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 components' fitted 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.