Discharge Depth Research Articles

Modeling the Effect of Cell Variation on the Performance of a Lithium-Ion Battery Module

Owing to the variation between lithium-ion battery (LIB) cells, early discharge termination and overdischarge can occur when cells are coupled in series or parallel, thereby triggering a decrease in LIB module performance and safety. This study provides a modeling approach that considers the effect of cell variation on the performance of LIB modules in energy storage applications for improving the reliability of the power quality of energy storage devices and efficiency of the energy system. Ohm’s law and the law of conservation of charge were employed as the governing equations to estimate the discharge behavior of a single strand composing of two LIB cells connected in parallel based on the polarization properties of the electrode. Using the modeling parameters of a single strand, the particle swarm optimization algorithm was adopted to predict the discharge capacity and internal resistance distribution of 14 strands connected in series. Based on the model of the LIB strand to predict the discharge behavior, the effect of cell variation on the deviation of the discharge termination voltage and depth of discharge imbalance was modeled. The validity of the model was confirmed by comparing the experimental data with the modeling results.

Triple-Function Electrolyte Regulation toward Advanced Aqueous Zn-Ion Batteries.

The poor Zn reversibility has been criticized for limiting applications of aqueous Zn-ion batteries (ZIBs); however, its behavior in aqueous media is not fully uncovered yet. Here, this knowledge gap is addressed, indicating that Zn electrodes face a O2 -involving corrosion, besides H2 evolution and dendrite growth. Differing from aqueous Li/Na batteries, removing O2 cannot enhance ZIB performance because of the aggravated competing H2 evolution. To address Zn issues, a one-off electrolyte strategy is reported by introducing the triple-function C3 H7 Na2 O6 P, which can take effects during the shelf time of battery. It regulates H+ concentration and reduces free-water activity, inhibiting H2 evolution. A self-healing solid/electrolyte interphase (SEI) can be triggered before battery operation, which suppresses O2 adsorption corrosion and dendritic deposition. Consequently, a high Zn reversibility of 99.6% is achieved under a high discharge depth of 85%. The pouch full-cell with a lean electrolyte displays a record lifespan with capacity retention of 95.5% after 500 cycles. This study not only looks deeply into Zn behavior in aqueous media but also underscores rules for the design of active metal anodes, including Zn and Li metals, during shelf time toward real applications.

An Approach to Flood Hazard Mapping for the Chao Phraya River Basin Using Rainfall-Runoff-Inundation Model

Flooding is a major natural hazard that can cause significant damage to socioeconomic and ecological systems. This study presents an approach to producing the maximum flood inundation and flood duration maps over the Chao Phraya River Basin (CPRB), Thailand. An integrated numerical model and spatial analysis tool were utilized in this study. The Rainfall-Runoff-Inundation (RRI) model was first used to simulate both river discharge and inundation depth. Then, the maximum flood inundation and flood duration maps with different return periods were estimated using a Geographical Information System (GIS) tool. The results illustrate that the flood inundation areas were spread out, starting from Nakhon Sawan Province, which is located in the central part of the basin. The maximum flood inundation depth could reach up to approximately 7.71, 8.28, and 8.78 m for the flood return periods of 50, 100, and 200 years, respectively. The results also indicate that the inundation areas over the CPRB could cover approximately 21,837, 23,392, and 24,533 km2 for flood return periods of 50, 100, and 200 years, respectively. The longest flood durations for return periods of 50, 100, and 200 years were approximately 159, 177, and 198 days, respectively. The longest flood duration occurred in the vicinity of the Nakhon Sawan. This study suggests that flood inundation areas and duration mapping could provide supporting information regarding the impacts caused by varying degrees of flood hazards and can be used to enhance comprehensive disaster risk management planning.

