Estimation and controlling the state of charge in battery augmented photovoltaic system

Abstract

Today solar technology is proving reliable and increasingly affordable. It is good to environment and a secure energy supply. The overall carbon footprint for generating solar electricity is 30 times less than using coal. The main drawback in PV system is the fluctuation in solar energy supply. In this work Kalman filter is used to estimate the State of Charge in battery storage system, and hence it is possible to know about the duration for which the demand can be met. The SOC estimation technique using Kalman filter which is an accurate adaptive method and by using three switches the charge of battery is maintained within the safe limit (20%-80%) so that overcharging and over discharging can be eliminated and hence the battery life and performance can also be improved. The efficacy of the proposed method is verified by a set of simulation using MATLAB simulink.