Low Frequency Oscillation Analysis System
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Solution Overview
Problem
Current methods for analyzing low frequency oscillations in power grids are limited by offline calculations and lack of real-time, accurate identification, especially in large interconnected systems, where eigenvalue analysis is not sufficient for online stability assessment and cannot determine the specific generators causing oscillations.
Innovation Solution
A system combining Wide Area Measurement Systems (WAMS) for real-time monitoring and dynamic early-warning systems to perform stability calculations with small disturbance, enabling online identification of damping ratios and oscillation frequencies, and providing detailed analytical information to locate and control low frequency oscillations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If offline eigenvalue analysis is used, then calculation cost is reduced, but real-time accuracy of oscillation identification is insufficient
Solution Approach 1:
The system pre-calculates and stores the relationship between eigenvalues, oscillation frequencies, and generator participation factors during system initialization or off-line periods. When real-time monitoring is needed, the pre-computed models are directly applied to measured data, avoiding time-consuming eigenvalue calculations while maintaining accuracy.
Solution Approach 2:
The patent replaces the traditional mechanical eigenvalue analysis computation with a simplified mathematical model that uses pre-computed transfer functions and measured frequency data. This substitution allows real-time calculation without the computational burden of full eigenvalue analysis.
2Loss of information
If WAMS monitoring is implemented, then real-time dynamic data is obtained, but specific oscillation sources cannot be identified
Solution Approach 1:
The patent introduces an intermediary analysis layer that processes WAMS data through pre-computed eigenvalue-eigenvector relationships. This intermediary model translates raw measurement data into meaningful oscillation source identification without requiring direct modification of the WAMS hardware or installation of additional sensors.
Solution Approach 2:
The system creates a simplified computational model that copies the essential dynamic characteristics of the power system. This model replicates the oscillation behavior and generator participation patterns, allowing identification of oscillation sources through model-based analysis rather than direct measurement.
3Measurement precision
If PMUs are installed at all nodes, then complete oscillation information is obtained, but system cost increases significantly
Solution Approach 1:
The patent applies partial action by using measurements from a limited subset of strategically placed PMUs rather than installing them at all nodes. The analysis method compensates for the incomplete measurement set by using system models and mathematical relationships to infer oscillation characteristics that would require full system coverage.
Data Source
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AI summary
A method and a system for a comprehensive analysis of low frequency oscillation. The method includes: firstly, initiating a wide area measurement system WAMS (71) to perform real-time monitoring; transmitting real-time low frequency oscillation information to a dynamic early-warning system (72) periodically; then converting the low frequency oscillation information received by the dynamic early-warning system (72) into an input file for stability calculation with small disturbance, and performing related calculation; finally, transmitting the calculated result back to the wide area measurement system WAMS (71) and a human-machine system interface for output. The system includes: the wide area measurement system WAMS (71), the dynamic early-warning system (72), a system for stability calculation with small disturbance (73) and an output system (74).