Guaranteed Phase & Topology Identification in Three Phase Distribution Grids

@article{Bariya2020GuaranteedP,
  title={Guaranteed Phase \& Topology Identification in Three Phase Distribution Grids},
  author={Mohini Bariya and Deepjyoti Deka and Alexandra von Meier},
  journal={IEEE Transactions on Smart Grid},
  year={2020},
  volume={12},
  pages={3605-3612}
}
We present a method for joint phase identification and topology recovery in unbalanced three phase radial networks using only voltage measurements. By recovering phases and topology jointly, we utilize all three phase voltage measurements and can handle networks where some buses have a subset of three phases. Our method is theoretically justified by a novel linearized formulation of unbalanced three phase power flow and makes precisely defined and reasonable assumptions on line impedances and… 
[PDF] Semantic Reader
6 Citations
Background Citations
3
Methods Citations
2

Figures from this paper

6 Citations

Distribution Network Topology Identification Method Based on Knowledge Graph

Accurate topology is the basis for refined management of the distribution network. In order to make full use of the data available in the distribution network when the topology identification work is…

Virtual Voltage Measurements via Averaging for Phase Identification in Power Distribution Systems

In phase identification, the goal is to determine the phase connections of loads within a Connectivity Model (CM) of a power distribution system. Knowledge of the correct phase connections is…

Learning Distribution Grid Topologies: A Tutorial

—Unveiling feeder topologies from data is of paramount importance to advance situational awareness and proper utilization of smart resources in power distribution grids. This tutorial summarizes,…

Phase Identification of Distribution System Users Through a MILP Extension of State Estimation

—To address the challenges and exploit the opportu- nities that the decarbonization of the energy sector is bringing about, advanced distribution network management and operation strategies are being…

Distribution Systems AC State Estimation via Sparse AMI Data Using Graph Signal Processing

This work establishes and validates a Grid Graph Signal Processing framework for estimating the state vector of a radial distribution feeder using a GSP interpretation of Ohm's law and shows that the system state can be well approximated with relatively few components that correspond to low-pass Graph Fourier Transform (GFT) frequencies.

Denoising with Singular Value Decomposition for Phase Identification in Power Distribution Systems

Singular Value Decomposition with the optimal Singular Value Hard Threshold (SVHT) as part of a feature engineering pipeline to denoise data matrices of voltage magnitude measurements to reduce Frobenius error and increase the average phase identification accuracy.

References

SHOWING 1-10 OF 35 REFERENCES

Unbalanced Three-Phase Distribution Grid Topology Estimation and Bus Phase Identification

This paper proves that the Chow-Liu algorithm finding the topology by utilizing power flow equations and the conditional independence relationships implied by the radial multi-phase structure of distribution grids with the presence of incorrect bus phase labels can be correctly identified using voltage measurements.

Topology Estimation Using Graphical Models in Multi-Phase Power Distribution Grids

A learning framework to reconstruct the radial operational structure of the distribution grid from synchronized voltage measurements and uses conditional independence tests for continuous random variables that is applicable to a wide class of probability distributions, and in particular Gaussian, for injections.

Phase identification in smart grids

The techniques are novel as they are purely based upon a time series of electrical power measurements taken at the household and at the distributing transformer and solutions can be retrieved using branch and bound search algorithms implemented by MIP solvers such as CPLEX.

Estimating distribution grid topologies: A graphical learning based approach

A novel graphical learning based approach to estimate the radial operational grid structure using voltage measurements collected from the grid loads and it is proven that the scheme can be used for several power flow laws (DC or AC approximations) and is independent of the specific probability distribution controlling individual bus's power usage.

Phase Balancing Using Energy Storage in Power Grids Under Uncertainty

This work considers a substation connected to multiple phases, each with single-phase loads, generation, and energy storage, and proposes both centralized and distributed real-time algorithms taking into account system uncertainty.

Distributed Energy Resources Topology Identification via Graphical Modeling

This paper proposes a methodology that utilizes new data from sensor-equipped DER devices to obtain the distribution grid topology and presents a graphical model to describe the probabilistic relationship among different voltage measurements.

Maximum Marginal Likelihood Estimation of Phase Connections in Power Distribution Systems

By linearizing the three-phase power flow manifold, a physical model is developed, which links the phase connections to the smart meter measurements, and an efficient solution method is proposed by decomposing the original problem into subproblems with a binary least-squares formulation.

Graph Algorithms for Topology Identification Using Power Grid Probing

A suite of graph-based topology identification algorithms is developed here, aimed at adopting inverter probing for feeder processing and ensuring recoverability guarantees carry over from the noiseless to the noisy setup with high probability.

A novel approach for phase identification in smart grids using Graph Theory and Principal Component Analysis

This work proposes an algorithm for inferring phase connectivity from noisy measurements based on Principal Component Analysis (PCA) and its Graph Theoretic interpretations, using energy measurements in equally timed short intervals, generated from smart meters.

Identification of power distribution network topology via voltage correlation analysis

This work uses an approximate model for the grid voltage magnitudes to propose an algorithm that performs well when an exact nonlinear model of the grid voltages is adopted, when realistic power demand profiles are considered, and when the voltage measurements are affected by measurement noise.