考虑大规模风电接入的电网薄弱区域动态无功需求评估

戴剑丰, 王子博, 谢嫦嫦, 汤奕

太阳能学报 ›› 2024, Vol. 45 ›› Issue (9) : 60-69.

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太阳能学报 ›› 2024, Vol. 45 ›› Issue (9) : 60-69. DOI: 10.19912/j.0254-0096.tynxb.2023-0534

考虑大规模风电接入的电网薄弱区域动态无功需求评估

  • 戴剑丰1,2, 王子博1,2, 谢嫦嫦3, 汤奕3
作者信息 +

DYNAMIC REACTIVE POWER DEMAND ASSESSMENT IN WEAK AREA OF POWER GRID CONSIDERING LARGE-SCALE WIND POWER INTEGRATION

  • Dai Jianfeng1,2, Wang Zibo1,2, Xie Changchang3, Tang Yi3
Author information +
文章历史 +

摘要

提出考虑大规模风电接入的电网薄弱区域动态无功需求评估方法。首先,采用随机矩阵理论对大规模风电场群接入的电力系统进行电压薄弱节点和薄弱区域辨识,若风电接入地区为电压薄弱区域,则令风电场群进入紧急电压控制预决策环节;然后,基于BP神经网络建立薄弱区域内暂态电压稳定指标计算模型,并在此基础上提出基于灵敏度的薄弱区域动态无功需求评估方法;最后,在风电场群接入的IEEE 10机 39节点系统上对该文所提方法的有效性进行验证。

Abstract

A dynamic reactive power demand assessment method considering large-scale wind power access is proposed in this paper. Firstly, the random matrix theory is applied to identify weak voltage nodes and areas in power system where the large-scale wind farm cluster is integrated. If the area where the wind farm cluster is integrated is the weak voltage area, the wind farm cluster enters the pre-decision link of emergency voltage control. Secondly, the calculation model of transient voltage stability index in weak areas is established based on BP neural network, and a sensitivity based dynamic reactive power demand assessment method was proposed. Finally, the effectiveness of the proposed method is verified on the IEEE 10 machine 39 bus system connected to the wind farm group.

关键词

风电 / 无功功率 / 电压控制 / 神经网络 / 随机矩阵理论 / 电压薄弱区域辨识

Key words

wind power / reactive power / voltage control / neural networks / random matrix theory / voltage weak area identification

引用本文

导出引用
戴剑丰, 王子博, 谢嫦嫦, 汤奕. 考虑大规模风电接入的电网薄弱区域动态无功需求评估[J]. 太阳能学报. 2024, 45(9): 60-69 https://doi.org/10.19912/j.0254-0096.tynxb.2023-0534
Dai Jianfeng, Wang Zibo, Xie Changchang, Tang Yi. DYNAMIC REACTIVE POWER DEMAND ASSESSMENT IN WEAK AREA OF POWER GRID CONSIDERING LARGE-SCALE WIND POWER INTEGRATION[J]. Acta Energiae Solaris Sinica. 2024, 45(9): 60-69 https://doi.org/10.19912/j.0254-0096.tynxb.2023-0534
中图分类号: TM732   

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基金

国家自然科学基金(52261145704)

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