A model predictive control based SIPS to prevent transient instability

This paper proposed a system integrity protection scheme (SIPS) that prevents the system from loss of synchronism. The control action applied is thyristor controlled series compensation (TCSC). A model predictive control approach optimizes the control action at every time step by adjusting the compensation level of the TCSC device. A supervised learning approach is used to predict the system states assuming each of the control action has been taken. Real time measurements over a wide area enable the system state to be predicted online and the coordinated control decisions taken. The location and number of PMU devices are determined by the relevance of each variable to the system dynamics. A feature selection technique is utilized to select the most relevant variable that needs to be measured for system state prediction. This could significantly reduce the number of PMU devices and relieve computation burden. This time discrete control technique can rapidly optimize the control action, which is very important during emergency conditions. Simulation studies conducted on a two machine four bus system show that the proposed SIPS can effectively maintain system synchronism in the aftermath of a large disturbance.