Maximum Power Point Tracking Algorithm for Laser Power Beaming Based on Neural Networks

With the high voltage intelligent substation developing at a pretty high speed, more and more artificial intelligent techniques have been incorporated into the power devices to meet the automation needs. For the sake of the line maintenance staff's safety, the high voltage isolating switch draws great attention among the most important power devices because of its capability of connecting and disconnecting the high voltage circuit. However, due to high-voltage isolating switch's working environment, the power supply system of the surveillance devices could suffer from great electromagnetic interference. Laser power beaming exhibits its merits in such situation because it can provide steady power from a distance despite the day or the night. Then the energy conversion efficiency arises as a new concern. To make full use of the laser power, this paper mainly focuses on extracting the maximum power from the photovoltaic (PV) panel. And a neural network based algorithm is proposed which combines both the intrinsic and the extrinsic features of the PV panel with the proportion of the voltage of the maximum power point (MPP) to the open circuit voltage of the PV panel. Simulations and experiments are carried out to verify the validness and feasibility of the algorithm.