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The aim of this study is to explore the prognostic values and optimal cutoff point of time to positivity (TTP) of blood culture in children with Klebsiella pneumoniae (K. pneumoniae) bloodstream infection. Ninety-four children with K. pneumoniae bloodstream infection hospitalized in Children's Hospital of Chongqing Medical University from April 2014 to January 2019 were enrolled retrospectively. TTP and risk factors were determined and analyzed by receiver operating characteristic (ROC) analysis and logistic regression analysis. The standard cutoff point of TTP was 13 h. Patients in early TTP (≤ 13 h) group had significantly higher in-hospital mortality (37.93% vs 6.15%, P = 0.000), higher incidence of septic shock (44.83% vs 6.15%, P = 0.000), higher proportion of PRISM III scores ≥ 10 (48.28% vs 20.00%, P = 0.005), and higher proportion of hypoalbuminemia on admission (44.83% vs 18.46%, P = 0.008). Multivariate analysis indicated PRISM III scores ≥ 10, early TTP, and hypoalbuminemia on admission were independent risk factors of in-hospital mortality (OR 8.36, 95% CI 1.80-38.92, P = 0.007; OR 5.85, 95% CI 1.33-25.61, P = 0.019; OR 5.73, 95% CI 1.30-25.22, P = 0.021, respectively) and septic shock (OR 14.04, 95% CI 2.63-75.38, P = 0.002; OR 11.26, 95% CI 2.10-60.22, P = 0.005; OR 10.27, 95% CI 2.01-52.35, P = 0.005, respectively).Conclusion: Early TTP (TTP ≤ 13 h), PRISM III scores ≥ 10, and hypoalbuminemia on admission appeared to be associated with worse outcomes for K. pneumoniae bloodstream infection children. What is Known: • Klebsiella pneumoniae bloodstream infection is an important cause of infectious disease morbidity and mortality worldwide in children. • Short duration of time to positivity indicated poor clinical outcomes. What is New: • Time to positivity ≤ 13 h, along with PRISM III scores ≥ 10 and hypoalbuminemia on admission, indicated higher in-hospital mortality and incidence of septic shock in Klebsiella pneumoniae bloodstream infection children. • The cut-off point of TTP in this pediatric study was much longer than that reported in adult patients.

Nonalcoholic fatty liver disease (NAFLD) has a developmental origin and is influenced in utero. We aimed to evaluate if maternal diet intervention before pregnancy would be beneficial to reduce the risk of offspring NAFLD. In our study, female mice were either on a normal-fat diet (NF group), or a high-fat diet for 12 weeks and continued on this diet throughout pregnancy and lactation (HF group), or switched from HF-to-NF diet 1 week (H1N group), or 9 weeks (H9N group) before pregnancy. Compared with the NF offspring, the H1N and HF, but not the H9N offspring, displayed more severe hepatic steatosis and glucose intolerance. More specifically, an abnormal blood lipid panel was seen in the H1N offspring and abnormal hepatic free fatty acid composition was present in both the HF and H1N offspring, while the H9N offspring displayed both at normal levels. These physiological changes were associated with desensitized hepatic insulin/AKT signaling, increased expression of genes and proteins for de novo lipogenesis and cholesterol synthesis, decreased expression of genes and proteins for fatty acid oxidation, increased Pcsk9 expression, and hypoactivation of 5′ AMP-activated protein kinase (AMPK) signaling in the HF and H1N offspring. However, these effects were completely or partially rescued in the H9N offspring. In summary, we found that early maternal diet intervention is effective in reducing the risk of offspring NAFLD caused by maternal HF diet. These findings provide significant support to develop effective diet intervention strategies and policies for prevention of obesity and NAFLD to promote optimal health outcomes for mothers and children. The authors evaluated the efficiency of different maternal diet interventions on reducing the risk for offspring nonalcoholic fatty liver disease due to maternal overnutrition. They found that that different maternal diet interventions prime the lipid metabolism differently via changes in lipogenesis and β-oxidation through insulin/AKT signaling and 5′ AMP-activated protein kinase signaling.

