A Novel Data-Driven Online Model Estimation Method for Renewable Energy Integrated Power Systems With Random Time Delay

Abstract

This letter presents a novel data-driven model estimation method for renewable energy source (RES) integrated system with random time delay. The proposed method exploits the theoretical properties of stochastic systems to achieve real-time estimation of the state matrix and the input matrix of a closed-loop system, and does not require any system model information. Experimental results demonstrate that compared with other phasor measurement units (PMU)-based estimation methods, the proposed method is more suitable for estimating random time delayed system and has better estimation performance.