Chaotic dynamic behavior analysis and control for a financial risk system

According to the risk management process of financial markets,a financial risk dynamic system is constructed in this paper.Through analyzing the basic dynamic properties,we obtain the conditions for stability and bifurcation of the system based on Hopf bifurcation theory of nonlinear dynamic systems.In order to make the system＇s chaos disappear,we select the feedback gain matrix to design a class of chaotic controller.Numerical simulations are performed to reveal the change process of financial market risk.It is shown that,when the parameter of risk transmission rate changes,the system gradually comes into chaos from the asymptotically stable state through bifurcation.The controller can then control the chaos effectively.

Risk Factors of Depression Screened by Two-Sample Mendelian Randomization Analysis:A Systematic Review

Objective This study explored the potentially modifiable factors for depression and major depressive disorder(MDD)from the MR-Base database and further evaluated the associations between drug targets with MDD.Methods We analyzed two-sample of Mendelian randomization(2SMR)using genetic variant depression(n=113,154)and MDD(n=208,811)from Genome-Wide Association Studies(GWAS).Separate calculations were performed with modifiable risk factors from MR-Base for 1,001 genomes.The MR analysis was performed by screening drug targets with MDD in the DrugBank database to explore the therapeutic targets for MDD.Inverse variance weighted(IVW),fixed-effect inverse variance weighted(FE-IVW),MR-Egger,weighted median,and weighted mode were used for complementary calculation.Results The potential causal relationship between modifiable risk factors and depression contained 459 results for depression and 424 for MDD.Also,the associations between drug targets and MDD showed that SLC6A4,GRIN2A,GRIN2C,SCN10A,and IL1B expression are associated with an increased risk of depression.In contrast,ADRB1,CHRNA3,HTR3A,GSTP1,and GABRG2 genes are candidate protective factors against depression.Conclusion This study identified the risk factors causally associated with depression and MDD,and estimated 10 drug targets with significant impact on MDD,providing essential information for formulating strategies to prevent and treat depression.

Exploring the impacts of major events on the systemic risk of the international energy market

This study examines the systemic risk caused by major events in the international energy market(IEM)and proposes a management strategy to mitigate it. Using the tail-event driven network(TENET)method, this study constructed a tail-risk spillover network(TRSN) of IEM and simulated the dynamic spillover tail-risk process through the cascading failure mechanism. The study found that renewable energy markets contributed more to systemic risk during the Paris Agreement and the COVID-19pandemic, while fossil energy markets played a larger role during the Russia-Ukraine conflict. This study identifies systemically important markets(SM) and critical tail-risk spillover paths as potential sources of systemic risk. The research confirms that cutting off the IEM risk spillover path can greatly reduce systemic risk and the influence of SM. This study offers insights into the management of systemic risk in IEM and provides policy recommendations to reduce the impact of shock events.

Evaluating soil acidification risk and its effects on biodiversity–ecosystem multifunctionality relationships in the drylands of China

Background:Soil acidifcationn caused by anthropogenic activities may aft soil biochemical cydling,bidiversity,productivity,and multiple eosystem-related functions in drylands.However,to date,such information is lacking to support this hypothesis.Methods Based on a transect survey of 78 naturally assembled shrub communities,we caloulated acid deposition flux in Northwest China and evaluated its likely ecological ffets by testing three altemnative hypotheses,namely:.nidche complementarity,mass ratio,and vegetation quantity hypotheses Rao's quadratic entopy and community-weighted mean traits were employed to represent the complementary aspect of niche complementarity and mass ratio effects,respectively.Resulbs:We observed that in the past four decades,the concentrations of exchangeable base cations in soil in Northwest China have decreased significantly to the extent of having faced the risk of depletion,whereas changes in the calium carbonate content and pH of soil were not significant.Adid deposition primani ly increased the aboweground biomass and shrub density in shrublands but had no sigmificant effect on shrub richness and ecasystem multifunctionality(EMF),indicating that acid deposition had positive but weak ecological effects on dryland ecosystems.Community wd ghted mean of functional traits(representing the mass ratio hypothesis)correlated negatively with EMF,whereas both Rao's quadratic entropy(representing the niche complementarity hypothesis)and aboveground biomass(representing the vegetation quantity hypothesis)correlated positively but insignifcantly with EMF.These biodiversity-EMF relationships highlight the fragility and instability of drylands relative to forest ecasystems.Concuions:The findings from this study serve as important reference points to understand the ris of soil acidification in arid regions and its impacts on biodiversity-EMF relationships.

