Dynamic performance improvement of isolated power system using intelligently controlled SMES

Isolated power system comprising of wind, diesel and energy storage presents an effective economical approach for supplying power. Advanced and intelligent control techniques are required to improve the power dispatch between storage devices and wind-diesel system especially during disturbances. This paper focuses on development of one step ahead adaptively controlled superconducting magnetic energy storage (SMES) for smoothing the power fluctuations of a standalone wind-diesel power system. Two sets of gate turn off (GTO) converters are utilized for obtaining a four quadrant operation of SMES system. System is represented by a third order autoregressive discrete time model. For estimating the system parameters online, recursive least square algorithm is used. System is considered as a two input two output system, where real and reactive powers demanded by SMES are the control signals issued by the controller. To restrict the energy trade within limits, constraints are imposed on the SMES current. Discrete time model of SMES is used for converting SMES current constraints into the energy level predictions and a separate model is then used for imposing the constraints. Scheme is tested for two disturbances and in both the cases, SMES current constraints are never violated while reducing the frequency and voltage deviations significantly.