Aging increases the internal resistance of a battery and reduces its capacity; therefore, energy storage systems (ESSs) require a battery management system (BMS) algorithm that can manage the state of the battery. This paper proposes a battery efficiency calculation formula to manage the battery state. The proposed battery efficiency calculation formula uses the charging time, charging current, and battery capacity. An algorithm that can accurately determine the battery state is proposed by applying the proposed state of charge (SoC) and state of health (SoH) calculations. To reduce the initial error of the Coulomb counting method (CCM), the SoC can be calculated accurately by applying the battery efficiency to the open circuit voltage (OCV). During the charging and discharging process, the internal resistance of a battery increase and the constant current (CC) charging time decrease. The SoH can be predicted from the CC charging time of the battery and the battery efficiency, as proposed in this paper. Furthermore, a safe system is implemented during charging and discharging by applying a fault diagnosis algorithm to reduce the battery efficiency. The validity of the proposed BMS algorithm is demonstrated by applying it in a 3-kW ESS.
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.
This paper investigates the operation of each power conversion system (PCS) for efficient energy management systems (EMSs) of microgrids (MGs). When MGs are linked to renewable energy sources (RESs), the reduction in power conversion efficiency can be minimized. Furthermore, energy storage systems (ESSs) are utilized to manage the surplus power of RESs. Thus, the present work presents a method to minimize the use of the existing power grid and increase the utilization rate of energy generated through RESs. To minimize the use of the existing power grid, a PCS operation method for photovoltaics (PV) and ESS used in MGs is proposed. PV, when it is directly connected as an intermittent energy source, induces voltage fluctuations in the distribution network. Thus, to overcome this shortcoming, this paper utilizes a system that connects PV and a distributed energy storage system (DESS). A PV-DESS integrated module is designed and controlled for tracking constant power. In addition, the DESS serves to compensate for the insufficient power generation of PV. The main energy storage systems (MESSs) used in MGs affect all aspects of the power management in the system. Because MGs perform their operations based on the capacity of the MESS, a PCS designed with a large capacity is utilized to stably operate the system. Because the MESS performs energy management through operations under various load conditions, it must have constant efficiency under all load conditions. Therefore, this paper proposes a PCS operation algorithm with constant efficiency for the MESS. Utilizing the operation algorithm of each PCS, this paper describes the efficient energy management of the MG and further proposes an algorithm for operating the existing power grid at the minimum level.
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