Improving Snow‐Process Modeling by Evaluating Reanalysis Vertical Temperature Profiles Using a Distributed Hydrological Model

AbstractThe use of the Japanese 55‐year Reanalysis (JRA55) vertical temperature profile (VTP) has been suggested in previous studies for estimating gridded air temperatures at high elevations in data‐scarce regions to conduct hydrological simulations. In this study, we investigate and further enhance the applicability of VTP for hydrological simulations through several experimental sets using a distributed hydrological model with improved snow physics (WEB‐DHM‐S) based on water and energy budget to simulate the hydrology of a snowfed river basin in Japan, Kurobe Basin, while simultaneously correcting the snow precipitation estimates through optimization. We examined the simulated discharge, point snow depth, and snow cover, finding that the snow processes were highly sensitive to the individual station used with VTP for extrapolating air temperature to higher elevations, with corrected snowfall estimates differing by as much as 18%. We further compared this with simulations based on linear regression‐based lapse rates derived from station observations (scarce and often distributed at low elevations). It was found that the use of VTP improved discharge simulations but deteriorated point snow depth simulations at low elevations, compared with linear regression‐based lapse rates. A hybrid of the two methods led to better discharge and point snow depth simulations with reasonable snow cover simulations. The study advances the application of snow‐process models in data‐scarce regions by enhancing our understanding about the usage of VTP.

Numerical and experimental study on thermal management of NCM-21700 Li-ion battery

Energy and environmental challenges have been increasingly important in recent years, and electric vehicles equipped by lithium-ion batteries have demonstrated significant promise and advantages in addressing these issues. Thermal management of battery has emerged as an important criterion to consider in development and spread of lithium-ion batteries used in electric vehicles. In this work, thermal management of a NCM-21700 battery is performed experimentally and numerically. An electrochemical model is employed to simulate the irreversible and reversible heat generation in battery at various discharge rates. The temperature predictions are carried out at different values of discharge rate and depth of discharge (DoD) using CFD commercial software. The results show that predictions at each discharge rate are well matched with experimental data. Besides, the measured results indicate that with the increase of the discharge rate, the attenuation of the battery capacity also increases, and the loss of capacity is proportional to the increase of the discharge rate. When discharge rate is increased to 5C rate, internal temperature of battery would be greater than 50 °C, which is beyond operating temperature range. A significant temperature gradient is also appeared inside battery, indicating that the non-uniformity in the temperature is increased rapidly.

Comparison of mortality prediction models for road traffic accidents: an ensemble technique for imbalanced data

BackgroundInjuries caused by RTA are classified under the International Classification of Diseases-10 as ‘S00-T99’ and represent imbalanced samples with a mortality rate of only 1.2% among all RTA victims. To predict the characteristics of external causes of road traffic accident (RTA) injuries and mortality, we compared performances based on differences in the correction and classification techniques for imbalanced samples.MethodsThe present study extracted and utilized data spanning over a 5-year period (2013–2017) from the Korean National Hospital Discharge In-depth Injury Survey (KNHDS), a national level survey conducted by the Korea Disease Control and Prevention Agency, A total of eight variables were used in the prediction, including patient, accident, and injury/disease characteristics. As the data was imbalanced, a sample consisting of only severe injuries was constructed and compared against the total sample. Considering the characteristics of the samples, preprocessing was performed in the study. The samples were standardized first, considering that they contained many variables with different units. Among the ensemble techniques for classification, the present study utilized Random Forest, Extra-Trees, and XGBoost. Four different over- and under-sampling techniques were used to compare the performance of algorithms using “accuracy”, “precision”, “recall”, “F1”, and “MCC”.ResultsThe results showed that among the prediction techniques, XGBoost had the best performance. While the synthetic minority oversampling technique (SMOTE), a type of over-sampling, also demonstrated a certain level of performance, under-sampling was the most superior. Overall, prediction by the XGBoost model with samples using SMOTE produced the best results.ConclusionThis study presented the results of an empirical comparison of the validity of sampling techniques and classification algorithms that affect the accuracy of imbalanced samples by combining two techniques. The findings could be used as reference data in classification analyses of imbalanced data in the medical field.

