Hybrid Power Management Using Interleaved Landsman Converter Implemented Through Machine Learning

The advancement in developed technologies demands energy supply sector to be developed with time. The implementation of micro grid provides decentralized energy supply. The industries need not depend on the grid for continuous power supply. They install their own renewable energy sources. This paper is proposed to regulate the energy needs of these industries. When the energy supplied by the renewable sources installed by the industry is not Sufficient the then required electric supply is taken from the grid provided supply by the renewable resources like the solar panel and wind generator. The energy compensation is taken care of the converter designed according to the industrial need. This paper has proposed interleaved landsman converter for this purpose. This converter helps to maintain the voltage, thus helps in maintaining the load efficiency. The renewable resource implemented by the industry is taken as solar panels. The converter is controlled by the microcontroller named NodeMCU which is trained by the algorithm called KNN(K nearest Neighbor). The microcontroller is trained using machine learning. The Photovoltaic cell is monitored by the MPPT(Maximum Power Point Tracking) algorithm. This circuit is implemented using MATLAB/ Simulink and the results are also attached.