Order Reduction of Autonomous Microgrids using Pade and Routh Approximation

Model order reduction (MOR) is an analytical or numerical methodology of reduced dimension. A specific computational process to create a low-order approximation that preserves the unique property of the high-order model and retains the basic characteristics of the model. The primary benefits of MOR include enhanced understanding and modeling of complex subsystems with dominant accuracy, acceleration of the design cycle, improved system efficiency, and reduced computational demands. This paper presents a methodology for reducing the model order of autonomous microgrids using both the Routh-approximation method (RAM) and the Markov Parameters (MaPs) & Time Moments (TiMs) method. This novel approach simplifies the power system model while ensuring stability and accuracy. Specifically, the methodology involves numerator reduction using MaPs & TiMs and denominator reduction via the Routh Approximation Method. An eighth-order microgrid model is reduced to second and third-order models. Theoretical analysis and numerical simulations demonstrate that these reduced models adequately capture the key features of the full system, making them suitable for control and stability studies. Different responses, including step response, impulse response, phase response, and Nyquist response, are provided for the proposed autonomous MG. The chief strength of the mixed-methods approach is that it always brings out a simple and stable structural lower order to preserve the critical features of this type of virtual space organization system. The accuracy of this proposed work is highly effective and significant in the following aspects.