Grid-Forming Inverter Overload Ride-Through for Disturbance Stability
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Solution Overview
Problem
Conventional grid-forming inverter-based resources face challenges in transient power-limiting during disturbances, leading to potential cascading instability and loss of synchronism due to unclear activation of virtual impedance and inadequate power reserve management.
Innovation Solution
A system-level overload ride-through control strategy employing online system-level analysis and control actions, including the preemptive transmission of modified parameter sets to inverter-based resources for rapid re-parameterization during severe grid events, ensuring self-protection, stability, and optimality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional grid-forming inverter-based resources use traditional control strategies during disturbances, then the system structure remains simple and easy to operate, but the system experiences cascading instability and loss of synchronism due to inadequate transient power-limiting capability
Solution Approach 1:
The system performs preliminary system-level analysis before disturbances occur to determine optimal modified parameter sets for virtual impedance and power reserve. These pre-calculated parameters are stored and ready for rapid deployment when disturbances occur, enabling proactive preparation rather than reactive adjustment during critical events
Solution Approach 2:
The patent introduces a system-level analysis module as an intermediary that bridges the gap between simple local controller and complex system behavior. This module calculates optimal parameter sets that account for network topology and system state, providing guidance to individual inverter-based resources without requiring them to directly communicate with each other
2Power
If virtual impedance is activated during disturbances, then transient power can be limited to prevent overload, but the activation timing and parameter selection are unclear leading to potential instability
Solution Approach 1:
The system continuously monitors grid conditions and feeds this information back to the system-level analysis module, which adjusts the modified parameter sets accordingly. This feedback mechanism ensures that virtual impedance activation and parameter selection are based on actual system state rather than fixed predetermined values, resolving the uncertainty in when and how to activate protection
Solution Approach 2:
The patent dynamically changes control parameters (virtual impedance values, power reserve levels) based on system conditions and disturbance severity. The system-level analysis module calculates optimal parameter values that adapt to the current operating state, providing clear guidance for activation timing and parameter selection rather than using fixed thresholds
3Productivity
If inverter-based resources maintain high power output during disturbances, then energy transfer efficiency is maximized, but the resources may trip due to overload conditions causing loss of synchronism
Solution Approach 1:
The system applies partial power limitation through modified parameter sets that reduce power output only to the extent necessary to prevent tripping. Rather than completely limiting power during disturbances, the system-level analysis determines the optimal reduction level that maintains continuous operation while preventing overload, allowing maximum power transfer within safe limits
Solution Approach 2:
The system establishes power reserves and adjusts operating points before disturbances occur to create a cushion against potential overloads. The system-level analysis module calculates appropriate power reserve levels that provide protection during disturbances while minimizing impact on normal power transfer efficiency
Data Source
AI summary
A method for controlling a network of inverter-based resources (IBRs) during a disturbance includes, in response to a start of the disturbance, employing a system-level overload ride-through (SLORT) algorithm among the network of IBRs. The SLORT algorithm includes determining, via a SLORT control module, a modified parameter set for one or more of the IBRs using regularly-updated system-level analyses, transmitting, via the SLORT control module, the modified parameter set to the IBRs, and automatically activating, via one or more local controllers of the IBRs, the modified parameter set, wherein automatically activating the modified parameter set comprises rapidly re-parameterizing one or more parameters of the one or more of the IBRs for a duration of and for a time period after the disturbance so as to transition the network of IBRs from a pre-disturbance stable state to a post-disturbance stable state.


