Improved control strategy for Cuk converter assisted wind‐driven SEIG for DC nanogrid

Abstract

In this study, the current mode control strategy for a Cuk converter assisted self-excited induction generator-based wind energy conversion system (WECS) for DC nanogrid is proposed. The sliding mode controller (SMC) is a non-linear controller and, is preferred because of good static and dynamic response for input -output disturbance rejections. However, the knowledge of all the state variables is required, which increases the number of sensors and control complexity. To reduce the number of sensors, reduced-order SMC (ROSMC) can be implemented. Conventionally design of the voltage loop in ROSMC does not consider the uncertainty of the control parameter. However, the accuracy of the control signal generated by the ROSMC also depends on how accurately the reference current is generated. Therefore, a genetic algorithm tuned PI controller is proposed to generate the ripple-free reference current. Artificial intelligence assisted ROSMC (AIROSMC) is proposed because of its advantages over SMC, which are a reduced number of sensors, improved dynamic response and easy implementation. The extensive simulation study is carried in MATLAB\Simulink for comparative analysis of fixed frequency SMC, two variable SMC, ROSMC, and AIROSMC. The harmonic spectrum analysis is carried out to justify the selection of DBR instead of the controlled rectifier.