Participation Factor-Based Adaptive Model Reduction for Fast Power System Simulation

TL;DR

This paper introduces an adaptive model reduction technique for power system simulations that uses participation factors to identify and reduce less influential system components, improving simulation speed without sacrificing accuracy.

Contribution

It proposes a novel participation factor-based method for selectively reducing nonlinear power system models, enhancing simulation efficiency and accuracy.

Findings

Effective reduction of power system models without loss of accuracy.

Improved simulation speed demonstrated on a 48-machine system.

Participation factors effectively identify critical system components.

Abstract

This paper describes an adaptive method to reduce a nonlinear power system model for fast and accurate transient stability simulation. It presents an approach to analyze and rank participation factors of each system state variable into dominant system modes excited by a disturbance so as to determine which regions or generators can be reduced without impacting the accuracy of simulation for a study area. In this approach, the generator models located in an external area with large participation factors are nonlinearly reduced and the rest of the generators will be linearized. The simulation results confirm that the assessment of the level of interaction between generators and system modes by participation factors is effective in enhancing the accuracy and speed of power system models. The proposed method is applied to the Northeastern Power Coordinating Council region system with 48-machine, 140-bus power system model and the results are compared with two cases including fully linearized model reduction and model reduction using the rotor angle deviation criteria.