A risk assessment model of power system cascading failure, considering the impact of ambient temperature

2015 ◽  
pp. 197-202
Keyword(s):  
Risk Assessment ◽  
Power System ◽  
Ambient Temperature ◽  
Assessment Model ◽  
Cascading Failure ◽  
Risk Assessment Model ◽  
The Impact

Power System Cascading Failure Risk Assessment Model Based on Graph Theory

2014 ◽  
Vol 496-500 ◽  
pp. 2844-2847
Author(s):  
Fu Chao Zhang ◽  
Jia Dong Huang
Keyword(s):  
Risk Assessment ◽  
Power System ◽  
Large Scale ◽  
Social Impact ◽  
Assessment Model ◽  
Levels Of Analysis ◽  
Economic Losses ◽  
Cascading Failure ◽  
Risk Assessment Model ◽  
Failure Risk

In recent years, large-scale power blackouts occur frequently in power system, resulting in extremely serious economic losses and social impact [. Scholars from various countries have made various levels of analysis on the causes of widespread blackouts from different angles [2-.The results show that most of the fault are caused by the cascading failure, and the linkage and relevance between failures are typical of such events. Accordingly, to strengthen the analysis of cascading has important significances on preventing the occurrence of large-scale power blackouts.

Leveraging HCA Results in an Advanced Pipeline Risk Assessment Model

2014 ◽  
Author(s):  
Otto Huisman ◽  
Ricardo Almandoz ◽  
Thomas Schuster ◽  
Adriana Andrade Caballero ◽  
Leonardo Martinez Forero
Keyword(s):  
Risk Assessment ◽  
American Petroleum Institute ◽  
Assessment Model ◽  
Mitigation Measures ◽  
South American ◽  
Risk Assessment Model ◽  
Industry Standards ◽  
Management Approaches ◽  
American Society ◽  
The Impact

Pipeline risk analysis is a common step carried out by operators in their overall Pipeline Integrity Management Process. There is a growing realization among operators of the need to adopt more proactive risk management approaches. This has brought about increased demand for more quantitative models to support risk reduction decision-making. Consequences of failure are a key component of these models where enhanced quantitative approaches can be deployed. Impacts to the environment and upon populations are key issues which both operators and regulatory bodies seek to minimize. Pipeline risk models and High Consequence Area (HCA) analyses play an increasingly important role in this context by allowing operators to identify a range of potential scenarios and the relative impact to receptors based upon the best available data sources. This paper presents the process and results of an HCA analysis project carried out by ROSEN for a major South American state-owned pipeline operator (hereafter referred to as ‘the Client’). This analysis was implemented using automated GIS processing methods and includes HCA analyses for approximately 2354 km of pipeline. The analysis was based on industry standards for both liquid and gas pipelines (i.e. American Petroleum Institute (API) and American Society of mechanical Engineers (ASME)), but customized for the specific needs of the Client and the South American geographical context. A key use for the results of this analysis is to serve as input for the pipeline risk assessment model jointly developed by ROSEN Integrity Solutions, MACAW Engineering and the Client. The methodology for development of this model is briefly discussed, and operational uses of HCA results are illustrated. The benefits of this project include, but are not limited to, identifying areas that could be severely impacted should a pipeline failure occur, being able to assess the risk profile of credible threats in HCAs, but also being able to prioritize preventative and mitigation measures at HCAs to either reduce the likelihood of failure or the impact of failure upon various receptors.

A Validated Risk Model for Prediction of Early Readmission in Patients with Hepatic Encephalopathy

2018 ◽  
Vol 17 (5) ◽  
pp. 0-10
Author(s):  
Andrew J. Kruger ◽  
Fasika Aberra ◽  
Sylvester M. Black ◽  
Alice Hinton ◽  
James Hanje ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Hepatic Encephalopathy ◽  
High Risk ◽  
Risk Model ◽  
Cox Regression ◽  
Low Risk ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Early Readmission ◽  
The Impact

