Inferring connectivity model from meter measurements in distribution networks

Abstract

We present a novel analytics approach to infer the underlying interconnection between various metered entities in a radial distribution network. Our approach uses a time series of power measurements collected from different meters in the distribution grid and infers the underlying network between these meters. The collected measurements are used to set up a system of linear equations based upon the principle of conservation of energy. The equations are analyzed to estimate a tree network that optimally fits the time series of meter measurements. We study experimentally the number of measurements needed to infer the true underlying connectivity with the help of both synthetic and real smart meter measurements in the noiseless setting.

Graphical Models in Meshed Distribution Grids: Topology Estimation, Change Detection & Limitations

“…Researchers have looked at multiple approaches, both active and passive, in learning using varying measurement type and availability. Example of such schemes include greedy methods [5], [6], voltage signature based methods [7], [8], probing schemes [9], imposing graph cycle constraints [10] and iterative schemes for addressing missing data [11], [12]. In contrast to the referred work that employ static voltage samples, learning schemes that exploit dynamic voltage measurements are reported in [13], [14].…”

Joint Estimation of Topology and Injection Statistics in Distribution Grids With Missing Nodes

“…For availability of both voltage and injection measurements, [14], [15] design algorithms for topology and parameter (line impedance) identification that considers missing nodes. In agnostic data-driven efforts, topology and parameter identification techniques using machine learning techniques have been discussed in [16], [17].…”

“…Computational Complexity: The complexity of Algorithm 3 can be computed similar to that of Algorithm 2 as the logic is similar. The primary difference in complexity arises due to separation between siblings and grandchildren of a node in Step (11)(12)(13)(14)(15)(16)(17) and identifying its missing children. This has complexity O(|V | 2 ).…”

Leveraging advanced metering infrastructure for distribution grid asset management

“…While before smart grid, this kind of information was not necessarily needed for utility operations, it is essential for estimating transformer load based on the meter energy measurements of the premises it provides service to. The authors in [13] developed an approach to reconstruct end-to-end connectivity in the distribution grid, but it assumes smart meters deployed at all topological nodes of the network, including at the transformers and feeder heads.…”