李岸滕, 赵健, 宣羿, 孙智卿. 基于电气特征和地理相关性的配电网线变关系辨识[J]. 现代电力. DOI: 10.19725/j.cnki.1007-2322.2022.0464
引用本文: 李岸滕, 赵健, 宣羿, 孙智卿. 基于电气特征和地理相关性的配电网线变关系辨识[J]. 现代电力. DOI: 10.19725/j.cnki.1007-2322.2022.0464
LI Anteng, ZHAO Jian, XUAN Yi, SUN Zhiqing. Identification of Feeder-transformer Connectivity in Distribution Network Based on Electrical Characteristics and Geographic Relevance[J]. Modern Electric Power. DOI: 10.19725/j.cnki.1007-2322.2022.0464
Citation: LI Anteng, ZHAO Jian, XUAN Yi, SUN Zhiqing. Identification of Feeder-transformer Connectivity in Distribution Network Based on Electrical Characteristics and Geographic Relevance[J]. Modern Electric Power. DOI: 10.19725/j.cnki.1007-2322.2022.0464

基于电气特征和地理相关性的配电网线变关系辨识

Identification of Feeder-transformer Connectivity in Distribution Network Based on Electrical Characteristics and Geographic Relevance

  • 摘要: 准确的配电网线变关系是线损计算、运维检修等电网业务的重要数据基础,而依靠人工排查线变关系的方法成本高、效率低,且无法适用于结构日趋复杂且变动频繁的配电网。在此背景下,提出一种基于配电网量测数据和设备档案信息的配电网线变关系辨识方法。首先,基于电压相似性原理,将电气距离邻近的配电变压器进行合并,并构建虚拟配变来代替作为后续输入。然后,分别构建线变能量差异和电压相似性评估指标,建立基于电气特征指标化的线变关系辨识模型。最后,为减小量测数据质量对模型的影响,在原模型的基础上加入配电变压器的地理位置信息,提出一种考虑地理相关性的改进优化辨识模型。在实际的配电系统中验证了该方法在提升线变关系辨识准确率等方面具有显著优势,有一定的实际工程应用价值和指导作用。

     

    Abstract: The accurate feeder-transformer connectivity of distribution network serves as a crucial data basis for power grid operations, such as loss calculation, operation and maintenance. The manual investigation method, however, incurs high cost and exhibits low efficiency, making it unsuitable for its application in the distribution network characterized by increasingly complex network structure and frequent changes. In view of this, a method to identify the feeder-transformer connectivity is proposed based on the measurement data and the equipment archives information. Firstly, the transformers that are electrically close to each other are merged based on the principle of voltage similarity, and then a virtual transformer is constructed as the subsequent input. After that, the evaluation indexes for feeder-transformer energy difference and voltage similarity are constructed respectively, followed by the establishment of an optimal identification model for feeder-transformer connectivity based on electrical characteristic indexation. Finally, to reduce the impact of measurement data quality on the model, the geographical location information of distribution transformer is added to the original model. Consequently, an improved optimal identification model considering geographical correlation is obtained. It has been verified in the actual distribution system that this method demonstrates significant advantages in improving the identification accuracy of line transformer relationship, and holds certain practical engineering application value as well as a guiding role.

     

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