Journal of System Simulation ›› 2015, Vol. 27 ›› Issue (3): 609-619.

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Simulation Study of Multiple Model Decentralized-coordinated Predictive Control for Hybrid Wind-thermal Power System

Niu Yuguang1, Li Xiaoming2, Wang Shilin2, Lin Zhongwei1,2   

  1. 1. State Key Laboratory for Alternate Electric Power System with Renewable Energy SourceNorth China Electric Power University, Beijing 102206, China;
    2. School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China;
  • Received:2014-03-12 Revised:2014-07-17 Online:2015-03-08 Published:2020-08-20

Abstract: The large-scale integration of wind power presents a higher requirement of power system operation and control. A multiple model predictive control based decentralized coordinated control, which combined the characteristics of multiple model predictive control (MPC) and interaction measurement modeling, was proposed and applied to the simulation study of a hybrid wind-thermal power system. In order to enhance the resistance against the stochastic disturbance from wind turbine, an augment correlative measured method was employed to hybrid power system modeling. The Bayesian probability based iteration method was employed to calculate the model weighting. A simple, generic hybrid power system model was used to demonstrate system performance contributions. Simulations of time response and dominated eigenvalue analysis illustrate the effectiveness of the proposed method.

Key words: hybrid wind-thermal power system, multiple model predictive control, decentralized coordinated control, transient stability, system damping

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