考虑强对流天气的农村配电网树线矛盾风险预警技术

Fengjun Li, Fuxing Yao, Haoyu Tan, Qian Sun, H. Yin, S. Miao
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引用次数: 0

摘要

树线矛盾是指在电力线架设空间种植树木与保证电力线安全稳定运行之间的冲突。在强对流天气下,林木线矛盾进一步加剧。一旦触发树栅接地故障,将严重影响农村配电网的供电可靠性。针对此,本文提出了一种考虑强对流天气的农村配电网树线矛盾分区预警机制。首先,针对树篱接地故障记录的不平衡问题,采用合成少数派过采样技术(SMOTE)算法将部分多数类样本替换为少数派样本,在保持数据集规模不变的基础上实现数据预处理;其次,结合强对流天气的6项气象监测指标,建立了基于极限学习机(ELM)的强对流天气与树木屏障接地风险映射模型;最后,以中国某农村配电网为例进行分析。结果表明,该模型能有效反映强对流天气与树障接地故障的映射关系,准确实现树障接地风险的分区预警,具有良好的鲁棒性和可扩展性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Tree-line Contradictory Risk Early Warning Technology of Rural Distribution Network Considering Severe Convective Weather
Tree-line contradiction refers to the conflict between planting trees in the power line erection space and ensuring the safe and stable operation of power lines. In severe convective weather, the tree-line contradiction is further intensified. Once the tree-barrier grounding fault is triggered, the power supply reliability of the rural distribution network will be seriously affected. Aiming at this, a zonal early warning mechanism for tree-line contradiction of rural distribution networks considering severe convective weather is proposed in this paper. Firstly, due to the imbalance of tree-barrier grounding fault records, the Synthetic Minority Oversampling Technique (SMOTE) algorithm is used to replace part of the majority class samples with minority class samples, and the data preprocessing is realized based on keeping the scale of the data set unchanged. Secondly, combined with six meteorological monitoring indexes of severe convective weather, a mapping model of severe convective weather and tree barrier grounding risk is established based on Extreme Learning Machine (ELM). Finally, the data of a rural distribution network in China is used for example analysis. The results show that the proposed model can effectively reflect the mapping relationship between severe convective weather and tree-barrier grounding faults, and accurately realize the zonal warning of tree-barrier grounding risk, which has good robustness and scalability.
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