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The increasing use of photovoltaics (PVs) in distribution systems owing to the low-carbon policy has given rise to the need for various technological changes. In particular, the operation of on-load tap changers (OLTCs) has attracted attention. In traditional distribution systems, the OLTC operates via a line-drop compensator (LDC), which focuses on the load to solve the low-voltage problem; however, the problem of over-voltage caused by PVs persists. Currently, a method for operating an OLTC using the measured voltage is being researched; however, solving the voltage problem for several feeders connected to a main transformer (MT) is not viable. Therefore, this study proposes an OLTC operation method to address the feeder with the largest voltage problem depending on the direction of power flow. The proposed method selects a point where the OLTC operates using the difference between the measured and reference voltages. Setting the reference voltage can solve the problem that occurs due to the direction of power flow. Finally, the effectiveness of the proposed method is verified via case studies. Based on the results, we can conclude that the proposed method effectively solves the voltage problem, and an increase in hosting capacity can be expected. [ABSTRACT FROM AUTHOR]

Owing to the outbreak of COVID-19, researchers are exploring methods to prevent contact and non-contact infections that occur via multiple transmission routes. However, studies on preventing infections caused by droplet transmission in public transportation are insufficient. To prevent the spread of infectious diseases, a new ventilation system in railway vehicles must be developed. In this study, a novel vertical drop airflow (VDA) system is proposed to mitigate the effect of droplet transmission in a high-speed train cabin. The droplet transmission route and droplet fate are investigated using three-dimensional fluid dynamics simulations, performed employing the Eulerian–Lagrangian model. Additionally, a porous model is adopted to simulate the effect of close-fitting masks. The results indicate that 120 s after coughing, the decrease in the droplet number in the VDA system is 72.1% of that observed in the conventional system. Moreover, the VDA system effectively suppresses droplet transmission because the maximum droplet travel distances of the VDA systems are 49.9% to 67.0% of those of the conventional systems. Furthermore, the effect of reducing droplet transmission by wearing a close-fitting mask is confirmed in all systems. Thus, the decrease in both droplet number and droplet transmission area in train cabins validate that the proposed VDA system has an effective airflow design to prevent droplet infection. [ABSTRACT FROM AUTHOR]

In the power distribution system of South Korea, the sectionalizer minimizes and recovers the system from failures, and prohibits independent operation of distributed energy resources. Therefore, it is difficult to expect reliability improvements owing to a photovoltaic system in the power distribution system. Herein, we propose a reliability-centered maintenance-scheduling method based on an economic analysis of photovoltaic integration facilities to ensure the economic feasibility of the photovoltaic system operator and the reliability of the power distribution system. Photovoltaic integration facilities are divided into two categories based on their spread of the failure, and the maintenance scheduling is evaluated according to the maximum and minimum losses according to the time of failure. Facilities that cause power outages to photovoltaics and to loads have relatively little effect on the time of failure. This is because the effects of the power outages in the loads predominate. In contrast, facilities that only cause photovoltaic outages are affected by the generation time. In particular, insulated gate bipolar transistors that operate only during photovoltaic generation have been found to be more economical for corrective replacement than preventive replacement. [ABSTRACT FROM AUTHOR]

Owing to the increasing penetration level of distributed energy resources (DER) and direct current (DC) load, the usage of low-voltage direct current (LVDC) systems has expanded to achieve efficient operations. However, because the LVDC system reaches the peak fault current at a faster rate than the alternating current (AC) system, a solution that protects the system components is necessary to maintain system integrity. It is required by the low-voltage ride-through (LVRT) that the DERs maintain their interconnections with the LVDC system and support fault recovery. In this study, a method is proposed to allow the application of the superconducting fault current limiter (SFCL) to reduce the fault current and enhance the LVRT capability. However, when the DER maintain a connection to support fault recovery, the conventional resistive-type SFCL must withstand the burden of high-temperature superconducting (HTSC) operation during fault state dependence on LVRT. Therefore, this study proposes a trigger-type SFCL to reduce the burden of the HTSC element and enhance the LVRT capability. The voltage sag related to the LVRT was improved owing to the SFCL. The proposed solution was confirmed using PSCAD/EMTDC, which is a commercial software. [ABSTRACT FROM AUTHOR]