The Association of Physical and Mental Illness and Self-Harm Resulting in Hospitalization: A Population-Based Study of Older Adults in South Korea.

Self-harm injury among older adults is a pressing problem that demands social attention in South Korea. This study sought to identify the association between physical and mental illness and hospitalization following self-harm injuries, compared to non-self-harm injuries, among older adults living in Korea. We analyzed individuals aged 65 and older who were admitted to hospitals either for self-harm or non-self-harm from a population-based survey of the Korea National Hospital Discharge In-depth Injury Survey (KNHDIS). A logistic regression analysis was performed. Compared with non-self-harm-related hospitalization, self-harm hospitalization was associated with higher odds of depression, other disorders of the nervous system, malignancies, alcohol misuse and dependence, and drug-related dependence. Dementia, anxiety disorder, diabetes, arthritis, cerebral palsy, and other paralytic syndromes had a lower likelihood of leading to self-harm than non-self-harm hospitalization. The findings of this study can inform medical professionals to identify older adults with a heightened risk of self-harming behavior leading to hospitalization.

The Energy Storage System Integration Into Photovoltaic Systems: A Case Study of Energy Management at UTFPR

Energy storage system integration can reduce electricity costs and provide desirable flexibility and reliability for photovoltaic (PV) systems, decreasing renewable energy fluctuations and technical constraints. In this sense, this study aimed to propose energy management strategies through this integration, aiming to improve the demand profile of a university commercial consumer for compensation during peak hours. To achieve the objectives of this research, a pilot project was installed which included a 10 kWp grid-tie PV system (GTPVS), bidirectional inverters, and battery bank, as part of a research and development (R&D) project implemented in the Federal University of Technology–Paraná (UTFPR) Curitiba campus at Neoville headquarters. The methodology consisted of the analysis of variables that interfere with the operation of this system, such as a detailed university profile of demand and consumption, local energy pricing, PV generation profile as well as the interaction between PV generator and the energy storage system, and the variation in power fluctuations throughout the year. Additionally, a technical feasibility study was carried out aimed to determine this consumer’s optimal size through the Homer Grid software. The detailed demand profile allowed us to know in depth the peak values were above 80 kW, for university working days. Furthermore, the daily analysis of the PV generation profile confirmed that although the PV source is quite variable, the scheduled dispatch operation is not interfered by the variability and intermittency of the solar source, as the system was designed and programmed to operate in parallel with the electrical network. Regarding the energy consumed at the university, very significant values were obtained, in which the month of July presented the highest consumption for the base year 2019, with a total monthly value of 48,670 kWh. The established operating strategy for the battery bank with a 10% discharge depth resulted in a life cycle of 2,500 cycles which can extend its useful life by approximately 9.5 years. The results obtained by the simulation show different levels of energy contribution with percentages of 60.0, 33.6, and 2.7%, respectively.

Clinical Characteristics of Adolescents Hospitalized Through Emergency Room for Intentional Self-Harm or Suicide Attempts

ObjectivesThis study aimed to investigate the clinical characteristics of adolescents hospitalized through the emergency room for intentional self-harm or suicide attempts.MethodsThis retrospective study used data from the Korean National Hospital Discharge In-depth Injury Survey conducted between 2006 and 2018 for individuals aged 10–24 years. The clinical characteristics of the patients were analyzed and compared across sex and age groups using the Rao-Scott chi-square tests and multiple logistic regression analysis for complex survey data.ResultsThe most common psychiatric diagnosis was mood disorder (22.0%), and more female patients were diagnosed with it than male patients (p=0.010). The 19–24 years age group was diagnosed with mood disorder the most compared to other younger groups (p=0.012). Male patients used lethal methods more than female patients (p=0.008), and the 19–24 years age group used more drug poisoning and cutting or piercing (p<0.001) for intentional self-harm or suicide attempts than younger groups.ConclusionAdolescents hospitalized for intentional self-harm or suicide attempts showed significant differences in clinical characteristics across sex and age groups. These findings suggest that measures for preventing self-harm or suicide attempts need to be differentiated according to the sex and age of adolescents.

