AISMC for Islanded Operation of Wind Driven SEIG Based DC Nanogrid

Abstract

In this paper, the current mode control strategy for a cuk converter assisted self-excited induction generator (SEIG) based wind energy conversion system (WECS) for DC nanogrid is proposed. Voltage regulation is a challenging task when SEIG is used in variable speed operation. Further, the nonlinear dynamics of cuk converter, uncertain network parameter and variable supply and demand make the voltage regulation more challenging. Sliding mode controller (SMC) which is a nonlinear controller is preferred for DC nanogrid application because of good static and dynamic response for input output disturbance rejection capability. Conventionally, design of voltage loop in SMC does not consider the uncertainty of the control parameter. However, the accuracy of the control signal generated by the SMC also depends on how accurately the reference current is generated. Therefore, genetic algorithm (GA) tuned PI controller is proposed to generate the ripple free reference current, which follows the load side and source side variations. Further, a control algorithm is integrated with SMC which calculates the design parameters for fixed frequency control resulting suppressed chattering in amplitude. Consequently, the performance of overall controller is enhanced which is compared with conventional two loop SMC. The dynamic performance of the controller is compared in terms of the tracking error, control effort and sliding surface error. Artificial intelligence assisted SMC (AISMC) is proposed because of its advantages over SMC controller like improved dynamic response and easy implementation. Extensive simulation study is carried in Matlab\\simulink for comparative analysis of conventional SMC and AISMC.