A Comparative Analysis of DC Microgrid Protection Using AI

Without being a part of a larger power grid, it can be used to independently produce, distribute, and store electricity. Here Direct current (DC) voltage levels are used to power small-scale DC Microgrid electric power systems. Power generation devices like solar cells, wind turbines, or fuel cells, energy storage devices like batteries or capacitors, power converters, and control systems are the main elements of a DC Microgrid. Due to its capacity to deliver dependable and effective electricity in off-the-grid or distant regions as well as their potential to lower energy prices and carbon emissions, DC Microgrids are growing in popularity. In this paper we are going to discuss about the designing of MATLAB/Simulink model of the DC Microgrid which is to be powered based on renewable sources of energy. The sources of energy are: - Wind Turbine, PV Arrays, Batteries and they are to be connected with the main utility grid. Various types of power electronic devices such as AC to DC converters, power MOSFET, diodes etc. Apart from the designing part of DC Microgrid we will also discuss about the di/dt and ANFIS protection schemes. The di/dt protection scheme focuses on monitoring the rate of change of current to detect abnormal current behaviour and trigger protective measures. Another protection scheme is based upon AI as it is able to figure out the abnormal conditions on its own based on the training data. The scheme is implemented with the help of ANFIS toolbox, The ANFIS protection scheme utilizes an adaptive neuro-fuzzy inference system, which learns from real-time data and provides intelligent fault detection, localization, and classification within the microgrid system. This scheme can be the future of more efficient protection of DC system if properly trained with varieties of data.