Three-Phase Network Phase Labeling via Adjacency Matrix Inference
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Solution Overview
Problem
Utility companies lose knowledge of phase labels at lateral and customer points in three-phase electric power distribution networks due to restoration, reconfiguration, maintenance, and addition of distributed energy resources, leading to reduced operational efficiency.
Innovation Solution
A method and system using an adjacency matrix to determine phase labels by analyzing electrical connections and sensor data, minimizing a mathematical function to derive phase labels for laterals and customers in a three-phase power distribution network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual tracking of phase labels is used during network changes, then operational control is maintained, but operational efficiency decreases due to time-consuming manual updates and increased human error
Solution Approach 1:
The system automatically determines phase labels by analyzing electrical connection data and sensor measurements without requiring manual intervention. The automated phase determination system serves itself by using existing network data to maintain phase label information, eliminating the need for manual tracking while preventing information loss.
Solution Approach 2:
The system uses sensor data from the network as feedback to continuously verify and update phase label determinations. By monitoring electrical characteristics and comparing them against the adjacency matrix model, the system maintains accurate phase label information dynamically without manual input.
2Measurement precision
If comprehensive monitoring of all network points is implemented, then phase label accuracy is maintained, but system complexity and cost increase
Solution Approach 1:
The adjacency matrix serves as an intermediary mathematical model that represents the entire network topology. Instead of directly monitoring all network points, the system uses this matrix representation to infer phase labels at any point by analyzing connections and sensor data from limited locations, reducing monitoring complexity while maintaining accuracy.
Solution Approach 2:
The system transforms the physical monitoring problem into a mathematical dimension by using the adjacency matrix representation. Phase labels are determined by analyzing the mathematical relationships in the matrix rather than direct physical measurements at every point, enabling accurate determination with fewer sensors.
3Adaptability or versatility
If the network configuration is frequently changed to meet customer demands, then network adaptability improves, but phase label knowledge is lost requiring re-balancing operations
Solution Approach 1:
The phase determination system is designed to be dynamic, automatically adapting to network reconfigurations. When the network topology changes, the system updates the adjacency matrix and re-determines phase labels based on the new configuration and sensor data, maintaining accurate phase information through changes rather than losing it.
Solution Approach 2:
The system proactively determines and updates phase labels immediately when network changes occur, rather than waiting for information to be lost. By continuously monitoring electrical characteristics and updating phase determinations in real-time, the system prevents information loss before it occurs.
Data Source
AI summary
A method for determining a plurality of phase labels, each phase label identifying a phase of a voltage at one of a lateral or a customer in a three phase power distribution network, comprises receiving data indicating a plurality of electrical connections of the three phase power distribution network; receiving a plurality of sensor data values, each sensor data value being a measured electrical characteristic from at least a portion of the customers; receiving a plurality of known phase labels associated with a portion of the laterals and customers; generating a form of an adjacency matrix associated with a graph of the electrical connections of the three phase power distribution network; determining the values of the adjacency matrix which minimize a mathematical function of the sensor data values and the known phase labels; and deriving the phase label for each lateral and customer from the adjacency matrix.