An Energy Storage System’s Operational Management and Control Method Considering a Battery System
Electronics 2020, 9(2), 356; https://doi.org/10.3390/electronics9020356 (registering DOI) - 20 Feb 2020
Losses in energy storage systems (ESSs) result from losses in battery systems and power conversion systems (PCSs). Thus, the power difference between the input and output occurs as a loss, which is considered an operational cost. Additionally, since battery systems consist of modules,
[...] Read more.
Losses in energy storage systems (ESSs) result from losses in battery systems and power conversion systems (PCSs). Thus, the power difference between the input and output occurs as a loss, which is considered an operational cost. Additionally, since battery systems consist of modules, there is always a temperature difference. Even if voltage balancing is conducted, deviations between the state of health (SoH) and state of charge (SoC) always exist. Therefore, a battery characteristic should be considered in relation to the efficient operation of an ESS. In this paper, charging control is implemented based on the SoC. When errors occur in the beginning, the coulomb counting method (CCM) continues to produce errors; it also calculates the SoC through an improved equation. Thus, it can calculate the SoC by using high-accuracy initial values. Moreover, battery deterioration occurs during charging and discharging, which increases a battery’s internal resistance. This reduces the switching time to the battery cut-off voltage or constant voltage (CV) mode, so it becomes possible to calculate the SoH. Therefore, in this paper, the algorithms and equations are proposed to perform SoH operations according to the charging time that is able to reach CV after charging. A conventional battery is usually charged by using constant current (CC) charging until the voltage of the battery module reaches the cut-off area. A switch to CV then occurs when the cut-off area is reached and maintained. However, SoC-based selective charging control is carried out to prevent heat problems. In addition, the battery is charged safely and efficiently by conducting SoH prediction considering the battery thermal characteristics, which vary depending on the charging time and other characteristics. In this paper, a 3 kW ESS was produced, and the proposed algorithm’s feasibility was verified.