In recent years, the demand for medium and large secondary batteries in EV (electric vehicle) and ESS (energy storage systems) applications has been rapidly increasing worldwide, and accordingly, the market size is increasing exponentially. However, the recent fire accidents related to secondary batteries for EVs and ESS are having a negative impact on the battery market. Therefore, this paper implements an accident simulation device to perform an external short-circuit test, one of the typical safety tests for NMC-series prismatic and pouch-type batteries that are widely used among battery cells used in medium and large secondary batteries. The implemented accident simulation device for the external short-circuit test is composed of short-circuit resistance, measuring device, control device, etc., and is configured to analyze external short-circuit characteristics according to various test conditions. Based on this, an external short-circuit test according to the type, short-circuit resistance and SOC (states of charge) of the lithium-ion battery was performed to confirm the current and temperature characteristics according to each condition. As a result of performing an external short-circuit test for each protection device in the battery module and preprocessing temperature, it is certain that the module fuse operates over 120 times faster than the cell fuse based on the same SOC conditions, and the quantity of electric charge in the module fuse is over 110 times smaller than of the cell fuse in the case of a short-circuit fault. It is also found that the highest and lowest preprocessing temperatures are considered to be severe conditions. Based on the proposed mechanism of an external short circuit in a Li-ion battery and the test device for the external short circuit, it is confirmed that this paper can contribute to the safety assessment of Li-ion battery-based ESS.

In recent years, the energy industry has increased the proportion of renewable energy sources, which are sustainable and carbon-free. However, the increase in renewable energy sources has led to grid instability due to factors such as the intermittent power generation of renewable sources, forecasting inaccuracies, and the lack of metering for small-scale power sources. Various studies have been carried out to address these issues. Among these, research on Virtual Power Plants (VPP) has focused on integrating unmanaged renewable energy sources into a unified system to improve their visibility. This research is now being applied in the energy trading market. However, the purpose of VPP aggregators has been to maximize profits. As a result, they have not considered the impact on distribution networks and have bid all available distributed resources into the energy market. While this approach has increased the visibility of renewables, an additional method is needed to deal with the grid instability caused by the increase in renewables. Consequently, grid operators have tried to address these issues by diversifying the energy market. As regulatory method, they have introduced real-time energy markets, imbalance penalty fees, and limitations on the output of distributed energy resources (DERs), in addition to the existing day-ahead market. In response, this paper proposes an optimal scheduling method for VPP aggregators that adapts to the diversifying energy market and enhances the operational benefits of VPPs by using two Mixed-Integer Linear Programming (MILP) models. The validity of the proposed model and algorithm is verified through a case study analysis.

The introduction of electrical vehicle charging infrastructure including electric vehicle (EV) charger renewable energy resource at the secondary feeder in a distribution system has been increased as one of countermeasure for global environmental issues. However, the electric vehicle charging (EVC) infrastructure may act as the peak load in the distribution system, which can adversely impact on the voltage stability when the electric vehicle is quickly charged. Therefore, to keep within the limit capacity of a secondary feeder and allowable limit for the feeder voltage, this paper proposes a stabilization method by an energy storage system (ESS) control strategy at the secondary feeder to not exceed the upper limit or fall below the lower limit. In addition, this paper presents an estimation method to keep the proper standard value of the state of charge (SOC). From the simulation results, the voltage stabilization operation by the ESS should make the feeder voltages of the distribution system (secondary feeder) introduced EVC infrastructure keep better voltage conditions. In addition, the estimation method was able to keep the proper standard value confirming that the SOC of the ESS when it is in standby can be kept within the proper reference range. Therefore, it is confirmed that this strategy is an effective tool to solve the voltage problems by ESS.

The voltage in distribution systems is controlled by the under-load tap changer of the substation and the pole transformer of the primary feeders. Recently, as one of the main countermeasures, a step voltage regulator is being introduced to solve voltage problems such as overvoltage phenomena in a distribution feeder interconnected with a renewable energy source and under voltage in a long-distance feeder. However, the tap of the step voltage regulator may be frequently operated due to its interdependent relationship with the under-load tap changer in the distribution system. Furthermore, given the existing operating characteristics of the step voltage regulator, it is difficult to perfectly maintain the customer voltage within an allowable limit using existing methods such as the line drop compensation method for a step voltage regulator. In addition, the existing line drop compensation method, considering the distributed generators, may be not able to control the proper voltage within an allowable limit. Therefore, in order to solve such voltage problems, this paper proposes a voltage control method for a step voltage regulator by considering the output voltage of an under-load tap changer that is operated via the line drop compensation method. In other words, to overcome the limitations of existing voltage control methods for step voltage regulators, this paper proposes an optimal control method to determine the optimal compensation rate for a step voltage regulator by considering the reverse power flow from a renewable energy source and the output voltage of the under-load tap changer of the main transformer.

With the intention of keep the customer voltage within a nominal voltage boundary (the South Korea voltage regulation in range of 220 V ± 6% for a single phase), the SVR (step voltage regulator) method in the primary feeder has been seriously systematized for the scheduled tap time delay (from a minimum of 120 s to a maximum of 900 s). The voltage must be compensated for the primary feeder during the tap delay time of SVR. However, when RES (renewable energy resource) is connected with the primary feeder, the customer voltage could exceed the nominal voltage boundary. Therefore, in order to keep the secondary feeder voltage within the nominal voltage boundary at all the time, this paper proposed a novel voltage control method in the primary feeder using coordinated controls between ESS (energy storage system) and SVR. Through the simulations based on PSCAD/EMTDC which is analysis tool of power system, it is confirmed that the proposed algorithm can effectively control the customer voltage within allowable limitation.

In this paper, a linear matrix inequality (LMI)-based robust model predictive speed control (RMPSC) with a disturbance observer (DOB) is proposed to guarantee stability and control performance against the parameter uncertainty and disturbance of a permanent magnetic synchronous motor (PMSM). All external torques applied to the PMSM are defined as disturbance, estimated by the DOB, and used to construct the RMPSC method. The proposed DOB and RMPSC are determined by a multiple LMI-based optimization approach. Furthermore, parameter uncertainty within a certain range, due to manufacturing errors or aging deterioration, is considered and a systematic tuning method is proposed to obtain the optimal gains. Finally, an offline optimization method is developed that ensures a low computational load to enable real-time processing. Simulation results demonstrate the effectiveness and validity of the proposed control method.