Development of Stand-Alone Photovoltaic System Test-Bed using Neural Network based Solar PV Array Emulator

Research on solar power generation is gaining momentum in recent decade, which requires a costly and complex experimental setup. The Photo-Voltaic (PV) source emulator is a low cost and necessary equipment to evaluate the solar PV array performance, Maximum Power Point Tracking (MPPT) algorithm, power converters, and corresponding control algorithm. This paper proposes a novel Neural Network (NN)-based Solar Array Emulator (SAE) to emulate PV array dynamic characteristics under varying environmental conditions. The proposed SAE reference model has been developed using NN, which can replicate a PV array characteristics with a programmable DC power source’s support. A 640 W stand-alone PV system has been designed and tested using the proposed SAE to validate the performance of the developed prototype under various environmental conditions. The results demonstrate that the developed SAE has good accuracy in replicating the PV array characteristics than the conventional diodebased SAE. DOI: 10.61416/ceai.v25i3.8106