The Impact of the Association between Cancer and Diabetes Mellitus on Mortality.

The prevalence of cancer, diabetes mellitus (DM), and hypertension is increasing in ageing populations. We analyzed the association of DM with cancer and its effects on cancer mortality. The data of 2009–2018 from the Korea National Hospital Discharge In-depth Injury Survey were used; 169,959 adults with cancer as the main diagnosis were identified. The association rule for unsupervised machine learning was used. Association rule mining was used to analyze the association between the diseases. Logistic regression was performed to determine the effects of DM on cancer mortality. DM prevalence was 12.9%. Cancers with high DM prevalence were pancreatic (29.9%), bile duct (22.7%), liver (21.4%), gallbladder (15.5%), and lung cancers (15.4%). Cancers with high hypertension prevalence were bile duct (31.4%), ureter (30.5%), kidney (29.5%), pancreatic (28.1%), and bladder cancers (27.5%). The bidirectional association between DM and hypertension in cancer was the strongest (lift = 2.629, interest support [IS] scale = 0.426), followed by that between lung cancer and hypertension (lift = 1.280, IS scale = 0.204), liver cancer and DM (lift = 1.658, IS scale = 0.204), hypertension and liver cancer and DM (lift = 3.363, IS scale = 0.197), colorectal cancer and hypertension (lift = 1.133, IS scale = 0.180), and gastric cancer and hypertension (lift = 1.072, IS scale = 0.175). DM increased liver cancer mortality (p = 0.000), while hypertension significantly increased the mortality rate of stomach, colorectal, liver, and lung cancers. Our study confirmed the association between cancer and DM. Consequently, a patient management strategy with presumptive diagnostic ability for DM and hypertension is required to decrease cancer mortality rates.

기후변화를 고려한 토석류 재해취약지역 레질리언스 강화를 위한 연구

Recently, climate change has caused serious natural disasters at the vulnerable areas with many mountainous regions. This study analyzes the behavior of debris flow with respect to time elapse by applying various precipitation, mountain slope change, and the categories of vegetation loosened in mountainous areas. The behavior of debris flow is debris flow discharge and water depth. In addition, the runout length of debris flow passed through the channel and reached the downstream according to the change of the water supply and slope was measured. The larger the supply flow, the higher the debris flow discharge, and the second peak value became faster as the supply flow increased, and the slope became steeper. In the category where the multiplier of vegetation for debris flow is large, the fluctuation period was made long, and the amplitude of the fluctuation was also made large. As for the debris flow runout length, the supply flow was large and it was spread in a considerable range on steep slopes. This study will provide various information such as establishing measures for debris flow occurring in vulnerable areas to natural disasters due to climate change, or establishing a plan for strengthening resilience.

Application of Machine Learning and Process-Based Models for Rainfall-Runoff Simulation in DuPage River Basin, Illinois

Rainfall-runoff simulation is vital for planning and controlling flood control events. Hydrology modeling using Hydrological Engineering Center—Hydrologic Modeling System (HEC-HMS) is accepted globally for event-based or continuous simulation of the rainfall-runoff operation. Similarly, machine learning is a fast-growing discipline that offers numerous alternatives suitable for hydrology research’s high demands and limitations. Conventional and process-based models such as HEC-HMS are typically created at specific spatiotemporal scales and do not easily fit the diversified and complex input parameters. Therefore, in this research, the effectiveness of Random Forest, a machine learning model, was compared with HEC-HMS for the rainfall-runoff process. Furthermore, we also performed a hydraulic simulation in Hydrological Engineering Center—Geospatial River Analysis System (HEC-RAS) using the input discharge obtained from the Random Forest model. The reliability of the Random Forest model and the HEC-HMS model was evaluated using different statistical indexes. The coefficient of determination (R2), standard deviation ratio (RSR), and normalized root mean square error (NRMSE) were 0.94, 0.23, and 0.17 for the training data and 0.72, 0.56, and 0.26 for the testing data, respectively, for the Random Forest model. Similarly, the R2, RSR, and NRMSE were 0.99, 0.16, and 0.06 for the calibration period and 0.96, 0.35, and 0.10 for the validation period, respectively, for the HEC-HMS model. The Random Forest model slightly underestimated peak discharge values, whereas the HEC-HMS model slightly overestimated the peak discharge value. Statistical index values illustrated the good performance of the Random Forest and HEC-HMS models, which revealed the suitability of both models for hydrology analysis. In addition, the flood depth generated by HEC-RAS using the Random Forest predicted discharge underestimated the flood depth during the peak flooding event. This result proves that HEC-HMS could compensate Random Forest for the peak discharge and flood depth during extreme events. In conclusion, the integrated machine learning and physical-based model can provide more confidence in rainfall-runoff and flood depth prediction.

