Efficient charging/discharging algorithm for battery storage system

Abstract

Batteries typically have a fixed amount of charge and discharge cycle before they come to the end of their useful lifespan. In order to maintain and maximize a battery’s lifespan, the battery has to go through a planned sequence of charging and discharging cycle to avoid overcharge or deep discharge. An important parameter that must be estimated is the state of charge (SOC), as there is no direct measurement available, it is very important to carry out an accurate method in estimating the SOC level of the battery. Failure to estimate the SOC precisely may affect the performance and the lifetime of the battery. This report discusses various techniques to estimate the SOC of the battery such as open-circuit voltage (OCV) method, coulomb counting method and extended Kalman filter (EKF) algorithm. Next, an efficient charging or discharging algorithm is designed by using LabVIEW software to maintain the desired SOC level automatically. This algorithm uses the state machine design pattern which is able to execute a network of decision-making algorithm. Then, a battery management system (BMS) is able to decide when to charge or discharge the battery energy storage system (BESS) based on the SOC level and power demand by the microgrid. Lastly, three case studies with implementation of the algorithm are discussed.