Connectivity Identification in Electrical Networks
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Solution Overview
Problem
Existing systems face difficulties in accurately identifying connectivity conditions in electrical networks, particularly in complex situations such as large load distributions, multiple phase connections, and cogeneration scenarios, where distinguishing between connection points becomes challenging due to combined current values and mixed power sources.
Innovation Solution
A system comprising first and second event detection means with current sensors and clocks, configured to detect changes in electric current magnitude and time patterns at load connection points and distribution lines, respectively, with connectivity checking means processing these data to determine connection lines based on similarity in event times, and capable of identifying non-technical losses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If current magnitude comparison is used to identify connectivity, then the method is simple to implement, but the identification becomes erroneous or impossible in complex situations with large load distributions and multiple phase connections
Solution Approach 1:
The patent transitions from one-dimensional current magnitude comparison to two-dimensional analysis by incorporating both magnitude and temporal characteristics (time patterns, event sequences, duration of current changes). This dimensional expansion enables differentiation of connectivity sources in complex scenarios where magnitude alone is insufficient.
Solution Approach 2:
The system changes the parameters used for connectivity identification from static current magnitude values to dynamic temporal parameters including event timing, duration, sequence patterns, and rate of change. This parameter transformation allows accurate identification even when multiple loads contribute to the same line current.
2Measurement precision
If event detection is performed at multiple connection points to improve identification accuracy, then connectivity can be determined more reliably, but the system complexity increases due to multiple detection means and data processing requirements
Solution Approach 1:
The event detection means are designed with multi-functionality, serving both local connectivity identification and contributing data to network-wide analysis. Each detection device performs local event detection, temporal pattern recording, and participates in centralized comparison, reducing the need for dedicated specialized equipment at each point.
Solution Approach 2:
The patent combines multiple detection functions into integrated event detection means that simultaneously perform local monitoring and network-wide event correlation. The centralized processing unit merges data from multiple sources, performing unified analysis that reduces overall system complexity despite the distributed nature of detection points.
3Measurement precision
If chronological recording of events is maintained for all detection means, then accurate time pattern comparison is possible, but data storage and processing requirements increase
Solution Approach 1:
The system extracts only the essential temporal characteristics from complete event data, storing key parameters such as event timing, duration, and sequence patterns rather than maintaining continuous detailed records. This extraction approach retains sufficient information for accurate time pattern comparison while significantly reducing storage requirements.
Solution Approach 2:
The patent implements partial recording by focusing on significant events that indicate connectivity changes rather than continuously recording all current variations. By capturing only relevant events above certain thresholds or with specific temporal patterns, the system achieves accurate connectivity identification with reduced data storage and processing demands.
Data Source
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AI summary
The system comprises detecting the time between events occurring at a load connection point of an electrical network and the time between events occurring in a distribution line of the electrical network and/or a supply point connected thereto, and subsequently comparing the times between detected events, to determine, based at least on the similarity between the compared times, to which distribution line or lines the load connection point is connected. The detected events are defined as changes in the magnitude of a passive electric current circulating through the location where detection takes place.