Lung Cancer Patients’ Characteristics and Comorbidities Using the Korean National Hospital Discharge In-depth Injury Survey Data

BackgroundThe aim of this study was to assess the incidence of lung cancer and comorbidities in Korea and analyze the lung cancer patient’s characteristics and their comorbidities over the past 12 years. This study also aimed to investigate factors related to death as treatment outcome in discharged lung cancer patients.MethodsThis study analyzed the data obtained from the Korean National Hospital Discharge In-depth Injury Survey from 2006 to 2017. The quantity of discharged lung cancer patients was assessed by year. Comorbidities were limited to those included in the Elixhauser Comorbidity Index (ECI). A Chi-square test was performed to determine statistically significant differences in the distributions of the ECI and ECI scores according to the presence or absence of metastatic cancer. Logistic regression analysis was used to analyze factors related to death as treatment outcome.ResultsFrom 2006 to 2017, the number of discharged male and female patients with lung cancer increased from 31,720 to 42,016 and 10,897 to 18,197, respectively. The increase in the number of lung cancer patients was greater in women than in men (67.0% vs. 32.5%, respectively). The most common associated comorbidities were hypertension, diabetes, and chronic pulmonary disease. The factors related to death as treatment outcome were found to include sex, admission route, number of hospital beds, length of stay, presence or absence of metastatic cancer, and ECI score.ConclusionThe number of lung cancer patients in Korea has increased, and a high proportion of these patients have chronic diseases, which negatively would impact the treatment and outcome of lung cancer patients as well as their quality of life. Thus, the management of chronic diseases needs to be prioritized in patients with lung cancer.

Factors Associated with Hospital Length of Stay among Women’s Cancer Patients: Based on the In-depth Injury Patient Surveillance System Data

Objectives: This study sought to evaluate factors associated with hospital length of stay (LOS) in four women’s cancer (ovarian, breast, uterine cervix and uterine corpus cancer) patients.Methods: The Korean National Hospital Discharge In-depth Injury Survey Data (2006-2017) collected by the Korea Centers for Disease Control and Prevention were used. We extracted 74,641 inpatients who were diagnosed with women’s cancer. We conducted a frequency analysis to analyze general characteristics of the study subjects for the four women’s cancers, and used the analysis of variance to compare the difference in the average LOS according to these characteristics. In addition, we performed Poisson regression analysis to evaluate the effects of demographic characteristics, medical institutions, medical use characteristics, and disease characteristics on the LOS in women’s cancer patients.Results: During the study period, the average LOS for each women’s cancer patients were 6.9 days for ovarian cancer, 6.0 days for breast cancer, 8.6 days for uterine cervical cancer, and 7.8 days for uterine corpus cancer. Among women’s cancers, cervical cancer patients had the longest average hospital stay. According to the Poisson regression analysis, it was found that pay method for medical expense (relative risk [RR] range: 1.019-1.498), admission route (RR range: 1.908-2.133), hospital residence (RR range: 0.698-1.068), the number of beds (RR range: 0.546-0.920), the Charlson Comorbidity Index (CCI) severity (RR range: 1.139-1.529), and comorbidities have a significant influence on LOS for all women’s cancer patients.Conclusions: It is necessary to efficiently manage the LOS for women’s cancer patients in the future by considering the determinants of each women’s cancer identified in our study.