Systematic review of risk factors,prognosis,and management of colorectal signet-ring cell carcinoma

BACKGROUND Colorectal signet-ring cell carcinoma(CSRCC)is a rare clinical entity which accounts for approximately 1%of all colorectal cancers.Although multiple studies concerning this specific topic have been published in the past decades,the pathogenesis,associated risk factors,and potential implications on treatment are still poorly understood.Besides the low incidence,historically confusing histological criteria have resulted in confusing data.Nevertheless,the rising incidence of CSRCC along with relatively young age at presentation and associated dismal prognosis,highlight the actual interest to synthesize the known literature regarding CSRCC.AIM To provide an updated overview of risk factors,prognosis,and management of CSRCC.METHODS A literature search in the MEDLINE/PubMed database was conducted with the following search terms used:‘Signet ring cell carcinoma’and‘colorectal’.Studies in English language,published after January 1980,were included.Studies included in the qualitative synthesis were evaluated for content concerning epidemiology,risk factors,and clinical,diagnostic,histological,and molecular features,as well as metastatic pattern and therapeutic management.If possible,presented data was extracted in order to present a more detailed overview of the literature.RESULTS In total,67 articles were included for qualitative analysis,of which 54 were eligible for detailed data extraction.CSRCC has a reported incidence between 0.1%-2.4%and frequently presents with advanced disease stage at the time of diagnosis.CSRCC is associated with an impaired overall survival(5-year OS:0%-46%)and a worse stagecorrected outcome compared to mucinous and not otherwise specified adenocarcinoma.The systematic use of exploratory laparoscopy to determine the presence of peritoneal metastases has been advised.Surgery is the mainstay of treatment,although the rates of curative resection in CSRCC(21%-82%)are lower compared to those in other histological types.In case of peritoneal metastasis,cytoreductive surgery with hyperthermic intraperitoneal chemotherapy should only be proposed in selected patients.CONCLUSION CSRCC is a rare clinical entity most often characterized by young age and advanced disease at presentation.As such,diagnostic modalities and therapeutic approach should be tailored accordingly.

Risk-Balanced Routing Strategy for Service Function Chains of Cyber-Physical Power System Considering Cross-Space Cascading Failure

Cyber-physical power system(CPPS)has significantly improved the operational efficiency of power systems.However,cross-space cascading failures may occur due to the coupling characteristics,which poses a great threat to the safety and reliability of CPPS,and there is an acute need to reduce the probability of these failures.Towards this end,this paper first proposes a cascading failure index to identify and quantify the importance of different information in the same class of communication services.On this basis,a joint improved risk-balanced service function chain routing strategy(SFC-RS)is proposed,which is modeled as a robust optimization problem and solved by column-and-constraint generation(C-CG)algorithm.Compared with the traditional shortest-path routing algorithm,the superiority of SFC-RS is verified in the IEEE 30-bus system.The results demonstrate that SFC-RS effectively mitigates the risk associated with information transmission in the network,enhances information transmission accessibility,and effectively limits communication disruption from becoming the cause of cross-space cascading failures.

Actuality and underlying mechanisms of systemic immuneinflammation index and geriatric nutritional risk index prognostic value in hepatocellular carcinoma

This editorial contains comments on the article“Correlation between preoperative systemic immune inflammation index,nutritional risk index,and prognosis of radical resection of liver cancer”in a recent issue of the World Journal of Gastrointestinal Surgery.It pointed out the actuality and importance of the article and focused primarily on the underlying mechanisms making the systemic immuneinflammation index(SII)and geriatric nutritional risk index(GNRI)prediction features valuable.There are few publications on both SII and GNRI together in hepatocellular carcinoma(HCC)and patient prognosis after radical surgery.Neutrophils release cytokines,chemokines,and enzymes,degrade extracellular matrix,reduce cell adhesion,and create conditions for tumor cell invasion.Neutrophils promote the adhesion of tumor cells to endothelial cells,through physical anchoring.That results in the migration of tumor cells.Pro-angiogenic factors from platelets enhance tumor angiogenesis to meet tumor cell supply needs.Platelets can form a protective film on the surface of tumor cells.This allows avoiding blood flow damage as well as immune system attack.It also induces the epithelial-mesenchymal transformation of tumor cells that is critical for invasiveness.High SII is also associated with macro-and microvascular invasion and increased numbers of circulating tumor cells.A high GNRI was associated with significantly better progression-free and overall survival.HCC patients are a very special population that requires increased attention.SII and GNRI have significant survival prediction value in both palliative treatment and radical surgery settings.The underlying mechanisms of their possible predictive properties lie in the field of essential cancer features.Those features provide tumor nutrition,growth,and distribution throughout the body,such as vascular invasion.On the other hand,they are tied to the possibility of patients to resist tumor progression and development of complications in both postoperative and cancer-related settings.The article is of considerable interest.It would be helpful to continue the study follow-up to 2 years and longer.External validation of the data is needed.

