Publication

Abstract : The DC microgrid is comprised of a considerable number of electronically regulated power electronic loads that act as constant power loads (CPLs). These power electronic devices have a high bandwidth regulation capability as well as a high-power conversion efficiency. Specifically, the high bandwidth control for the output of the converter load, when paired with the system’s filtering components, results in negatively damped oscillations. These features, even if needed, may cause system instability and, finally, system failure if not avoided. To achieve effective power flow control in a DC microgrid, it is crucial to eliminate the undesired behaviour of the CPLs. The control objective requires the assessment of the power for uncertain loads, which vary with time. This paper proposes an adaptive controller linked to a cubature Kalman filter(CKF) for a DC microgrid with time-varying non-ideal CPLs. The controller utilises the neuro-fuzzy inference system(ANFIS) to make the design adaptive. The CKF method is used to determine the instantaneous value of time-varying load power. The assessed power is afterward sent to an ANFIS-based controller, which aims to modify the energy storage systems (ESS) injected current adaptively. The suggested controller not only maintains overall stability when the CPLs vary significantly, but it has a rapid dynamic response and accurate tracking across a wide operating range as well. The simulation results demonstrate that the proposed adaptive controller can improve the DC microgrid’s transient response while also increasing the stability margin.