A Novel Data-Driven Online Model Estimation Method for Renewable Energy Integrated Power Systems With Random Time Delay
Zhenjie Cui, Weihao Hu, Guozhou Zhang, Qi Huang, Zhe Chen, Frede Blaabjerg
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.
Topics & Concepts
PhasorElectric power systemComputer scienceRenewable energyEstimationControl theory (sociology)Phasor measurement unitEnergy (signal processing)Power (physics)EngineeringMathematicsStatisticsControl (management)Electrical engineeringPhysicsSystems engineeringQuantum mechanicsArtificial intelligencePower System Optimization and StabilityFrequency Control in Power SystemsMicrogrid Control and Optimization