Risk assessment of high-speed railway CTC system based on improved game theory and cloud model

Purpose-In order to solve the problem of inaccurate calculation of index weights,subjectivity and uncertainty of index assessment in the risk assessment process,this study aims to propose a scientific and reasonable centralized traffic control(CTC)system risk assessment method.Design/methodologylapproach-First,system-theoretic process analysis(STPA)is used to conduct risk analysis on the CTC system and constructs risk assessment indexes based on this analysis.Then,to enhance the accuracy of weight calculation,the fuzzy analytical hierarchy process(FAHP),fuzzy decision-making trial and evaluation laboratory(FDEMATEL)and entropy weight method are employed to calculate the subjective weight,relative weight and objective weight of each index.These three types of weights are combined using game theory to obtain the combined weight for each index.To reduce subjectivity and uncertainty in the assessment process,the backward cloud generator method is utilized to obtain the numerical character(NC)of the cloud model for each index.The NCs of the indexes are then weighted to derive the comprehensive cloud for risk assessment of the CTC system.This cloud model is used to obtain the CTC system's comprehensive risk assessment.The model's similarity measurement method gauges the likeness between the comprehensive risk assessment cloud and the risk standard cloud.Finally,this process yields the risk assessment results for the CTC system.Findings-The cloud model can handle the subjectivity and fuzziness in the risk assessment process well.The cloud model-based risk assessment method was applied to the CTC system risk assessment of a railway group and achieved good results.Originality/value-This study provides a cloud model-based method for risk assessment of CTC systems,which accurately calculates the weight of risk indexes and uses cloud models to reduce uncertainty and subjectivity in the assessment,achieving effective risk assessment of CTC systems.It can provide a reference and theoretical basis for risk management of the CTC system.

Climate Change-Related Disaster Risk Events in Togo: A Systematic Review

Togo is facing significant climate challenges that have profound consequences for its environment, economy, and population. This study provides an overview of various climate phenomena affecting Togo and highlights potential adaptation strategies. We used the inclusion and exclusion criteria (PRISMA) to search both French and English articles on climate change-related disaster risk events in Togo through Google Scholar, Directory of Open Access Journals (DOAJ), and PubMed databases using the keywords “Climate Change”, “Floods”, “Drought”, “Coastal erosion”, “High winds”, “Epidemy”, Heatwaves”, and “Air pollution”. Twenty-five articles from 2000-2023 were included in this study after applying different criteria. Droughts, floods, coastal erosion, food and crop productivity loss, heatwaves, spread of vector-borne diseases, air pollution, and high winds are among the climate phenomena discussed. These challenges are driven by climate change, altering precipitation patterns, increasing temperatures, and rising sea levels. Drought, floods, coastal erosion, loss of food and crop productivity, spread of vector-borne diseases, air pollution and heatwaves are the most climate risks experienced by Togo. Drought contributes to decreased plant cover, water scarcity, and changes in the water and energy balance. Floods cause property damage, health risks, and disruptions to livelihoods. Coastal erosion threatens coastal communities, infrastructure, and ecosystems. Adaptation strategies include early warning systems, improved water management, sustainable agriculture, urban and health planning, and greenhouse gas emissions reduction. Drought-resistant crops, mosquito control, and clean energy adoption are essential.