This paper proposes a cyber-physical active distribution system (CPADS) planning method, which considers the economic aspect and overall performance in the context of distributed generations (DGs) interconnection. First, the composition of CPADS is introduced for analyzing the effect of cyber system on the planning goals and constraints, based on which the dependence of the physical system on the cyber system is investigated. Then, the framework of CPADS planning is proposed by comparing it with active distribution system (ADS). Second, the planning is modeled to search for the appropriate DGs capacities, communication mode, and voltage control frequency with the constraints including performance, construction investment, and out-of-limit voltage probability, aiming at minimizing the construction and operation cost of cyber-physical systems and maximizing the DG penetration level. After that, the bi-layer multi-objective programming without considering the random failure of cyber system is adopted to derive the optimal solution set. Monte Carlo Simulation is then performed to solve for the out-of-limit voltage probability due to cyber failures, based on which the final scheme is obtained. Simulations are conducted on the modified IEEE 33-node distribution system. The results verify the effectiveness of the proposed method.

Background: Renal cell carcinoma (RCC) is one of the most common malignancies worldwide. Noninvasive imaging techniques, such as magnetic resonance imaging (MRI), single photon emission computed tomography (SPECT), and positron emission tomography (PET), have been involved in increasing evolution to detect RCC. This meta-analysis aims to compare to compare the value of MRI, SPECT, and PET in the diagnosis of RCC, and to provide evidence for decision-making in terms of further research and clinical settings.Methods: Electronic databases including PubMed, Web of Science, Embase, and Cochrane Library were systemically searched. Studies concerning MRI, SPECT, and PET for the detection of RCC were included. Pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), with their respective 95% confidence interval (CIs) and the area under the summary receiver operating characteristic (SROC) curve (AUC) were calculated.Results: A total of 44 articles were finally detected for inclusion in this meta-analysis. The pooled sensitivities of MRI, SPECT, and PET were 0.80, 0.81, and 0.88, respectively. Their respective overall specificities were 0.90, 0.54, and 0.87. Results in the subgroup analysis of the performance of SPECT that the pooled sensitivity, specificity, and AUC of the prospective SPECT studies included were 0.80, 0.42, 0.80, respectively. In the analysis of 18F-FDG PET, the pooled sensitivity, specificity, and AUC were 0.88, 0.86, and 0.92, respectively. PET studies showed a pooled sensitivity, specificity, and AUC of 0.80, 0.85, and 0.85, respectively in the diagnosis of primary RCC. The pooled sensitivity, specificity, and AUC of PET studies in detecting recurrent or metastatic RCC were 0.93, 0.88, and 0.94.Conclusion: Our meta-analysis manifests that MRI and PET present better diagnostic value for the detection of RCC in comparison with SPECT. PET is superior in the diagnosis of recurrent or metastatic RCC.

BACKGROUND: Vancomycin trough concentrations are associated with clinical outcomes and drug adverse effects. This study investigates the effects of continuous venovenous hemofiltration (CVVH) on vancomycin trough concentrations in critically ill children with a vancomycin dosage of 40–60 mg/kg/day. METHODS: Children with steady-state vancomycin trough concentrations admitted to the pediatric intensive care unit (PICU) between January 2016 and December 2019 were retrospectively enrolled. Patients were divided into CVVH and non-CVVH groups according to treatment differences and renal function. Vancomycin trough concentrations were then compared between the groups, and risk factors for supratherapeutic trough concentrations (>20 mg/L) were analyzed with logistic regression. RESULTS: Of the 119 patients included, 35 were enrolled in the CVVH group and 84 in the non-CVVH group. Median vancomycin trough concentrations were significantly higher in the CVVH group than those in the non-CVVH group [14.9 (IQR =9.6–19.6) vs. 9.3 (IQR =7.0–13.4), P

Objectives: To evaluate the effects of time to appropriate therapy (TTAT) on outcomes in children with nosocomial K. pneumoniae bloodstream infection, and to find an optimal time window for empiric antibiotics administration. Methods: Children with nosocomial K. pneumoniae bloodstream infection hospitalized in Children’s Hospital of Chongqing Medical University from April 2014 to December 2019 were enrolled retrospectively. TTAT cutoff point and risk factors were determined and analyzed by Classification and Regression Tree (CART) analysis and Logistic Regression analysis. Results: Overall, sixty-seven patients were enrolled. The incidence of septic shock and mortality was 17.91% (12/67) and 13.43% (9/67), respectively. The CART-derived TTAT cutoff point was 10.7 hours. The multivariate logistic regression analysis indicated delayed therapy (TTAT ≥ 10.7 h), PRISM III scores ≥ 10, early TTP (TTP ≤ 13 h), and need for invasive mechanical ventilation were independent risk factors of septic shock (OR 9.87, 95% CI 1.46-66.59, P = 0.019; OR 9.69, 95% CI 1.15-81.39, P = 0.036; OR 8.28, 95% CI 1.37-50.10, P = 0.021; OR 6.52, 95% CI 1.08-39.51, P = 0.042; respectively) and in-hospital mortality (OR 22.19, 95% CI 1.25-393.94, P = 0.035; OR 40.06, 95% CI 2.32-691.35, P = 0.011; OR 22.60, 95% CI 1.78-287.27, P = 0.016; OR 12.21, 95% CI 1.06-140.67, P = 0.045; respectively). Conclusions: TTAT is an independent predictor of poor outcome in children with nosocomial K. pneumoniae bloodstream infection. Initial appropriate antibiotic therapy should begin within 10.7 hours from the onset of bloodstream infection.

