Performance Analysis of ANFIS-PSO based STATCOM in an Isolated Renewable Energy based Micro-Grid

In recent times, the micro-grids have gained more importance owing to the increased need for providing reliable and quality power to the users at remote locations. This work proposes a novel application of Adaptive Neuro-Fuzzy Inference System (ANFIS) in conjunction with Particle Swarm Optimization (PSO)-based controller for static synchronous compensator to improve the performance of a hybrid renewable energy based isolated micro grid environment. Adaptive and robust ANFIS controller combines the features of artificial neural network and fuzzy inference system. The proposed controller provides reactive power compensation and maintains the stability of the system. The functionality of the system is tested in MATLAB/Simulink under varying conditions and results show improvement in power factor and reduction in harmonics. Also, the performance of PSO-ANFIS is superior to conventional PI and ANFIS controller in terms error components.