Mapping Climate Services for Disaster Risk Management: A Systematic Review and Research Gaps from a Policy Process Perspective

Climate services (CS) are crucial for mitigating and managing the impacts and risks associated with climate-induced disasters. While evidence over the past decade underscores their effectiveness across various domains, particularly agriculture, to maximize their potential, it is crucial to identify emerging priority areas and existing research gaps for future research agendas. As a contribution to this effort, this paper employs the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to review the state-of-the-art in the field of climate services for disaster risk management. A comprehensive search across five literature databases combined with a snowball search method using ResearchRabbit was conducted and yielded 242 peer-reviewed articles, book sections, and reports over 2013-2023 after the screening process. The analysis revealed flood, drought, and food insecurity as major climate-related disasters addressed in the reviewed literature. Major climate services addressed included early warning systems, (sub)seasonal forecasts and impact-based warnings. Grounded in the policy processes’ theoretical perspective, the main focus identified and discussed three prevailing policy-oriented priority areas: 1) development of climate services, 2) use-adoption-uptake, and 3) evaluation of climate services. In response to the limitations of the prevalent supply-driven and top-down approach to climate services promotion, co-production emerges as a cross-cutting critical aspect of the identified priority areas. Despite the extensive research in the field, more attention is needed, particularly pronounced in the science-policy interface perspective, which in practice bridges scientific knowledge and policy decisions for effective policy processes. This perspective offers a valuable analytical lens as an entry point for further investigation. Hence, future research agendas would generate insightful evidence by scrutinizing this critical aspect given its importance to institutions and climate services capacity, to better understand intricate facets of the development and the integration of climate services into disaster risk management.

Systematic Risk Analysis of Listed Financial Institutions from the Perspective of Complex Network

Based on the complex network theory,this paper studies the systemic financial risks in China’s financial market.According to the industry classification of the China Securities Regulatory Commission in 2012,the daily closing prices of 45 listed financial institutions are collected and the daily return rates of each financial institution are measured according to the logarithmic return rate calculation formula.In this paper,the risk spillover value ΔCoVaR is used to measure the contribution degree of each financial institution to systemic risk.Finally,the relationship between the risk spillover valueΔCoVaR and the node topology index of the risk transmission network is investigated by using a regression model,and some policy suggestions are put forward based on the regression results.

Correlation between preoperative systemic immune inflammation index, nutritional risk index, and prognosis of radical resection of liver cancer

BACKGROUND Radical surgery is the most commonly used treatment for hepatocellular carcinoma(HCC).However,the surgical effect remains not ideal,and prognostic evaluation is insufficient.Furthermore,clinical intervention is rife with uncertainty and not conducive to prolonging patient survival.AIM To explore correlations between the systemic immune inflammatory index(SII)and geriatric nutritional risk index(GNRI)and HCC operation prognosis.METHODS This retrospective study included and collected follow up data from 100 HCC.Kaplan–Meier survival curves were used to analyze the correlation between SII and GNRI scores and survival.SII and GNRI were calculated as follows:SII=neutrophil count×platelet count/lymphocyte count;GNRI=[1.489×albumin(g/L)+41.7×actual weight/ideal weight].We analyzed the predictive efficacy of the SII and GNRI in HCC patients using receiver operating characteristic(ROC)curves,and the relationships between the SII,GNRI,and survival rate using Kaplan–Meier survival curves.Cox regression analysis was utilized to analyze independent risk factors influencing prognosis.RESULTS After 1 year of follow-up,24 patients died and 76 survived.The area under the curve(AUC),sensitivity,specificity,and the optimal cutoff value of SII were 0.728(95%confidence interval:0.600-0.856),79.2%,63.2%,and 309.14,respectively.According to ROC curve analysis results for predicting postoperative death in HCC patients,the AUC of SII and GNRI combination was higher than that of SII or GNRI alone,and SII was higher than that of GNRI(P<0.05).The proportion of advanced differentiated tumors,tumor maximum diameter(5–10 cm,>10 cm),lymph node metastasis,and TNM stage III-IV in patients with SII>309.14 was higher than that in patients with SII≤309.14(P<0.05).The proportion of patients aged>70 years was higher in patients with GNRI≤98 than that in patients with GNRI>98(P<0.05).The 1-year survival rate of the SII>309.14 group(compared with the SII≤309.14 group)and GNRI≤98 group(compared with the GNRI>98 group)was lower(P<0.05).CONCLUSION The prognosis after radical resection of HCC is related to the SII and GNRI and poor in high SII or low GNRI patients.

