Improvement of Power System Stability and Performance in a Solar, Wind and fuel cell Sources based Micro Grid System using ANFIS Techniques

Authors

  • Rajesh Thangella, Srinivasa Rao Yarlagadda

Abstract

Now a day’s renewable energy sources are playing an important role in power generation. Power quality is the main problem which is caused due to nonlinear loads. In this paper AdaptiveNeuron-Fuzzy Inference System (ANFIS)-based micro grid integration for Power flowcontrol and the system stability improvement using hybrid renewable sources is proposed. Photovoltaic (PV), PMSG based wind energy generation control and fuel cell are integrated together to the grid along with their respective maximum power point tracking. All the sources are employed with dc/dc power converters in order to connect to the common dc bus. ANIFS supervisory control topology of boost converter are developed to solve various power quality and oscillations damping issues due to rapid change in heavy loads connected to the grid is considered. The proposed system simulation is carried in dynamic MATLB/Simulink demonstrates the performance of the hybrid systemshows betteroscillations damping and power flow continuity and the results are compared for uncontrolled, neural network controlled and ANFIS controlled and found that later is having better capability in all power systems terms. 

Keywords-:Power System Stability; DC- DC Boost converter; VSI Inverter; Micro-grid; PV Cell; Wind Energy Conversion System (WECS); Fuel Cell; Neural Network: ANFIS

Published

2020-11-28

Issue

Section

Articles