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In this study, a novel PV emulator and the state-of-art learning–based real-time hybrid global search adaptive perturb and observe (P&amp;amp;O) maximum power point tracking (MPPT) algorithm have been presented. The prime objective of the constructed emulator based on integration of unilluminated solar panels with an external current source to overcome the constraints such as the need for wide surrounding space, high installation cost, and lack of control over the environmental conditions. Moreover, the developed algorithm resolved the drawbacks of the conventional P&amp;amp;O MPPT method associated with the use of a constant perturbation size that leads to poor transient response, high continuous steady-state oscillation, and inefficient tracking performance of maximum power point voltage in the presence of partial shading. The intended algorithm has been verified using MATLAB/Simulink by applying comparative analysis with the conventional P&amp;amp;O MPPT. In addition, the performance of the proposed control scheme is validated experimentally with the implementation of MATLAB/Simulink/Stateflow a on dSPACE Real-Time-Interface (RTI) 1007 processor board and DS2004 A/D and CP4002 Digital I/O boards. The results indicate that the algorithm is effective in reducing power losses and faster in tracking the speed of the maximum power point with less oscillation. In addition, excellent dynamic characteristics of the proposed emulator have been proven to be an ideal tool for testing PV inverters and various maximum power point tracking (MPPT) algorithms for commercial applications and university studies.

frontiers in energy research

External Current Source–Based Unilluminated PV Partial Shading Emulation System Verified Through the Hybrid Global Search Adaptive Perturb and Observe MPPT Algorithm