论文标题
基于图理论的仪表转换器映射的识别
Explainable Graph Theory-Based Identification of Meter-Transformer Mapping
论文作者
论文摘要
分布式能源资源对环境更好，但可能会导致分配网格中的变压器过载，呼吁恢复仪表转换器映射以提供情境意识，即变压器加载。挑战在于恢复两个常见场景的仪表转换器（M.T.）映射，例如，仪表及其母体变压器之间的较大距离或仪表的消耗模式与非父母变压器的仪表的高相似性。过去的方法要么像传输网格中一样采用多种数据，要么忽略上述两个常见方案。因此，我们建议通过使用跨频谱嵌入来利用上述观察结果，该属性是跨晶型仪表消耗不相同的，并且数据中的噪声受到限制，以便所有基于电压的laplacian矩阵的最小特征值都比下一个最小的特征性laplacian laplac Matrix的特征值小。我们还基于此理解提供了保证。此外，我们通过利用位置信息来部分放松假设，以帮助地理位置较远但电压相似的区域的电压信息。我们合作伙伴实用程序的IEEE测试系统和真实馈线的数值模拟表明，所提出的方法正确识别了M.T.映射。
Distributed energy resources are better for the environment but may cause transformer overload in distribution grids, calling for recovering meter-transformer mapping to provide situational awareness, i.e., the transformer loading. The challenge lies in recovering meter-transformer (M.T.) mapping for two common scenarios, e.g., large distances between a meter and its parent transformer or high similarity of a meter's consumption pattern to a non-parent transformer's meters. Past methods either assume a variety of data as in the transmission grid or ignore the two common scenarios mentioned above. Therefore, we propose to utilize the above observation via spectral embedding by using the property that inter-transformer meter consumptions are not the same and that the noise in data is limited so that all the k smallest eigenvalues of the voltage-based Laplacian matrix are smaller than the next smallest eigenvalue of the ideal Laplacian matrix. We also provide a guarantee based on this understanding. Furthermore, we partially relax the assumption by utilizing location information to aid voltage information for areas geographically far away but with similar voltages. Numerical simulations on the IEEE test systems and real feeders from our partner utility show that the proposed method correctly identifies M.T. mapping.
