Multiple Renewable Sources Integrated Micro Grid with ANFIS Based Charge and Discharge Control of Battery for Optimal Power Sharing

Abstract

In this paper an Fuzzy Inference System based battery pack charge and discharge control is achieved in renewable micro grid application. The charge and discharge of the battery pack is determined by the load demand, State of charge of the battery and available power from the micro grid sources. The micro grid comprises of solar plant, fuel cell, wind farm, biomass plant, diesel generator and Battery Energy Storage System. The proposed control module has the capability to avoid overcharge and overdischarge as per the powers from the sources. The Fuzzy Inference System is later updated with Adaptive Neuro Fuzzy Inference System module for better estimation of the battery current improving the micro grid performance. Adaptive Neuro Fuzzy Inference System is less complex module which has simple linear rule base trained by optimization technique controlling the battery current. The micro grid is operated in different operating conditions with change in power generation and load demand. The modeling is designed in MATLAB Simulink environment with graphs generated taking time as reference. A comparative analysis is carried out with FIS and ANFIS modules in the test system with comparative graphs.