Osteopenia and sarcopenia can cause various senile diseases and are key factors related to the quality of life in old age. There is need for portable tools and methods that can analyze osteopenia and sarcopenia risks during daily life, rather than requiring a specialized hospital setting. Gait is a suitable indicator of musculoskeletal diseases; therefore, we analyzed the gait signal obtained from an inertial-sensor-based wearable gait device as a tool to manage bone loss and muscle loss in daily life. To analyze the inertial-sensor-based gait, the inertial signal was classified into seven gait phases, and descriptive statistical parameters were obtained for each gait phase. Subsequently, explainable artificial intelligence was utilized to analyze the contribution and importance of descriptive statistical parameters on osteopenia and sarcopenia. It was found that XGBoost yielded a high accuracy of 88.69% for osteopenia, whereas the random forest approach showed a high accuracy of 93.75% for sarcopenia. Transfer learning with a ResNet backbone exhibited appropriate performance but showed lower accuracy than the descriptive statistical parameter-based identification result. The proposed gait analysis method confirmed high classification accuracy and the statistical significance of gait factors that can be used for osteopenia and sarcopenia management. [ABSTRACT FROM AUTHOR]

Simple Summary: Tumor budding is a histopathologic characteristic which has led to a growing interest in the prognosis prediction of cancers of various sites. We aimed to evaluate whether imaging biomarkers could predict tumor budding status. Preoperative MRI radiomic features were used as imaging biomarkers. Four machine learning classifiers were applied to build prediction models using a training dataset. Internal validation was performed to validate the built models. As a result, radiomics-based models predicted tumor budding status with a mean area under the receiver operating characteristic value of 0.816 and a mean accuracy of 0.779 in the independent test dataset. Final selected features were mostly from filtered images, implying the importance of filtering methods in radiomics. Preoperative prediction of tumor budding status may help personalize treatment in cervical cancer patients. Background: Our previous study demonstrated that tumor budding (TB) status was associated with inferior overall survival in cervical cancer. The purpose of this study is to evaluate whether radiomic features can predict TB status in cervical cancer patients. Methods: Seventy-four patients with cervical cancer who underwent preoperative MRI and radical hysterectomy from 2011 to 2015 at our institution were enrolled. The patients were randomly allocated to the training dataset (n = 48) and test dataset (n = 26). Tumors were segmented on axial gadolinium-enhanced T1- and T2-weighted images. A total of 2074 radiomic features were extracted. Four machine learning classifiers, including logistic regression (LR), random forest (RF), support vector machine (SVM), and neural network (NN), were used. The trained models were validated on the test dataset. Results: Twenty radiomic features were selected; all were features from filtered-images and 85% were texture-related features. The area under the curve values and accuracy of the models by LR, RF, SVM and NN were 0.742 and 0.769, 0.782 and 0.731, 0.849 and 0.885, and 0.891 and 0.731, respectively, in the test dataset. Conclusion: MRI-based radiomic features could predict TB status in patients with cervical cancer. [ABSTRACT FROM AUTHOR]

Lithium batteries are used for frequency regulation in power systems because of their fast response and high efficiency. Lithium batteries have different life characteristics depending on their type, and it is necessary to set the optimal state-of-charge (SOC) operating range considering these characteristics to obtain the maximum gain. In general, narrowing the operating range increases the service life but may lower the performance of charging and discharging operations in response to frequency fluctuations, and vice versa. We present performance assessment indicators that consider charging and discharging due to frequency variations and lifespan of the batteries. However, to evaluate the performance, while reflecting the non-linear life characteristics of lithium batteries, simulating the entire operation is necessary, which requires a long calculation time. Therefore, we propose a master–slave parallel genetic algorithm to derive the optimal SOC operating range with reduced calculation time. A simulation program was implemented to evaluate the computational performance that determines the optimal SOC range. The proposed method reduces the calculation time while considering the non-linear life characteristics of lithium batteries. It was confirmed that a more accurate SOC operating range could be calculated by simulating the entire life span. [ABSTRACT FROM AUTHOR]

This paper proposes a method to improve the performance of a distribution system by optimizing volt–var function of a smart inverter to alleviate the voltage deviation problem due to distributed generation connection. In order to minimize voltage deviation and line losses which represent the performance of a distribution system, this paper proposes an algorithm that optimally sets the parameters of the volt–var function. In the process of optimizing the parameters of the volt–var function, the algorithm proposed in this paper considers minimizing the contribution of the reactive power in order not to affect the output of the distributed generation. In order to apply to the field, the distribution system in South Korea considering the configuration and operation regulation was selected as a test model for algorithm verification. As a result, the system performance was successfully improved by optimally setting the volt–var function of the smart inverter which is an effective way to solve the over-voltage problem caused by distributed generation connection. This paper verified the proposed method through OpenDSS, a quasi-static time-series simulation, for the test model considering the characteristics of the distribution system in South Korea. [ABSTRACT FROM AUTHOR]

