Nonlinear Grid Voltage Sensing for Fast Distortion Tracking
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Solution Overview
Problem
Existing power grid information sensing technologies face challenges with poor robustness, real-time calculation capabilities, low estimation accuracy, and slow tracking speeds, particularly in new-energy power generation systems where power grid voltage waveforms are distorted, making it difficult to ensure stable and accurate sensing of amplitude, frequency, and phase.
Innovation Solution
A method based on nonlinear robust estimation is proposed, which involves acquiring a phase voltage signal, establishing a nonlinear state-space model, converting the H∞ smoothing estimation problem into a generalized H2 problem, and constructing an H∞ smoothing estimator to sense power grid information accurately and quickly, using space mapping technology and output reconstruction for robust and fast parameter calculation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional linear filtering sensing method is used, then filtering effect is achieved, but deviation is great and response speed is slow
Solution Approach 1:
The patent transforms the sensing problem from linear filtering parameter optimization to nonlinear state estimation by changing the mathematical model parameters. It uses Lipschitz continuous nonlinear functions to describe the power grid voltage characteristics, allowing the system to adapt to distorted waveforms while maintaining both accuracy and fast response through recursive estimation algorithms.
Solution Approach 2:
The patent replaces traditional mechanical filtering approaches (hardware circuits, moving average filters) with a mathematical substitution approach using nonlinear state-space modeling and H∞ filtering. This substitution enables the system to achieve filtering and estimation functions through computational methods rather than physical filtering components, improving both speed and accuracy.
2Measurement precision
If window length of filter is increased to improve filtering effect, then filtering effect is improved, but dynamic response becomes slower
Solution Approach 1:
The patent implements a dynamic estimation approach where the state estimator recursively updates power grid information in real-time based on current measurements and system model. Unlike fixed window-length filters, this dynamic approach adapts to changing grid conditions instantaneously, achieving both good filtering effect and fast dynamic response through time-varying state estimation.
3Measurement precision
If feedback-principle-based phase-locked loop method is used, then sensing control is achieved, but conflict between sensing accuracy and high speed cannot be reconciled
Solution Approach 1:
The patent introduces an H∞ state estimator as an intermediary between the power grid voltage measurements and the control system. This estimator acts as a sophisticated mediator that processes measurements through a nonlinear state-space model, providing both accurate and fast tracking of power grid information without the oscillatory behavior and accuracy-speed conflict inherent in traditional phase-locked loop feedback mechanisms.
4Reliability
If existing sensing methods are used in distorted power grid, then basic sensing is achieved, but robustness is poor and estimation accuracy is low
Solution Approach 1:
The patent performs preliminary action by establishing a nonlinear state-space model of the power grid system before actual sensing occurs. This pre-established model, which incorporates Lipschitz continuous nonlinear functions to represent distorted voltage characteristics, provides a robust framework that maintains high estimation accuracy even when grid conditions deviate from ideal sinusoidal waveforms, unlike methods that assume perfect grid conditions.
Data Source
AI summary
A method for sensing power grid information based on nonlinear robust estimation, including: acquiring an actual power grid phase voltage signal; obtaining a nonlinear state-space distorted power grid model based on the actual power grid phase voltage signal and a phase voltage signal virtual orthogonal signal; establishing an H∞ smoothing estimation performance indicator based on the nonlinear state-space distorted power grid model, converting an H∞ smoothing estimation problem into a generalized H2 smoothing estimation problem according to the H∞ smoothing estimation performance indicator, and constructing an H∞ smoothing estimator; and obtaining an initial sensed amplitude value and an initial sensed phase value of a power grid voltage signal by using the H∞ smoothing estimator, and performing zero-crossing point detection on the initial sensed amplitude value and the initial sensed phase value of the power grid voltage signal to obtain sensed amplitude, frequency and phase values of a distorted voltage.