Introduction and aim. Hepatic encephalopathy (HE) is a common complication in cirrhotics and is associated with an increased healthcare burden. Our aim was to study independent predictors of 30-day readmission and develop a readmission risk model in patients with HE. Secondary aims included studying readmission rates, cost, and the impact of readmission on mortality. Material and methods. We utilized the 2013 Nationwide Readmission Database (NRD) for hospitalized patients with HE. A risk assessment model based on index hospitalization variables for predicting 30-day readmission was developed using multivariate logistic regression and validated with the 2014 NRD. Patients were stratified into Low Risk and High Risk groups. Cox regression models were fit to identify predictors of calendar-year mortality. Results. Of 24,473 cirrhosis patients hospitalized with HE, 32.4% were readmitted within 30-days. Predictors of readmission included presence of ascites (OR: 1.19; 95% CI: 1.06-1.33), receiving paracentesis (OR: 1.43; 95% CI: 1.26-1.62) and acute kidney injury (OR: 1.11; 95% CI: 1.00-1.22). Our validated model stratified patients into Low Risk and High Risk of 30-day readmissions (29% and 40%, respectively). The cost of the first readmission was higher than index admission in the 30-day readmission cohort ($14,198 vs. $10,386; p-value < 0.001). Thirty-day readmission was the strongest predictor of calendar-year mortality (HR: 4.03; 95% CI: 3.49-4.65). Conclusions. Nearly one-third of patients with HE were readmitted within 30-days, and early readmission adversely impacted healthcare utilization and calendar-year mortality. With our proposed simple risk assessment model, patients at high risk for early readmissions can be identified to potentially avert poor outcomes.

scholarly journals Finding a rIsk assessmeNt moDel for thromboembolic events in hospItalized Cancer pATiEnts: the INDICATE study running title: thromboembolism in hospitalized cancer patients

2021 ◽  
Author(s):  
Federico Nichetti ◽  
Francesca Ligorio ◽  
Giulia Montelatici ◽  
Luca Porcu ◽  
Emma Zattarin ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Cancer Patients ◽  
Predictive Value ◽  
Assessment Model ◽  
Primary Study ◽  
Low Grade ◽  
Risk Assessment Model ◽  
Thromboembolic Events ◽  
Study Objective ◽  
The Impact

Abstract Background: Hospitalized cancer patients are at increased risk for Thromboembolic Events (TEs). As untailored thromboprophylaxis is associated with hemorrhagic complications, the definition of a risk-assessment model (RAM) in this population is needed. Objectives: INDICATE was an observational study enrolling hospitalized cancer patients, with the primary objective of assessing the Negative Predictive Value (NPV) for TEs during hospitalization and within 45 days from discharge of low-grade Khorana Score (KS=0). Secondary objectives were to assess KS Positive Predictive Value (PPV), the impact of TEs on survival and the development of a new RAM. Materials and Methods: Assuming 7% of TEs in KS=0 patients as unsatisfactory percentage and 3% of as satisfactory, 149 patients were needed to detect the favorable NPV with one-sided a= 0.10 and power=0.80. Stepwise logistic regression was adopted to identify variables included in a new RAM.Results: Among 535 enrolled patients, 153 (28.6%) had a KS=0. The primary study objective was met: 29 (5.4%) TEs were diagnosed, with 7 (4.6%) cases in the KS=0 group (NPV=95.4%, 95%CI: 90.8-98.1%; one-sided p=0.084). However, the PPV was low (5.7%, 95%CI: 1.9-12.8%); a new RAM based on albumin (OR 0.34, p=0.003), log(LDH) (OR 1.89, p=0.023) and presence of vascular compression (OR 5.32, p<.001) was developed and internally validated. Also, TEs were associated with poorer OS (median, 5.7 vs 24.8 months, p <.001).Conclusion: INDICATE showed that the KS has a good NPV but poor PPV for TEs in hospitalized cancer patients. A new RAM was developed, and deserves further assessment in external cohorts.

scholarly journals A risk assessment model of WSMC projects under emergencies

2021 ◽  
Author(s):  
Xiaosheng Wang ◽  
Wei Li ◽  
Haiying Guo ◽  
Ran Li
Keyword(s):  
Risk Assessment ◽  
Risk Index ◽  
Water Saving ◽  
Risk Tolerance ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Water Users ◽  
Theoretical Support ◽  
Management Contract ◽  
The Impact

Abstract As a novel market-based water-saving mechanism, the Water Saving Management Contract (WSMC) project faces interruption risk caused by emergencies like the coronavirus disease-2019 (COVID-19) pandemic. An interruption risk assessment model of WSMC projects is established through a quantitative evaluation of the impact of emergencies on water users based on input-output theory. First, the concept of the interruption risk index (IRI) is defined as a function of the duration of enterprise shutdown (DES). Second, the DES is divided into two parts: the duration caused by COVID-19 and the that under other types of emergencies. Third, the risk tolerance threshold is given to estimate the interruption result, and its different consequences are discussed. Finally, a WSMC project in China is taken as a case study, and its interruption risks are analysed. The results show that the IRIs of this WSMC in both 2020 and 2021 are theoretically greater than the risk tolerance thresholds, and the high pandemic prevention standards and conservative pandemic estimates are the main reasons for the above results. The model established in this study provides a reference for WSMC participants to deal with emergencies and provides the theoretical support for the extension of the WSMC.