Prediction of flood discharge and flood flow depth using a hydraulic model and flood marks on the trees in ungauged forested watersheds

It is difficult to estimate flood discharges and the flood zones as well as to design hydraulic structures in rivers without using hydrometric stations. Furthermore, using different models to determine the mentioned cases will be accompanied by errors. Therefore, flood marks on the trunks of trees located in the Babolrood riverbed were used to determine the peak discharge, flood flow depth, and flood zone in northern Iran. First, a hydraulic model for the study river was provided using topographic maps with a scale of 1: 1 000, HEC-GeoRAS extension (GIS), and HEC-RAS model. Then, the flood marks of past floods in the form of silt and clay sediments (deposits on the trees in the riverbed) were evaluated and the maximum flood flow depth was determined. Finally, the peak discharge of the past flood was estimated by the trial-and-error method to achieve the flood flow depth in the different river reaches. Then, the hydraulic model using the flow depth data was calibrated in the reaches, and, in the final step, based on the flood marks of other reaches, the model was validated. According to the results, the maximum instantaneous discharge rate of the study flood was 155 m&lt;sup&gt;3&lt;/sup&gt;·s&lt;sup&gt;–1&lt;/sup&gt; and the maximum flood flow depth was about 2 m. Furthermore, the results showed that the flood mark data in forest lands can be used as a tool for the calibration and validation of hydraulic models. The present methodology is an efficient method for determining the flood peak discharge, spatial variation of the flood depth, and flood zone in forest watersheds without hydrometric stations.

Multiscale investigation of discharge rate dependence of capacity fade for lithium-ion battery

Commercial 18,650 lithium-ion batteries are cycled at different discharge current rates. It reveals that an accelerated capacity fade occurs for cells at a low discharge rate which is attributed to the loss of lithium inventory (LLI) from the differential voltage analysis (DVA). Cells using high discharge rates exhibit more kinetic loss at the same capacity retention from the analysis of impedance. Characterization techniques, i.e., post-mortem analysis including scanning electron microscopy (SEM) and ex-situ x-ray diffraction (XRD), galvanostatic tests, and in-situ XRD on half-cells made with cathodes and anodes retrieved from the 18,650 batteries, are used to further address the degradation factors. It indicates that the kinetic loss of the high discharge cells can be ascribed to the cathode where more particles are cracked and pulverized. Degradation on the anode is the primary reason for accelerated capacity fade occurring at the low discharge rate. The low discharge current deepens the discharge depth leading the graphite accessing into a higher potential over de-lithiation. Worse interphases and dense agglomerated structure are found from SEM images, which is deemed to result from the anode cycled at a high potential where large volumetric change happens as evidenced by the cycling of new anode half-cells.

Overcharge to Remove Cathode Passivation Layer for Reviving Failed Li–O 2 Batteries

Overcharge to Remove Cathode Passivation Layer for Reviving Failed Li–O ₂ Batteries

Assessment of Groundwater Potential Zones of Upper Blue Nile River Basin Using Multi-Influencing Factors under GIS and RS Environment: A Case Study on Guder Watersheds, Abay Basin, Oromia Region, Ethiopia