The sudden pandemic of SARS-Cov-2 (also known as novel coronavirus disease 2019, COVID-19) poses a severe threat to hundreds of millions of lives in the world. The complete cure of the virus largely relies on the immune system, which becomes particularly a challenge for the cancer subjects, whose immunity is generally compromised. However, in a constant evolving situation, the clinical data on the prevalence of SARS-Cov-2 for cancer patients is still limited. On top of a wide range of medical references and interim guidelines including CDC, NCI, ASCO, ESMO, NCCN, AACR, ESMO, and the National Health Commission of China, etc., we formed into a guideline based on our experience in our specialized cancer hospital in Wuhan, the originally endemic center of the virus. Furthermore, we formulated an expert consensus which was developed by all contributors from different disciplines after fully discussion based on our understanding and analysis of limited information of COVID-19. The consensus highlighted a multidisciplinary team diagnostic model with assessment of the balance between risks and benefits prior to treatment, individualizing satisfaction of patients’ medical needs, and acceptability in ethics and patients’ socio-economic conditions.

Industrial wireless sensor networks have been widely deployed in many industrial systems. The main communication paradigm of such systems, known as convergecast, is to converge sensing data to a centralized manager. The rapid and reliable data convergecast is essential to the industrial production. Multiple radio interfaces on a network device and convergecast scheduling algorithms can effectively reduce convergecast delay. Existing works confine to the convergecast based on linear- and tree-based routing. Compared to the two routing schemes, graph routing is more reliable. Although the graph routing gains more popularity in industrial networks due to its better reliability, few works have addressed its temporality performance. On the other hand, the number of radio interfaces also impacts on the convergecast delay. In this paper, we present a holistic framework to solve how to use multiple radio interfaces to converge data. First, we propose a convergecast scheduling algorithm for industrial wireless sensor networks with multiple radio interfaces. Second, based on our proposed scheduling algorithm, we propose an optimal algorithm and a fast heuristic algorithm to minimize the number of radio interfaces under the temporality constraint of industrial production. Evaluations show that all our algorithms perform closely to the optimal solution.

Background Pseudomonas aeruginosa (P. aeruginosa) is a major Gram-negative pathogen, which has been reported to result in high mortality. We aim to investigate the prognostic value and optimum cut-off point of time-to-positivity (TTP) of blood culture in children with P. aeruginosa bacteremia. Methods From August 2014 to November 2018, we enrolled the inpatients with P. aeruginosa bacteremia in a 1500-bed tertiary teaching hospital in Chongqing, China retrospectively. Receiver operating characteristic (ROC) analysis was used to determine the optimum cut-off point of TTP, and logistic regression were employed to explore the risk factors for in-hospital mortality and septic shock. Results Totally, 52 children with P. aeruginosa bacteremia were enrolled. The standard cut-off point of TTP was18 h. Early TTP (≤18 h) group patients had remarkably higher in-hospital mortality (42.9% vs 9.7%, P = 0.014), higher incidence of septic shock (52.4% vs12.9%, P = 0.06), higher Pitt bacteremia scores [3.00 (1.00–5.00) vs 1.00 (1.00–4.00), P = 0.046] and more intensive care unit admission (61.9% vs 22.6%, P = 0.008) when compared with late TTP (> 18 h) groups. Multivariate analysis indicated TTP ≤18 h, Pitt bacteremia scores ≥4 were the independent risk factors for in-hospital mortality (OR 5.88, 95%CI 1.21–21.96, P = 0.035; OR 4.95, 95%CI 1.26–27.50, P = 0.024; respectively). The independent risk factors for septic shock were as follows: TTP ≤18 h, Pitt bacteremia scores ≥4 and hypoalbuminemia (OR 6.30, 95%CI 1.18–33.77, P = 0.032; OR 8.15, 95%CI 1.15–42.43, P = 0.014; OR 6.46, 95% CI 1.19–33.19 P = 0.031; respectively). Conclusions Early TTP (≤18 hours) appeared to be associated with worse outcomes for P. aeruginosa bacteremia children.

