Cloud-Edge Harmonic Source Tracing for Distributed Power Grids
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Solution Overview
Problem
Existing methods for harmonic contribution evaluation in power distribution networks lack integration with cloud-edge-terminal collaboration technology, making it difficult to effectively trace and evaluate harmonic sources in the field.
Innovation Solution
A system and method for tracing harmonic sources based on cloud-edge-terminal collaboration, which deploys harmonic measurement terminals, edge computing servers, and cloud servers to collect, process, and trace harmonic data hierarchically, enabling location and contribution evaluation of harmonic sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional harmonic contribution evaluation methods are used, then the evaluation can be performed with simple centralized processing, but the system cannot effectively trace harmonic sources in distributed power grids and lacks real-time monitoring capability
Solution Approach 1:
The system divides the power grid into multiple hierarchical levels (cloud layer, edge layer, terminal layer) with each level performing specific functions. Terminal devices collect harmonic data locally, edge servers perform preliminary processing and filtering, and cloud centers conduct comprehensive analysis. This segmentation enables effective harmonic source tracing in distributed grids while distributing computational load to avoid excessive complexity at any single point.
Solution Approach 2:
The patent introduces a spatial dimension to harmonic evaluation by deploying measurement terminals and edge servers at multiple physical locations throughout the power grid. This multi-dimensional deployment enables localization of harmonic sources through spatial comparison of harmonic data from different nodes, transforming a traditional centralized 2D evaluation into a 3D spatial-temporal analysis system.
2Ease of operation
If all harmonic data processing and assessment calculations are performed in the cloud, then centralized control is simplified, but the workload of cloud data calling and computation becomes excessive
Solution Approach 1:
The computational workload is segmented across three hierarchical levels: terminal devices perform local data collection and preliminary filtering, edge servers conduct real-time processing and anomaly detection, and cloud centers perform comprehensive analysis and long-term storage. This segmentation reduces cloud computational burden by distributing processing tasks to edge and terminal layers.
Solution Approach 2:
Edge servers perform preliminary processing of harmonic data including filtering, validation, and preliminary analysis before data is transmitted to cloud centers. This preliminary action at the edge reduces the volume and complexity of data requiring cloud processing, significantly lowering cloud computational workload while maintaining centralized oversight.
3Measurement precision
If measurement terminals are deployed throughout the power grid, then harmonic monitoring coverage is improved, but the complexity of data collection and management increases
Solution Approach 1:
The system segments data collection and management functions across terminal devices, edge servers, and cloud centers. Each terminal collects local harmonic data and transmits it to nearby edge servers, which aggregate and pre-process data before forwarding to cloud centers. This segmentation manages complexity by distributing data handling responsibilities rather than requiring centralized collection from all terminals.
Solution Approach 2:
Edge servers act as intermediaries between terminal measurement devices and cloud data centers. They receive raw data from multiple terminals, perform local processing and filtering, validate data quality, and forward processed data to the cloud. This intermediary layer simplifies cloud data management while maintaining comprehensive monitoring coverage.
Data Source
AI summary
The invention belongs to the technical field of harmonic contribution evaluation, and particularly relates to a system for tracing harmonic sources based on a cloud-edge-terminal collaboration and a method thereof, comprising: terminal module, collecting and transmitting real-time harmonic data to edge module; edge module, comprising plurality of edge computing servers deployed for the transformer substations and the transformer districts by units, realizing hierarchical control between edge computing servers according to voltage levels, and transmitting harmonic sources tracing task through hierarchical interactions between the edge computing servers; the edge computing server receiving harmonic sources tracing service request performs the tracing task, and feeds tracing result back to central module; and, central module, comprising cloud server receiving harmonic sources tracing service request initiated by user, determining edge computing server offloaded by the request, storing final tracing result from entire the system, and matching typical harmonic source according to disturbance source information.