Enhancing performance of interleaved KY converter control in single phase grid-tied PV systems: A hybrid approach

Abstract

This paper proposes a hybrid COA-QNN approach for an interleaved KY converter with closed-loop control for a single-phase grid-connected photovoltaic (PV) system. The proposed strategy combines both Cheetah Optimizer algorithm (COA) and Quantum Neural Network (QNN), and it is commonly named the COA-QNN technique. The interleaved KY converter is connected in the converter side. The primary goal of the COA-QNN technique is to enhance PQ while maximizing PV electricity being transferred to the grid. The proposed COA is utilized to identify the optimal closed-loop controller enhancements for on-grid solar photovoltaic systems. The QNN is used to predict the optimal control parameter. The PV-interleaved KY converter is managed by a predictive control mechanism to carry out both tasks of PQ enhancement. By then the COA-QNN technique is implemented on the MATLAB platform and compared with existing methods. Finally, the proposed method shows better results in all methods, such as GWO, FF optimization and combined GWO-FF.