Purpose To compare 3D liver acceleration volume acquisition (LAVA) and digital subtraction angiography (DSA) for evaluating the presence of accessory hepatic veins (AHV) in Budd-Chiari syndrome (BCS). Materials and Methods This was a retrospective study in 228 patients with BCS who underwent 3.0T magnetic resonance imaging (MRI) with the 3D LAVA sequence. Two reviewers noted AHV: openings located in the inferior vena cava (IVC), caliber, and the angle of entering into the IVC. MRI results were compared to DSA. Kappa statistics were calculated to quantify intrareader variability in detecting AHVs. Results On MRI, 63 patients demonstrated no AHV on LAVA images, 70 had one AHV, 62 had two AHVs, 26 patients had three AHVs, six patients had four AHVs, and one patient had five AHVs (P < 0.05 vs. DSA). The mean caliber of the AHVs was 8.3 ± 4.0 mm compared to 9.9 ± 3.2 for DSA (P < 0.001). Among the 301 AHVs, there were 140 with acute angles (46.5%), 71 with right angles (23.6%), and 90 with obtuse angles (29.8%). The prevalence of AHVs on DSA was 54.8% (125/228), while MRI demonstrated 301 AHVs in 165 patients, for a prevalence of 72.4% (165/228) compared to 54.8% for DSA (P = 0.001). The two methods were concordant in only 116/228 (50.9%) patients. The kappa coefficient demonstrated good intrareader consistency for all documented MRI findings of AHVs (κ = 0.626 for caliber and κ = 0.65 for angles). Conclusion More AHVs were visible on MRI LAVA sequences than on conventional DSA. Level of Evidence: 4 J. Magn. Reson. Imaging 2017;45:401–409.

The authors regrets that there is a typo error on the Abbreviation section of their published paper. "Area under the curve" should have been abbreviated to "AUC" instead of "A". The authors have requested that this be noted. The original article has been corrected.

One key issue in designing battery-powered wireless sensor networks is to properly control the energy consumption of the sensor nodes in order to prolong their operation time (i.e. lifetime ). In this article, we present a real-life application of wireless sensor networks in trains to monitor the goods conditions in a long-distance transportation. We study the wireless sensor network deployment problem in developing a monitoring system with the goal of maximizing the network lifetime under constraints derived from the real application scenario. The key technical problem to solve is to determine the sensor placement and the transmission level for each sensor node, as well as the appropriate number of sensor nodes. We first formulate the problem with a realistic discrete power model as a mixed integer linear programming problem. Then, a two-step efficient deployment heuristic is proposed to satisfy these constraints step by step. The evaluation results indicate that the proposed heuristic performs almost the same as the optimal mixed integer linear programming solution. Moreover, the wireless sensor network with appropriate number of nodes can improve its lifetime up to 10.6% for a train with 80 boxcars. We also discussed a tested experiment in a laboratory environment, as well as the real implementation of the whole monitoring system.

Up till now, the high penetration of intermittent distributed generation (DG) has posed great challenges to the planning and operation of the grid. To achieve the best balance between the economic cost and the acceptable capacity of DG, this paper proposes a new integrated planning method of active distribution network (ADN) while considering decentralized voltage control. The technical framework and control strategy of voltage control system are set up. An integrated planning model under the constraint of maintaining voltage acceptable is implemented, whose objectives are comprehensive cost minimization and clean energy utilization maximization. The simulations are conducted using the Multi-objective Differential Evolution Algorithm (MODE). IEEE 33-node test feeder is employed with 4 DGs participating in the voltage control. The results demonstrate that the proposed approach is able to connect larger distributed generators and improve distribution network's economic benefits while maintaining voltage within the statutory limits.

