Power System Inertia Estimation Using Fault-Time Sliding Windows
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Solution Overview
Problem
Existing methods for calculating power system inertia fail to accurately account for non-regulated generator units, loads, and new forms of inertia, leading to underestimated values and instability during power system operations.
Innovation Solution
A method and system using a sliding window approach to calculate system inertia by filtering data from PMU devices, employing empirical mode decomposition and moving average algorithms to determine fault occurrence, and calculating inertia based on frequency change rates and oscillation centers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If SCADA system is used to calculate inertia by counting rotational inertia of grid-connected synchronous generator units, then the calculation method is simple, but the monitoring range cannot cover non-regulated generator units, loads and other potentially new forms of inertia, leading to underestimated inertia values and low accuracy
Solution Approach 1:
The patent replaces the traditional mechanical counting method of synchronous generator units with a signal processing-based approach using PMU frequency data. By substituting direct mechanical inertia measurement with frequency transient analysis, the system can capture all forms of inertia including non-regulated generators, loads, and distributed energy resources, thereby improving measurement accuracy while maintaining computational feasibility
Solution Approach 2:
The patent introduces frequency change rate as an intermediary parameter to indirectly measure system inertia. Instead of directly measuring inertia, the system uses PMU frequency data and calculates the frequency change rate, which serves as a mediator to reflect the total inertia of all system components including traditional and non-traditional sources
2Adaptability or versatility
If wide-area measurement power system is used to assess power system inertia based on power, frequencies and other data measured after large disturbance, then the assessment can be applied to post-accident offline analysis or online analysis, but challenges arise in acquiring accurate data such as disturbance moment, disturbance quantity and power system frequency change rate, and filtering the data
Solution Approach 1:
The patent performs preliminary filtering and processing of PMU frequency data before the actual inertia calculation. By pre-processing the data to remove noise and identify the disturbance moment in advance, the system simplifies the subsequent inertia assessment process and ensures accurate data quality for both offline and online analysis applications
Solution Approach 2:
The patent enables the system to automatically identify disturbance events and filter relevant data without requiring manual intervention. The system uses the frequency data itself to detect disturbance moments and automatically selects the appropriate data segments for inertia calculation, making the process self-sufficient for both offline and online applications
3Ease of operation
If online assessment of power system inertia is based on data of minor disturbance events such as load changes and generator unit power output adjustments, then the method can be applied online, but such events are relatively rare and usually cause significant frequency disturbances, making verification difficult and the method still in the exploratory stage
Solution Approach 1:
The patent creates a multi-functional inertia assessment system that can handle multiple types of disturbance events including load changes, generator trips, and other significant disturbances. The unified approach based on PMU frequency data and frequency change rate calculation makes the method universally applicable to various disturbance scenarios, enabling reliable verification across different event types
Data Source
AI summary
Disclosed are a method and system for calculating system inertia based on a sliding window at a moment of fault occurrence. The method includes: acquiring a frequency of each bus of a power system, active data of tie lines, and an active power output of a generator unit, and calculating a capacity of the power system; filtering the frequency of each bus, a bus voltage and the active power output of the generator unit; calculating a frequency change rate of the power system at each node, and determining a moment of fault occurrence; calculating a voltage fluctuation index of each bus; calculating a frequency change rate of each window; calculating an inertia change curve of the power system; and obtaining inertia of the power system according to the inertia change curve of the power system.