Risk Assessment Model of Cascading Failures in Power System Based on Danger Lines

2013 ◽  
Vol 373-375 ◽  
pp. 1349-1352
Author(s):  
Fu Chun Zhang ◽  
Jia Dong Huang
Keyword(s):  
Power System ◽  
Power Flow ◽  
Probability Model ◽  
Power Line ◽  
Assessment Model ◽  
Cascading Failure ◽  
Bus Voltage ◽  
Line Overload ◽  
The Impact ◽  
Load Margin

Based on the theory of risk, a new model is proposed for cascading failure in power system. According to fault factor of power line itself and the impact of real-time power flow, the branch outage probability model is established, and then the probability of cascading failure can be calculated. The severity function of cascading failure is defined by the analysis of fault consequences including the decrease of load margin, bus voltage offset and power line overload. The use of the set of danger lines which is judged by the amount of active power increase and load margin of power line can speed the search of fault mode. The simulation and analysis of IEEE 39-node proves the effectiveness of the method.

Impact of Venous Thromboembolism (VTE) Prophylaxis and Risk Stratification with the Caprini Model in Hospitalized Patients with Cancer

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 364-364
Author(s):  
Joshua M Ruch ◽  
Hsou M Hu ◽  
Vinita Bahl ◽  
Suman L. Sood
Keyword(s):  
Risk Assessment ◽  
High Risk ◽  
Conflicts Of Interest ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Medical Patients ◽  
Vte Prophylaxis ◽  
Patients With Cancer ◽  
Pharmacologic Prophylaxis ◽  
The Impact

Abstract Abstract 364 Introduction: VTE is a common complication in hospitalized medical patients and the role of pharmacologic anticoagulation prophylaxis is well-established. Patients with active malignancy are at higher risk for VTE during hospitalization. However, VTE prophylaxis is underutilized in these patients due to many real and perceived contraindications to prophylaxis. To aid clinicians in determining VTE risk and guide choice of prophylaxis, our institution adopted the Caprini risk assessment model (Ann Surg, 2010; 251[2]:344–50), based on clinical factors such as age, comorbidities, and recent surgery. Our primary objective was to assess adherence to recommended VTE prophylaxis in hospitalized medical patients with solid tumors, hematological malignancies, and bone marrow transplant (BMT) patients in comparison to general medical (GM) patients, and the impact of recommended prophylaxis use on VTE outcomes. Secondary objectives were to evaluate the distribution of Caprini risk scores and the utility of the Caprini risk assessment model for guiding prophylaxis in this population. Methods: Patients admitted to the hematology/oncology (HO; oncology, malignant hematology, and BMT) and GM inpatient services at the University of Michigan between July 1, 2009 to December 31, 2011 were included in the study. After IRB approval, patient information was extracted from the electronic medical record (EMR). A point-scoring method based on the Caprini risk assessment model was used to calculate VTE risk at admission. A score of 3–4 was high risk and ≥ 5 highest risk for VTE. Type of VTE prophylaxis and VTE rate were determined. Recommended prophylaxis was 5000 units TID SQ heparin, 30–40 mg SQ enoxaparin, or 2.5 mg SQ fondaparinux, ± sequential compression devices (SCDs). Pharmacological prophylaxis administration was verified in the EMR. VTE is defined as deep venous thrombosis (DVT) or pulmonary embolism (PE) occurring during hospitalization or within 90 days, confirmed by Doppler, CT or V/Q scan. Adherence was defined as the percentage of patients at high or highest risk for VTE with a length of stay ≥ 2 days who received guideline recommended prophylaxis within 2 days of admission. Patients with a contraindication to prophylaxis were excluded. A retrospective cohort study was performed. Chi-squared test was used to test differences in proportions and Cochran-Armitage test for trends. Results: 4300 patients were admitted to HO and 18,347 to GM services. Compared to GM patients (86.8%), the rate of adherence to recommended VTE prophylaxis was similar for oncology (87.6%), hematology (85.4%), and lower (45.6%) for BMT patients (p<0.0001). The overall VTE rate on HO services was 2.77%. Compared with 1.45% in GM, VTE rate was 3.02% in oncology (p=0.070), 2.01% in hematology (p=0.220), and 3.61% for BMT (p=0.001). Over half (51.3%) of VTE in HO patients occurred in patients who did not receive pharmacologic prophylaxis. In HO patients with a VTE, ordered prophylaxis included 16.0% combined pharmacological and SCD, 32.8% pharmacological alone, 32.8% SCD alone, and 18.5% none. Use of combined or pharmacologic prophylaxis alone was non-significantly increased in the non-VTE HO patients. By the Caprini risk assessment model, 33.3% of all patients on HO services were high and 62.2% highest risk, with less oncology (p=0.0001) and more BMT (p=0.0003) patients classified as high or highest risk. VTE rate in HO patients rose as Caprini risk score increased: score (n, % with VTE) 0–1 (23, 4.35%,); 2 (169, 0.59%); 3–4 (1434, 1.67%); 5–6 (1691, 2.90%); 7–8 (745, 3.76%); and 9 (238, 6.72%), p<0.0001 for trend. Conclusions: Adherence to recommended VTE prophylaxis was high in medical patients with cancer, resulting in low overall rates of VTE during and following discharge. The majority of patients with VTE did not receive recommended pharmacologic prophylaxis. Most VTE occurred in patients at highest risk (Caprini risk assessment score ≥ 5), with a trend to higher VTE rate as individual score increased. These data suggest that the individual Caprini score may provide more detailed VTE risk assessment and may help inform the need for prophylaxis despite perceived relative contraindications in this high risk cancer population. Further study is needed to understand the barriers to ordering VTE prophylaxis in this population and encourage increased prophylaxis use. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Online Operation Risk Assessment of the Wind Power System of the Convolution Neural Network (CNN) Considering Multiple Random Factors

