Adaptive predictive control of flywheel storage for transient stability enhancement of a wind penetrated power system

Abstract

Flywheel energy storage system (FESS) needs to be operated within its allowable speed range because it will be shut down outside this range. Furthermore, the power supplied/absorbed by FESS is constrained by the associated power electronic interface. This article proposes supervisory adaptive predictive control (APC) scheme for flywheel energy storage system to enhance power system transient stability while addressing the constraints mentioned earlier. The supervisory adaptive predictive controller gives a reference power command signal to the inner control loop of FESS while ensuring the operation of FESS within its regime of operation. The gains of the inner control loop are optimized by employing Genetic Algorithm (GA). The constraints on the state of charge of FESS and power rating of the associated converter are explicitly included in the adaptive predictive controller formulation, which is usually done in an ad hoc manner. The performance of the proposed control strategy is evaluated under four scenarios: a step wind disturbance, realistic wind profile, doubly fed induction generator (DFIG) outage, and a severe symmetrical fault condition on modified New York/New England 16 machine 68-bus power system. The validity of the adaptive predictive control based flywheel energy storage system (APC based FESS) in improving transient stability of power system is verified by the simulation studies carried out in MATLAB/Simulink environment.