Compared to electric vehicle (EV) charging mode, battery swapping mode can realize concentrated and orderly charging. Therefore battery swapping stations (BSS) can participate in the demand side management (DSM) as an integrated form. In this context, a new method to plan the capacity and location of BSS for EV, considering DSM, is proposed in this paper. Firstly, based on the original charging power of BSS with the rule of “First-In First-Out”, a bi-level optimal configuration model of BSS, in which net profit of BSS is maximized in the upper model and operating cost of Distribution Company is minimized in the lower model, is developed to decide the rated power, number of batteries, contract pricing and dispatched power of BSS for DSM. Then, the optimal locating model of BSS with the objective of minimizing network loss is built. A mesh adaptive direct search algorithm with YALMIP toolbox is applied to optimize the bi-level model. Simulation calculation was carried on IEEE-33 nodes distribution system and the results show that participating in DSM can improve the economic benefits of both BSS and distribution network and promote the consumption of distributed generation, verifying the feasibility and effectiveness of the proposed method.

With the rich in resources of solar energy and rapidly development of the new energy resources-based generation, the maximization of photovoltaic (PV) generation consumption has been paid much attention to. High voltage problem is one of the major limits to high penetration of PV station connected to power grid. Several voltage control strategies are proposed to improve voltage profile. An optimization method is proposed for computing the maximum penetration level of PV, taking active voltage regulation into account. Computer simulations have been performed on a 33-nodes distribution system to demonstrate the effectiveness of the proposed voltage control schemes at different operating conditions in increasing the maximum power generation of PV.

Up till now, the high penetration of intermittent distributed generation (DG) has posed great challenges to the planning and operation of the grid. To achieve the best balance between economic cost and acceptable capacity of DG, this paper proposes a new integrated planning method of the active distribution network while considering voltage control cost. Firstly, characteristics of decentralized and centralized voltage control methods were analyzed. The technical frameworks, voltage control strategies and economical models of different voltage control systems were put forward. Then, an integrated planning model with objectives to minimize the comprehensive cost and maximize clean energy utilization under the constraint of maintaining acceptable voltage was implemented. Simulations were conducted using the Multi-objective Differential Evolution Algorithm (MODE). IEEE 33-bus test systems were employed to verify the effectiveness of the proposed method. The results demonstrate that the proposed approach is able to connect larger distributed generators and decrease the economic cost of Distribution Network Operators while maintaining voltage within the statutory limits.

To observe the effects of p38 mitogen activated protein kinase (MAPK) inhibitor SB203580 by intrathecal injection on the pain behavior and the spinal proinflammatory cytokines in a rat model of bone cancer pain induced by breast cancer cells. Eleven rats were used to establish the models of bone cancer pain, six rats were treated by intrathecal SB203580 injection, and the other 5 were as the controls. The paw withdrawal latency (PWL), histology and the spinal levels of IL-1β and TNF-α were detected. All the 11 rats presented evident bone destruction and thermal hyperalgesia after intra-tibial injection of breast cancer cells. No effect of SB203580 on the bone destruction was observed. However, following intrathecal injection of SB203580, the left PWLs (12.12 ± 1.26 s at 16 days and 12.99 ± 1.65 s at 19 days) were significant higher than that of controls (9.05 ± 1.08 s at 16 days and 8.55 ± 1.60 s at 19 days), P < 0.05. Meanwhile, intrathecal injection of SB203580 evidently reduced the levels of spinal IL-1β and TNF-α. Intrathecal injection of SB203580 in a rat model of bone cancer pain cannot prevent the tibial destruction but significantly depress the thermalgia sensitivity, which might result from inhibiting intracellular p38 MAPK signaling transduction, and thereby reducing the release of the proinflammatory cytokines.

The integration of a high penetration of intermittent distributed generation (DG) poses challenges to the planning and operation of the grid. In order to increase the acceptable capacity of DG, this paper researches on the sizing of DG based on active operation. After the analysis of several scenarios, a technical framework of secondary voltage control system is set up. It coordinates day-ahead control with real-time control. A simulation method is put forward. A sizing optimization model of run-of-river small hydro power is built. The minimal loss of distribution network and maximal clean energy generation ratio are taken as the objective functions under constraints of qualified voltage level. The simulation is based on the integration of operation and planning. By taking 33 nodes distribution system with DG as case study, analysis is carried out using multi-objective differential evolution algorithm. The effectiveness and applicability of the model and algorithm are manifested.