Processes ◽  
2019 ◽  
Vol 7 (7) ◽  
pp. 464
Author(s):  
Qingwu Gong ◽  
Si Tan ◽  
Yubo Wang ◽  
Dong Liu ◽  
Hui Qiao ◽  
...  
Keyword(s):  
Neural Network ◽  
Risk Assessment ◽  
Power System ◽  
Wind Power ◽  
Convolution Neural Network ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Online Application ◽  
Wind Power System ◽  
Operation Risk

In order to solve the problem of the inaccuracy of the traditional online operation risk assessment model based on a physical mechanism and the inability to adapt to the actual operation of massive online operation monitoring data, this paper proposes an online operation risk assessment of the wind power system of the convolution neural network (CNN) considering multiple random factors. This paper analyzes multiple random factors of the wind power system, including uncertain wind power output, load fluctuations, frequent changes in operation patterns, and the electrical equipment failure rate, and generates the sample data based on multi-random factors. It uses the CNN algorithm network, offline training to obtain the risk assessment model, and online application to obtain the real-time online operation risk state of the wind power system. Finally, the online operation risk assessment model is verified by simulation using the standard network of 39 nodes of 10 machines New England system. The results prove that the risk assessment model presented in this paper is more rapid and suitable for online application.

scholarly journals The Study on Lightning Disaster Risk Assessment Model of 10kV Overhead Line

2018 ◽  
Vol 173 ◽  
pp. 01008
Author(s):  
Song wei ◽  
Wang Yanfeng ◽  
Wang shuanghu
Keyword(s):  
Risk Assessment ◽  
Social Impact ◽  
Distribution Network ◽  
Weight Ratio ◽  
Disaster Risk ◽  
Assessment Model ◽  
Theoretical Research ◽  
Risk Assessment Model ◽  
Overhead Line ◽  
The Impact

Taking all kinds of affecting factors into account, the 10kV overhead line of distribution network lighting disaster risk is studied. Historical hidden fault, line equipment, topography, climatic conditions and social impact are selected as key factors of damage and the impact. The correlation among the factors and the weight ratio of each factor were studied. The risk assessment model of 10kV distribution network overhead line was established by multi-factor, hierarchical classification assessment method. It solves the evaluation index insufficient problem of the single factor as the evaluation condition, and provides the theoretical research and practical support to the 10kV overhead line reconstruction and the lightning prevention. The reliability and effectiveness of the research results have been proved by practical application in distribution network operation and maintenance control.

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