Black Box-Based Incremental Reduced-Order Modeling Framework of
Inverter-Based Power Systems
Abstract
Due to the capability to perform participation factor analysis and
oscillation origin location, the state-space model (SSM)-based
eigenvalue method has been widely used for stability assessment of
inverter-penetrated power systems. However, possible internal
confidentiality of inverters impedes the derivation of their SSMs. In
addition, conventional derivation procedure of system SSM can be tedious
when complicated transmission network topology and various transmission
cables are involved, which may result in a high-order system SSM. To
this end, this article presents a black box-based incremental
reduced-order modeling framework. The reduced-order SSMs of the
inverters and transmission cables are extracted from their dq-domain
admittance frequency responses and abc-domain impedance frequency
responses, respectively, by the matrix fitting algorithm. Then, the SSM
operators proposed in this article recursively assemble the fitted
components’ SSMs in the similar manner as the impedance model
operator-based recursive components’ impedance aggregation, while
preserving the dynamics of individual components. Simulation results
show that the presented state-space modeling framework can properly
identify the state-space models of black-box devices at component
modeling stage, simplify assembling procedure at subsystems/components
integration stage, and release computational burden at system
participation factor analysis stage.