Primary pulmonary diffuse large B-cell lymphoma (PPDLBCL) directly arising from lung tissue is extremely rare. It may usually be misdiagnosed as inflammation including pulmonary tuberculosis, even lung cancer, because its clinical symptoms and signs are often nonspecific. The final diagnosis usually depends on lung biopsy. Herein, we report a case of PPDLBCL and review of diagnosis of this disease, particularly in radiology. A 44-year-old man presented with cough, sputum, and intermittent chest pain for 4 weeks. Multiple radiological examinations showed an irregular mass in the right upper lobe with ground-glass opacities around it and air-filled bronchi in the consolidation. Fluorodeoxyglucose (FDG) positron emission tomography/computed tomography-magnetic resonance imaging (MRI) detected positive FDG uptake, and diffusion-weighted imaging indicated abnormal hyperintension in the lesion. Inflammation was suspected, but malignance cannot be excluded. Finally, ultrasound-guided fine-needle aspiration cytology was performed for histological examination and definitive diagnosis yielded lymphomatous cells infiltration in the right upper lobe. This report emphasizes the significance of multimodality radiological examinations. Multimodality imaging contributes to proper diagnosis, staging, and management of lymphomas.

It poses high requirements for the calculation speed and the precision of the solving method when we consider the large-scale transmission expansion planning (TEP) problems. Therefore, combined with the respective characteristics of EDA (Distribution of Estimation Algorithm) and DE (Differential Evolution algorithm), this paper puts forward a new hybrid EDA/DE algorithm for large-scale TEP problems. Meanwhile, it improves the updating mechanism of probabilistic model of EDA based on the characteristics of the TEP problems. Considering the investments of grid company, the new energy incentive politics and network security constraints, this paper proposes a multi-objective static planning model for the TEP considering wind power penetration, which takes the comprehensive cost, the wind curtailment and the risk value into consideration. Finally, a specific example is applied in this paper to verify the applicability and effectiveness of the proposed model and algorithm.

Recently, energy harvesting has been emerging as a promising technique to prolong the lifetime for wireless sensor nodes. Most existing efforts address the design of energy harvesting and sensor node subsystem separately or ignore some real-world constraints. In this paper, we study how to codesign the two subsystems and how to jointly manage energy harvesting, storage, and usage. We first propose a novel system architecture for energy harvesting which employs several supercapacitors to eliminate the conflicts on charging and discharging among different system components. Then, we present a method to schedule their charging and discharging, which is proved to be able to guarantee zero waste of the harvested energy if the battery is not full. Third, we propose an optimal algorithm to minimize different components’ capacity and two heuristic algorithms to maximize the system reward. We conduct extensive experiments based on real-life data traces. Results show that the proposed system architecture can harvest more energy compared to the state of the art, and the capacity optimization algorithm can choose the most suitable size for each system component.

This paper presents a centralized coordinated voltage control method for active distribution network to solve off-limit problem of voltage after incorporation of distributed generation (DG). The proposed method consists of two parts, it coordinated primal-dual interior point method-based voltage regulation schemes of DG reactive powers and capacitors with centralized on-load tap changer (OLTC) controlling method which utilizes system’s maximum and minimum voltages, to improve the qualified rate of voltage and reduce the operation numbers of OLTC. The proposed coordination has considered the cost of capacitors. The method is tested using a radial edited IEEE-33 nodes distribution network which is modelled using MATLAB.

Cascading trips caused by flow transferring are crucial for lots of well-known blackouts. For a power system with heavy load flow, once there is a fault, the system might suffer flow transferring after the fault clearing. However, for relays, they cannot know the sensing overcurrent is caused by internal faults or flow transferring. The relays will trip the overcurrent after the predefined time delay, which might result in flow transferring again and worsen the system state. Therefore, if relays pickup due to flow transferring, the back-up relay should be blocked until the thermal limit of the line reaches. In this paper, Flow Transferring Relativity Factor (FTRF) is suggested to estimate the flow distribution after a line is tripped. Moreover, based on the relationship of node injection and branch currents, the impact of transient period on the flow distribution is analyzed. Finally, a flow transferring identification algorithm is presented to distinguish flow transferring from internal fault caused by fault clearing. The simulation results of 10-generator 39-bus New England system show that the proposed flow transferring identification algorithm works well.

In this paper, a cost-benefit analysis based optimal planning model of battery energy storage system (BESS) in active distribution system (ADS) is established considering a new BESS operation strategy. Reliability improvement benefit of BESS is considered and a numerical calculation method based on expectation is proposed for simple and convenient calculation of system reliability improvement with BESS in planning phase. Decision variables include both configuration variables and operation strategy control variables. In order to prevent the interaction between two types of variables and enhance global search ability, intelligent single particle optimizer (ISPO) is adopted to optimize this model. Case studies on a modified IEEE benchmark system verified the performance of the proposed operation strategy and optimal planning model of BESS.