Intelligent Control Approach Applied for Grid-Forming Power Converters

This paper proposes an intelligent nested-loop control scheme based on brain emotional learning for voltage control of a grid-forming (GFM) power inverter. The proposed controller offers features such as coping with modeling uncertainties and disturbances impacting the system model. The proposed approach is quite model-free, implying that the inverter is controlled without prior knowledge of the GFM model and parameters. Unlike the conventional nested-loop control methods typically designed for a specified operating condition, the proposed approach avoids the dependency of the control system on the operating conditions, which provides the benefits of lower total harmonic distortion and robustness against parameter changes and disturbances. Experimental results obtained from a GFM inverter laboratory setup establish the effectiveness of the proposed method.