| 引用本文: | 李攀龙,侯俊杰,樊艳芳,等.基于卷积功率能量比的全直流风电系统汇集线路故障选线方法[J].电力系统保护与控制,2025,53(9):154-165.[点击复制] |
| LI Panlong,HOU Junjie,FAN Yanfang,et al.Fault line selection scheme for collection lines in the all-DC wind power systems based on convolutional power energy ratio[J].Power System Protection and Control,2025,53(9):154-165[点击复制] |
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| 摘要: |
| 全直流风电系统能够有效地解决交流电缆对地电容导致的无功功率及电压波动等问题，逐渐成为研究热点之一。针对全直流风电系统汇集支路多，相邻线路间的故障特征差异小和阈值整定等问题，提出一种基于卷积功率能量比的全直流风电系统汇集线路故障选线方法。首先，分析了故障线路与非故障线路的频域暂态功率幅值特征，发现在特征频带下，故障线路的暂态功率大于非故障线路。其次，构造了一种时域故障特征量——卷积功率，对频域暂态功率特征进行有效提取。同时，为了提高耐受过渡电阻能力，提出了各汇集线路与汇流母线出口处时域卷积功率能量比，分析发现在特征频带内时域卷积功率能量比可以有效识别故障线路。结合故障启动判据、选极判据构成故障选线识别方案。最后，PSCAD/EMTDC仿真结果表明：所提选线方法可以正确识别全直流风电系统汇集线路中的故障线路，在80 Ω过渡电阻和20 dB的噪声干扰下仍能有效识别故障，且无需仿真整定。 |
| 关键词: 全直流风电系统 故障选线 特征频带 卷积功率能量比 |
| DOI：10.19783/j.cnki.pspc.240864 |
| 投稿时间：2024-07-06修订日期：2024-11-03 |
| 基金项目:国家重点研发计划项目资助(2021YFB1507000)；国家自然科学基金项目资助(52442705)；新疆维吾尔自治区自然科学基金项目资助(2022D01C662)；“天池英才”引进计划项目资助 |
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| Fault line selection scheme for collection lines in the all-DC wind power systems based on convolutional power energy ratio |
| LI Panlong1,HOU Junjie1,FAN Yanfang1,SONG Guobing1,2,WU Xiaofang3,LIU Mengyao1 |
| (1. School of Electrical Engineering, Xinjiang University, Urumqi 830046, China;
2. School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 711049, China;
3. Electric Power Research Institute of State Grid Xinjiang Electric Power Co., Ltd., Urumqi 830011, China) |
| Abstract: |
| All-DC wind power systems can effectively address issues such as reactive power and voltage fluctuations caused by AC cable capacitance, making them a growing focus of research. To tackle challenges such as the large number of collection branches, small differences in fault characteristics between adjacent lines, and difficulties in threshold setting, this paper proposes a fault line selection method based on the convolutional power energy ratio for all-DC wind power systems. First, the characteristics of transient power amplitude in the frequency domain for faulted and non-faulted lines are analyzed, revealing that within a characteristic frequency band, the transient power of faulted lines is greater than that of the non-faulted lines. Second, convolution power, as a time-domain fault characteristic quantity, is constructed to effectively extract the frequency domain power characteristics. Additionally, to improve the ability to withstand transition resistance, a time-domain convolutional power energy ratio is proposed between each collection line and the outlet of the collection bus. Analysis shows that the time-domain convolutional power energy ratio can effectively identify the faulty line within the characteristic frequency band. Combined with fault initiation and fault pole selection criteria, a complete fault line selection scheme is developed. Finally, PSCAD/EMTDC simulation results show that the proposed method can correctly identify faulty lines in all-DC wind power systems under fault resistance of 80 Ω and noise interference of 20 dB, without the need for simulation-based threshold tuning. |
| Key words: all-DC wind power system fault line selection characteristic frequency band convolutional power energy ratio |