Research on strategic risk identification method of equipment system development based on system dynamics

Strategic management of equipment system develop-ment must attach importance to effective strategic risk manage-ment.Aiming at the identification of strategic risk of equipment system development,firstly,the source of strategic risk of equip-ment system development is analyzed and classified.Based on this,a causal loop diagram of strategic risk of equipment sys-tem development based on system dynamics is established.The system dynamics analysis software Vensim PLE is used to carry out the risk influencing factors analysis,risk consequences ana-lysis,risk feedback loop identification and corresponding pre-control measures,and achieves a good risk identification effect.

Significant risk factors for intensive care unit-acquired weakness:A processing strategy based on repeated machine learning

BACKGROUND Intensive care unit-acquired weakness(ICU-AW)is a common complication that significantly impacts the patient's recovery process,even leading to adverse outcomes.Currently,there is a lack of effective preventive measures.AIM To identify significant risk factors for ICU-AW through iterative machine learning techniques and offer recommendations for its prevention and treatment.METHODS Patients were categorized into ICU-AW and non-ICU-AW groups on the 14th day post-ICU admission.Relevant data from the initial 14 d of ICU stay,such as age,comorbidities,sedative dosage,vasopressor dosage,duration of mechanical ventilation,length of ICU stay,and rehabilitation therapy,were gathered.The relationships between these variables and ICU-AW were examined.Utilizing iterative machine learning techniques,a multilayer perceptron neural network model was developed,and its predictive performance for ICU-AW was assessed using the receiver operating characteristic curve.RESULTS Within the ICU-AW group,age,duration of mechanical ventilation,lorazepam dosage,adrenaline dosage,and length of ICU stay were significantly higher than in the non-ICU-AW group.Additionally,sepsis,multiple organ dysfunction syndrome,hypoalbuminemia,acute heart failure,respiratory failure,acute kidney injury,anemia,stress-related gastrointestinal bleeding,shock,hypertension,coronary artery disease,malignant tumors,and rehabilitation therapy ratios were significantly higher in the ICU-AW group,demonstrating statistical significance.The most influential factors contributing to ICU-AW were identified as the length of ICU stay(100.0%)and the duration of mechanical ventilation(54.9%).The neural network model predicted ICU-AW with an area under the curve of 0.941,sensitivity of 92.2%,and specificity of 82.7%.CONCLUSION The main factors influencing ICU-AW are the length of ICU stay and the duration of mechanical ventilation.A primary preventive strategy,when feasible,involves minimizing both ICU stay and mechanical ventilation duration.

Risk Assessment of Deep-Water Horizontal X-Tree Installation

Due to the high potential risk and many influencing factors of subsea horizontal X-tree installation,to guarantee the successful completion of sea trials of domestic subsea horizontal X-trees,this paper established a modular risk evaluation model based on a fuzzy fault tree.First,through the analysis of the main process oftree down and combining the Offshore&Onshore Reliability Data(OREDA)failure statistics and the operation procedure and the data provided by the job,the fault tree model of risk analysis of the tree down installation was established.Then,by introducing the natural language of expert comprehensive evaluation and combining fuzzy principles,quantitative analysis was carried out,and the fuzzy number was used to calculate the failure probability of a basic event and the occurrence probability of a top event.Finally,through a sensitivity analysis of basic events,the basic events of top events significantly affected were determined,and risk control and prevention measures for the corresponding high-risk factors were proposed for subsea horizontal X-tree down installation.

Automatic detection of small bowel lesions with different bleeding risks based on deep learning models

BACKGROUND Deep learning provides an efficient automatic image recognition method for small bowel(SB)capsule endoscopy(CE)that can assist physicians in diagnosis.However,the existing deep learning models present some unresolved challenges.AIM To propose a novel and effective classification and detection model to automatically identify various SB lesions and their bleeding risks,and label the lesions accurately so as to enhance the diagnostic efficiency of physicians and the ability to identify high-risk bleeding groups.METHODS The proposed model represents a two-stage method that combined image classification with object detection.First,we utilized the improved ResNet-50 classification model to classify endoscopic images into SB lesion images,normal SB mucosa images,and invalid images.Then,the improved YOLO-V5 detection model was utilized to detect the type of lesion and its risk of bleeding,and the location of the lesion was marked.We constructed training and testing sets and compared model-assisted reading with physician reading.RESULTS The accuracy of the model constructed in this study reached 98.96%,which was higher than the accuracy of other systems using only a single module.The sensitivity,specificity,and accuracy of the model-assisted reading detection of all images were 99.17%,99.92%,and 99.86%,which were significantly higher than those of the endoscopists’diagnoses.The image processing time of the model was 48 ms/image,and the image processing time of the physicians was 0.40±0.24 s/image(P<0.001).CONCLUSION The deep learning model of image classification combined with object detection exhibits a satisfactory diagnostic effect on a variety of SB lesions and their bleeding risks in CE images,which enhances the diagnostic efficiency of physicians and improves the ability of physicians to identify high-risk bleeding groups.

