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AUSTRALIAN PATENT | Event Date: Wednesday, 11th, November 2020

AUSTRALIAN PATENT ON “MAXIMUM POWER POINT TRACKABLE AND OPTIMIZED IOT BASED PV CHARGE CONTROLLER USING MACHINE LEARNING”

An Innovation Patent on “Maximum Power Point Trackable and Optimized IOT Based PV Charge Controller Using Machine Learning” was certified by the Australian Government. The Patentees include Mr. K. Sakthidasan Sankaran, Assoc. Prof. ECE; Dr. N. Vasudevan, Prof., ECE & Dean E & T; Mr. S. Sasikumar, Prof. ECE; Ms. S. Prabha Assoc. ECE; Mr. Himanshu Shekhar, Prof. ECE; Mr. P. Elangovan Assoc. Prof., EEE; Mr. P. Thirumaraiselvan, Asst. Prof. ECE.

The invention relates to improving the power point tracker and optimizes the internet of things based photovoltaic (PV) charge controller using the machine learning technique. As an approach, the four-sun technology based solar PV panel was taken and it was led to the Maximum Power Point Tracking (MPPT) system which includes the DC-DC (Direct Current) boost converter and Support Vector Machine (SVM) to predict the output voltage. It then uses the Proportional Integral Derivative (PID) for maintaining a stable output voltage. To convert and further to check the stability of the voltage it is fed through the micro inverter which will invert the DC to AC (Alternative Current) voltage and produces a text using the Arduino micro controller within a range of 0 to 1023. Battery is also used as an alternative measure for making the inversion. As a result, the maximum power is tracked and the PV charge is controlled using a machine learning technique yielding high efficiency of voltage.