Stability and Analysis of Power Quality Issues in a Photovoltaic-Based Micro Grid Using an Improved Optimized Extreme Learning Machine

The renewable source integration in utility Grid through Micro Grids (MGs) have gained popularity in power system. In present situation the photo voltaic cell (PV), wind turbine generators and fuel cell are the is one of the major renewable sources (RES) used as generating sources in Micro Grid. In this study, maximum power point tracking error, stability and power quality issues have been improved in a PV based MG. A new Extreme Learning Machine (ELM) technique known as Ridge Extreme Learning Machine (RELM) has been investigated in order to reduce the MPPT error and to improve the dynamic oscillations. Further to achieve a robust error reduction, improved dynamics, a modified water cycle base Ridge Extreme Learning Machine (WC-RELM) is investigated using MATLAB/SIMULINK software, in this work. Finally, one of the case studies is validated in HIL, real time simulation