Feature-Reduced Stability Analysis of Islanded Photovoltaic Microgrid Inverters

Abstract

A smart grid environment is prone to data explosion while controlling a microgrid system. Islanded Microgrid’s stability analysis involves a large number of system state variables thus consuming more computational memory due to parallel connected inverter dynamics. Parallel inverters generate reference voltage and frequency using droop controllers, unlike grid-connected inverters where the primary grid provides the reference voltage and frequency. This paper develops feature-reduced stability analysis of the parallel inverters thus reducing the computational memory of its stability analysis. Principal component analysis being a feature extraction technique is applied to reduce the number of variables determining stability. MATLAB is used to develop the average model of a parallel inverter with an LCL filter and a three-phase AC load. Evaluation of the stability analysis using the state variable analysis with the virtual resistance method is simulated. Simulation validates stability analysis of the model with reduced state variables. An average model developed using MATLAB and PCA carried out using Python clearly indicated the validation of the dimensionality reduction in the stability analysis. The reduced number of variables is validated for a stable range of the parallel inverter droop controller. Both cases validated the dimensionality reduction in the stability analysis of parallel inverters.