Fast Transient Hybrid Neuro Fuzzy Controller for STATCOM During Unbalanced Voltage Sags

Abstract

A static synchronous compensator (STATCOM) is generally used to regulate voltage and improve transient stability in transmission and distribution networks. This is achieved by controlling reactive power exchange between STATCOM and the grid. Unbalanced sags are the most common type of voltage sags in distribution networks. A static synchronous compensator (STATCOM) is generally used to maintain voltage and improve transient stability. This is achieved by regulating reactive power exchange between compensator device and grid. In this paper, A hybrid neuro-fuzzy current controller for STATCOM control is proposed. The controller has minimum mass of calculations. Learning process is carried out by an improved supervisory error-back propagation (SEBP) method instead of usual EBP algorithm. This results in better performance and efficiency and leads to a robust model with fast transient capability. The model is developed in MATLAB/SIMULINK environment. STATCOM operation during scenarios of balanced and unbalanced voltage sags is studied. Performance is compared with the operation of a conventional proportional-resonant controller. The results show faster dynamic and better capability of neuro-fuzzy controller in responding to voltage sag occurrences.