Groundwater is the most crucial resource for human beings and plays an important role in combating climate change and is substantial to human existence on the globe. Overall increased demand for water in different sectors, population growth, and unreliable rainfall necessitates the planning and management of groundwater. In this study, groundwater potential zones are delineated by combining remote sensing and geographical information system techniques in the Guder watersheds of the Upper Blue Nile Basin. Groundwater potential zones are prepared by using various multi-influencing factors like geomorphology, land use/cover, lithology, soil type, soil texture, drainage density, slope, lineament, rainfall, and elevation. These influencing factors’ features were given appropriate weightage according to Saaty’s AHP method, expert judgment, and their relative significance for groundwater occurrence. The groundwater potential zone was classified into different categories as very poor, poor, moderate, good, and very good according to quantile classification. This study reveals that about 33.6% of the Guder River Basin represents a good andvery good GWPZ category with an equal value of 16.8%,; while values 23.3%, 20.2%, and 22.9% were denoted by very poor, poor, and moderate groundwater potential zone, respectively. GWPZ was validated by field-collected data such as well discharge and soil depth. An accepted similarity was observed between delineated GWPZ and the basin’s soil depth graphically. The results of this study were also verified by correlation and kappa statistics values of 0.73and 77%, respectively. The study is certain with a sensible dimension of consistency in pairwise comparison between influencing and the overall weightage. The very high GWPZs are found in the northern part starting from the center longitude of the study area, more along with the northwestern, southern, and southwestern of the Guder subbasin. Low to very low groundwater potentiality has been seen at different distances from the center due to the presence of escapements, hills and steep side slopes, slopes, and rock surfaces. The study also revealed that the zone of high groundwater potential has high soil depth, and the zone of low groundwater showed low soil depth as the capacity of the aquifer to store water may depend on the depth of soil profile. This study attests to the GIS and remote sensing techniques as an effective model for delineation of GWPZs and can be applied at other basins of Ethiopia.

Comparison of energy parameters of electric storage systems for DC and AC traction power supply systems

Introduction. The article discusses the energy parameters of electric power storage systems for DC and AC traction power supply systems. The purpose of the research is to evaluate the energy parameters of electric power storage systems located within the inter-substation zone boundaries of the AC traction power supply system at the 25 kV voltage.Materials and methods. The author used the methods of modeling, statistics and the experimental results processing. Moreover, the paper presented the parameter estimation of the energy accumulation system on the basis of the traction calculations for the AC rolling stock. In addition, the author made two variants of calculations — in the presence and the absence of the electric storage system. The researcher also made the simulation of the electric storage system for the voltage source connected to the sectioning post busbars.Results. Using the simulation modeling, the author presents active and reactive power graphs of the inter-substation zone boundaries in the active sectioning post operation conditions. Therefore, the article demonstrates the graph of the expected charge, the discharge depth calculations for the nominal energy capacity and the required charging features, which guarantee the charge restoration of the accumulation system to the initial level.Discussion and conclusion. The author offers the comparative assessment of the electric storage systems for the traction power supply with the DС voltage of 3 kV and the AC voltage of 25 kV. The research demonstrates the reducing potential of the nominal accumulation parameters.

Analysing the Performance of Four Hydrological Models in a Chinese Arid and Semi-Arid Catchment

Frequent flood hazards in the Raoyang River Basin in western Liaoning, China, have posed serious threats to people’s lives and property. In an effort to study the simulation efficiencies of hydrological models in this arid and semi-arid catchment, this study examined the performance of the Xin’anjiang model, the Liaoning unsaturated model, and the DHF model in the Dongbaichengzi station watershed in the upper reaches of the Raoyang River, China. Additionally, this paper proposed an improved DHF model, which considers the impoundment and regulation of small- and medium-sized reservoirs in the upper reaches of the basin. The flood simulation results demonstrated that the Xin’anjiang model was difficult to apply in this area because the average value of its Nash–Sutcliffe efficiency (NSE) was as low as 0.31. Meanwhile, the simulation efficiencies of the Liaoning unsaturated model and the DHF model were higher than that of the Xin’anjiang model, but the relative error of flood peak discharge and runoff depth for most floods were still high and could not meet the actual forecast requirements by the Reservoir Administration Bureau of Liaoning Province. Overall, the improved DHF model showed the best efficiency, and the mean value of the NSE reached 0.79. Therefore, the improved DHF model has good applicability in the Dongbaichengzi station watershed in the upper reaches of the Raoyang River, China.