As the application of low-voltage-direct-current system increases, fault analysis in the low-voltage-direct-current system has essential because the fault response has different from the conventional AC distribution system. Especially, the fault current by the discharge current of the capacitor in the low-voltage-direct-current distribution system has very large compared with the conventional AC distribution system. Therefore, this paper proposed the application of the superconducting fault current limiter for limiting the fault current on the low-voltage-direct-current system. As one of the protected methods against fault current, the superconducting fault current limiter which could quickly limit the fault current has been noticed as an attractive method. However, the protection relay may malfunction such as over current relay, selective protection relay due to limiting fault current by applying superconducting fault current limiter. Therefore, in this paper proposed a solution to malfunction problem of the protection relay using the voltage components of the high temperature superconductivity. This paper verified the effect of the proposed method through test modelling and PSCAD/EMTDC. [ABSTRACT FROM AUTHOR]

This study proposes a method for optimally selecting the operating parameters of an energy storage system (ESS) for frequency regulation (FR) in an electric power system. First, the method allows the optimal objective function of the selected parameters to be set in a flexible manner according to the electric market environment. The objective functions are defined so that they could be used under a variety of electricity market conditions. Second, evaluation frequencies are created in order to simulate the overall lifespan of the FR-ESS. Third, calendar and cycle degradation models are applied to the battery degradation, and are incorporated into evaluations of the degradation progress during the entire FR-ESS lifespan to obtain more accurate results. A calendar life limit is set, and the limit is also considered in the objective function evaluations. Fourth, an optimal parameter calculation algorithm, which uses the branch-and-bound method, is proposed to calculate the optimal parameters. A case study analyzes the convergence of the proposed algorithm and the results of the algorithm under various conditions. The results confirmed that the proposed algorithm yields optimal parameters that are appropriate according to the objective function and lifespan conditions. We anticipate that the proposed FR-ESS algorithm will be beneficial in establishing optimal operating strategies. [ABSTRACT FROM AUTHOR]

The penetration of wind turbine generators onto the grid has grown worldwide at unprecedented rates in recent years. This raises the concern that the tripping of wind turbine generators could potentially cause system collapses. To alleviate these concerns, wind turbine generators need to maintain connection with the grid when a grid fault occurs. This has provoked many countries to adopt low-voltage ride-through (LVRT) for wind turbine generators. The LVRT is the capability of wind turbine generators to maintain connectivity during certain periods of voltage sag. The wind turbine generators should be connected to the grid to support fault recovery. Also, wind turbine generators must provide reactive power according to the grid voltage sag. Therefore, much research has been focused on enhancing LVRT capability. To enhance LVRT capability, this paper proposes the application of a superconducting fault current limiter (SFCL) in the system. The fault current was suppressed and the voltage sag was improved through the application of the SFCL. By improving the voltage sag, the wind turbine generator and the grid were able to maintain a connection. However, suppression of the fault current can cause a problem in the overcurrent relay (OCR) trip time delay. The trip time delay was solved by OCR resetting. Through a power system computer-aided design/electromagnetic transients including DC (PSCAD/EMTDC), the enhancement of LVRT capability and improvement of the trip delay was confirmed. [ABSTRACT FROM AUTHOR]

Offshore wind farms with good wind quality are exponentially increasing. To take advantage of this, the offshore wind farms and the grid are connected using the MVDC. In the event of a grid fault, the traditional wind generators and the MVDC are disconnected from the grid fault to protect the devices. However, the wind generators and the MVDC must support the recovery of the grid fault because the disconnection of large capacity wind farms will cause a grid collapse. To prevent this problem, the LVRT requires maintaining the connection between the wind generators and the grid to contribute to the recovery of the grid fault. In this situation, the DC voltage of the MVDC rises due to the unbalanced power of the input and output. Several methods have been proposed to suppress the DC voltage rise of the MVDC. Among various methods, the CR is an effective method to suppress the DC voltage rise of the wind generators and the MVDC. However, the conventional CR designs only consider rated voltage and system capacity. Therefore, this paper proposes the parameter estimation of the CR considering the important factors. The proposed method is verified by PSCAD/EMTDC. [ABSTRACT FROM AUTHOR]