干扰稳定性，E-mail：568842812@163.com
  何方(1999)，女，硕士研究生，研究方向为海上风电场集群灵活性，E-mail：hf991219@163.com
  刘阳(1997)，男，硕士研究生，研究方向为海上风电场集群稳定域，E-mail：790177420@qq.com
- 基金信息：
  
  国家自然科学基金项目(52377063);上海市教委自然科学重大项目(2021-01-07-00-07-E00122);上海高校特聘教授(东方学者)特聘教授(TP2020066);上海科技创新行动计划(22DZ1206100)。
- DOI：10.19725/j.cnki.1007-2322.2024.0070
  中图分类号： 3
- 纸质出版：2026
- 稿件说明：
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魏书荣, 冯启睿, 何方, 等. 基于改进人工蜂群算法的海上风电场柔直并网系统次同步振荡特性分析与抑制[J]. 现代电力, 2026,43(3):492-498.

WEI Shurong, FENG Qirui, HE Fang, et al. Characterization and Suppression of Sub-synchronous Oscillations in Flexible Grid-connected Offshore Wind Farm Systems Equipped With SVGs Based Improved Artificial Bee Colony Algorithm[J]. 2026, 43(3): 492-498.
魏书荣, 冯启睿, 何方, 等. 基于改进人工蜂群算法的海上风电场柔直并网系统次同步振荡特性分析与抑制[J]. 现代电力, 2026,43(3):492-498. DOI： 10.19725/j.cnki.1007-2322.2024.0070.

WEI Shurong, FENG Qirui, HE Fang, et al. Characterization and Suppression of Sub-synchronous Oscillations in Flexible Grid-connected Offshore Wind Farm Systems Equipped With SVGs Based Improved Artificial Bee Colony Algorithm[J]. 2026, 43(3): 492-498. DOI： 10.19725/j.cnki.1007-2322.2024.0070.

摘要

海上风电经柔直并网系统的次同步振荡（sub-synchronous oscillation，SSO）问题频繁出现，亟需掌握海上风电场、柔直系统、静止无功发生器（static var generator，SVG）对SSO的作用机理，提出有效的次同步振荡抑制方式。构建含有SVG的直驱风机海上风电场经柔直并网系统小信号模型，基于特征值分析法、参与因子法，研究系统振荡模式，得到海上风电场经柔直并网发生次同步振荡的主导状态变量。采用混沌映射改进人工蜂群算法（artificial bee colony

ABC），优化主导状态变量涉及的控制参数，进一步抑制SSO发生。分析结果表明，海上风电场、柔直系统与SVG共同影响系统的SSO振荡模态，其中海上风电场与柔直系统在不同振荡模态下对SSO的影响不同，SVG对SSO的影响不受振荡模态变化的影响。进一步，通过改进ABC算法优化控制器参数，可以改善系统特征根分布并提高阻尼比，有效提升系统稳定性。

Abstract

The sub-synchronous oscillation (SSO) problem in offshore wind farms connected to grids through flexible DC systems occurs frequently. It is urgent to thoroughly understand the mechanism of offshore wind farm

flexible DC system

and SVG on SSO

and to develop effective sub-synchronous oscillation suppression methods. A small-signal model for a direct-drive wind turbine-based offshore wind farm equipped with SVG is constructed. Using the eigenvalue analysis method and the participation factor method

the system oscillation mode is investigated to identify the dominant state variables associated with SSO in offshore wind farms connected to the grid through flexible DC systems. The control parameters involved in the dominant state variables are optimized through the improved artificial bee colony algorithm (ABC) with chaotic mapping

aiming to further suppress the occurrence of SSO. The analysis results indicate that the offshore wind farm

the flexible DC system and the SVG jointly affect the oscillation mode of system SSO. Specifically

the offshore wind farm and the flexible DC system have different impacts on SSO under different oscillation modes

and the impact of the SVG on the SSO remains unaffected by changes in the oscillation mode. Further optimization of the controller parameters through the improvements to the ABC algorithm leads to an enhanced system eigenroot distribution and damping ratio

which effectively enhances the system stability.

关键词

Keywords

references

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