Ohmic Matrix Model for Electrical Network Anomaly Detection
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Solution Overview
Problem
Current methods for detecting anomalies in electrical networks, such as meter-transformer pairing errors and electricity theft, are hindered by variable line voltage and the presence of electromechanical meters, leading to imprecise low-voltage network modeling.
Innovation Solution
A computer-implemented method that generates an ohmic matrix model from consumption measurements, compares resistive quantities, and uses inverse matrix models to detect anomalies by analyzing relative voltage drops and unmetered currents, while adjusting for modeling conditions and anomalies detected.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods are used to detect anomalies in electrical networks, then the detection process is simpler, but the precision of anomaly detection deteriorates due to variable line voltage and electromechanical meters
Solution Approach 1:
The patent introduces an ohmic matrix model as an intermediary representation of the electrical network. This matrix model serves as a mediator between the raw consumption measurements and the anomaly detection process, allowing for precise comparison of electrical parameters while accounting for variable line voltage and electromechanical meter effects without requiring direct complex measurements
Solution Approach 2:
The patent transforms the anomaly detection problem by changing parameters from direct voltage and current measurements to resistive quantities derived from consumption measurements. By computing resistance values from power and voltage data and comparing them against the ohmic matrix model, the system achieves precise anomaly detection while handling variable line voltage conditions
2Reliability
If the system accounts for variable line voltage and electromechanical meters, then the reliability of network modeling improves, but the complexity of the detection system increases
Solution Approach 1:
The ohmic matrix model is constructed self-service from the available consumption measurements themselves. The model uses power and voltage measurements from the meters to compute resistive quantities and build the network representation, eliminating the need for separate measurement infrastructure or complex calibration procedures while improving reliability
Solution Approach 2:
The ohmic matrix model serves multiple functions simultaneously: it represents the network topology, accounts for variable line voltage effects, handles electromechanical meter characteristics, and provides the basis for anomaly detection. This multi-functionality improves modeling reliability without proportionally increasing system complexity
3Measurement precision
If consumption measurements are used to generate ohmic matrix models, then the accuracy of voltage drop analysis improves, but the computational requirements increase
Solution Approach 1:
The patent segments the electrical network into discrete components represented by matrix elements, where each element corresponds to a specific network segment's resistive characteristics. This segmentation allows for precise voltage drop analysis at each segment while keeping computational requirements manageable through structured matrix operations
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method provides a precise diagnosis of electrical network anomalies, including meter-transformer pairing errors, defective meters, and electricity theft, by accurately modeling the low-voltage network and identifying deviations from expected voltage drops and currents.
Implementation Method 1
generating an ohmic matrix model of the electrical network, the ohmic matrix model having currents carried by the meters as input, relative voltage drops of the meters referenced to a voltage of a reference node located on the electrical network as output, and resistive quantities initially determined by currents and voltages
Data Source
AI summary
The disclosed method detects anomalies in an electrical network. An ohmic matrix model of the network is initially generated from consumption measurements produced by meters connected to a same transformer. The model has currents carried by the meters as input, relative voltage drops of the meters referenced to a voltage of a reference node located on the network as output, and resistive quantities initially determined by currents and voltages based on the consumption measurements as matrix terms, the relative voltage being a voltage difference between a voltage determined for a meter and an average of voltages determined for a set of meters of the network. The model is iteratively modified according to detected anomalies, and a diagnosis of the network characterizing the detected anomalies is provided.