Cloud-Edge Pseudo-Leakage Compensation for Zero Sequence Transformers
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Solution Overview
Problem
The existing zero sequence current transformers used for measuring leakage current in electrical circuits suffer from measurement errors due to magnetic leakage and uneven winding, leading to a 'pseudo-leakage' phenomenon that significantly overestimates the actual leakage current.
Innovation Solution
A leakage measurement error compensation method and system based on cloud-edge collaborative computing, which involves monitoring load voltage, load current, and leakage current data at the edge terminal, uploading this data to a cloud platform for iterative training of a pseudo-leakage compensation model, and then feeding back the model parameters to the edge terminal for data processing to eliminate pseudo-leakage errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If zero sequence current transformer is used to measure leakage current, then leakage current can be monitored, but measurement errors occur due to magnetic leakage and uneven winding causing pseudo-leakage phenomenon
Solution Approach 1:
The patent establishes a feedback mechanism where the edge terminal sends measured leakage current data to the cloud platform, which processes the data and returns compensation parameters to the edge terminal. This closed-loop feedback system continuously optimizes the measurement accuracy by compensating for pseudo-leakage errors based on historical data and environmental factors.
Solution Approach 2:
The patent introduces a cloud platform as an intermediary between the edge terminal and the compensation process. The cloud platform receives raw measurement data, performs complex data processing and analysis, generates compensation parameters, and returns them to the edge terminal. This intermediary handles the computationally intensive tasks that would burden the edge terminal.
2Measurement precision
If cloud platform processes all data for pseudo-leakage compensation, then accurate compensation parameters can be obtained, but communication bandwidth and platform burden increase
Solution Approach 1:
The patent segments the data processing tasks between edge terminal and cloud platform. The edge terminal performs preliminary data collection and local processing, while the cloud platform handles complex analysis and parameter generation. This segmentation reduces the amount of data that needs to be transmitted over the network, conserving bandwidth and reducing platform burden.
Solution Approach 2:
The patent implements a dynamic compensation mechanism where the edge terminal can perform real-time compensation using locally stored compensation parameters for urgent situations. The terminal dynamically switches between using pre-generated compensation parameters and requesting updated parameters from the cloud platform based on the urgency and nature of the measurement needs.
3Speed
If edge terminal performs real-time compensation calculation, then response speed increases, but terminal computing power is insufficient
Solution Approach 1:
The patent applies preliminary action by having the cloud platform pre-calculate and generate compensation parameters based on historical data and environmental factors before they are needed at the edge terminal. These pre-generated parameters are stored locally at the edge terminal, enabling fast real-time compensation without requiring complex calculations at the terminal during critical measurements.
Data Source
AI summary
A leakage measurement error compensation method based on cloud-edge collaborative computing is implemented on a communication network formed by an interconnection between a leakage current edge monitoring terminal and a power consumption management cloud platform. The method includes the following steps: iteratively training, by the power consumption management cloud platform, a pseudo-leakage compensation model by using the received leakage current data, continuously updating pseudo-leakage model parameters, and feeding the pseudo-leakage model parameters back to the leakage current edge monitoring terminal; and processing, by the leakage current edge monitoring terminal, the leakage current data according to the pseudo-leakage compensation model parameters.