Ranking Power Distribution Network Assets by Downstream Event Probability
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Solution Overview
Problem
In radial power distribution networks, identifying the likely causes of network conditions such as outages or voltage anomalies is challenging due to the large number of assets and sensors, as existing methods require numerous event reports and lack efficient probabilistic analysis to pinpoint malfunctioning assets.
Innovation Solution
A method and system for ranking power distribution network assets based on downstream events, which involves receiving sensor communications, calculating the probability of assets causing problems, and determining the spread probability of these issues, allowing for the identification of assets with the highest malfunction probability and subsequent control measures to mitigate problems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods are used to identify malfunctioning assets in radial power distribution networks, then comprehensive monitoring of all assets is achieved, but the number of required event reports increases significantly and the time to pinpoint the malfunctioning asset increases
Solution Approach 1:
The patent segments the radial power distribution network into multiple zones based on the topological structure, with each zone containing specific assets and sensors. This segmentation allows the system to focus analysis on relevant zones rather than evaluating all assets network-wide, thereby reducing the time and computational resources needed to identify malfunctioning assets while maintaining identification accuracy.
Solution Approach 2:
The system pre-calculates and stores the topological relationships, zone assignments, and probabilistic models for all assets before actual monitoring begins. When events occur, the system can immediately apply these pre-established structures and models to rapidly identify malfunctioning assets without performing comprehensive real-time analysis of all network components.
2Loss of information
If comprehensive monitoring of all assets is implemented, then complete network visibility is achieved, but the complexity of data processing and analysis increases
Solution Approach 1:
The patent applies different analysis methods and data processing approaches to different zones based on their specific characteristics, such as the type of assets present, sensor configurations, and historical event patterns. This localized approach allows the system to maintain complete network visibility while simplifying data processing by tailoring the complexity of analysis to the specific needs of each zone rather than applying uniform complex processing across the entire network.
Solution Approach 2:
The system extracts and focuses on the most relevant features and parameters from the comprehensive sensor data in each zone, such as event types, asset states, and probabilistic indicators. By extracting only the critical information needed for malfunction identification rather than processing all raw data, the system maintains complete information availability while reducing processing complexity.
3Measurement precision
If probabilistic analysis is applied to all assets simultaneously, then accurate malfunction identification is achieved, but the computational resources and time required increase
Solution Approach 1:
The patent divides the network into zones and performs probabilistic analysis separately for each zone rather than simultaneously for all assets. This segmentation allows the computational workload to be distributed and processed in parallel, maintaining accurate malfunction probability calculations while significantly improving analysis speed and reducing computational resource requirements.
Solution Approach 2:
The system performs probabilistic analysis on a partial set of assets within each zone that are most likely to be malfunctioning based on event patterns and topological relationships, rather than calculating probabilities for all assets in the network. This partial action approach maintains sufficient accuracy for effective identification while reducing computational complexity and processing time.
Data Source
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AI summary
A method for ranking network assets based on downstream events may include: receiving communications from one or more sensors in a power distribution network, the communications indicating the occurrence of a network event; calculating a probability of a network asset causing a problem indicated by the event for each network asset in an affected area of the network; calculating a spread probability of the network asset causing the problem for each network asset in the affected area of the network; based on the probability and the spread probability, calculating a probability of the network asset malfunctioning for each network asset in the affected area of the network; comparing the probability of the network asset malfunctioning to a threshold value; based on the comparison, determining a network asset having a highest probability of malfunctioning; and controlling one of more other network assets to mitigate the problem.