Natural Disaster Risk Monitoring for Immovable Cultural Relics Based on Digital Twin

Natural disaster risk monitoring is an important task for disaster prevention and reduction.In the case of immovable cultural relics,however,the feedback mechanism,risk factors,monitoring logic,and monitoring indicators of natural disaster risk monitoring are complex.How to achieve intelligent perception and monitoring of natural disaster risk for immovable cultural relics has always been a focus and a challenge for researchers.Based on the analysis of the concepts and issues related to the natural disaster risk of immovable cultural relics,this paper proposes a framework for natural disaster risk monitoring for immovable cultural relics based on the digital twin.This framework focuses on risk monitoring,including the physical entities of natural disaster risk for immovable cultural relics,monitoring indicators,and virtual entity construction.A platform for monitoring the natural disaster risk of immovable cultural relics is proposed.Using the Puzhou Ancient City Site as a test bed,the proposed concept can be used for monitoring the natural disaster risk of immovable cultural relics at different scales.

Diagnostic value of ABCD2 and ABCD3-Ⅰ risk scoring systems in determining one-month risk of stroke in patients with transient ischemic attack: An observational study

Objective:To compare the diagnostic value of the ABCD2 and ABCD3-栺scoring systems in predicting the development of a 30-day neurological event in adult patients with transient ischemic attack(TIA)presenting to the emergency department.Methods:The study was observational and prospective and was conducted in a single center.The diagnostic values of the ABCD2 and ABCD3-栺scores in predicting a neurological event within one month were compared in patients diagnosed with TIA in the emergency department.Results:A statistically significant difference was observed between groups with or without stroke within one month in terms of both the ABCD2 and ABCD3-栺scores(P=0.044 and P=0.029,respectively).There was no statistically significant difference between the patients with and without a recurrent TIA within one month in relation to the ABCD2 score(P=0.934),but a statistically significant difference was found in the ABCD3-栺scores of these groups(P<0.001).Conclusions:Both the ABCD2 and ABCD3-栺scoring systems could predict ischemic stroke within 30 days of TIA,the ABCD3-栺score is more effective than the ABCD2 score in the prediction of TIA recurrence.

Carbon emission trading system and stock price crash risk of heavily polluting listed companies in China:based on analyst coverage mechanism

This study reveals the inconsistencies between the negative externalities of carbon emissions and the recognition condition of accounting statements.Hence,the study identifies that heavily polluting enterprises in China have severe off-balance sheet carbon reduction risks before implementing the carbon emission trading system(CETS).Through the staggered difference-in-difference(DID)model and the propen-sity score matching-DID model,the impact of CETS on reducing the risk of stock price crashes is examined using data from China’s A-share heavily polluting listed companies from 2007 to 2019.The results of this study are as follows:(1)CETS can significantly reduce the risk of stock price crashes for heavily polluting companies in the pilot areas.Specifically,CETS reduces the skewness(negative conditional skewness)and down-to-up volatility of the firm-specific weekly returns by 8.7%and 7.6%,respectively.(2)Heterogeneity analysis further shows that the impacts of CETS on the risk of stock price crashes are more significant for heavily polluting enterprises with the bear market condition,short-sighted management,and intensive air pollution.(3)Mechanism tests show that CETS can reduce analysts’coverage of heavy polluters,reducing the risk of stock price crashes.This study reveals the role of CETS from the stock price crash risk perspective and helps to clarify the relationship between climatic risk and corporate financial risk.

Over-limit risk assessment method of integrated energy system considering source-load correlation

In an integrated energy system,source-load multiple uncertainties and correlations lead to an over-limit risk in operating state,including voltage,temperature,and pressure over-limit.Therefore,efficient probabilistic energy flow calculation methods and risk assessment theories applicable to integrated energy systems are crucial.This study proposed a probabilistic energy flow calculation method based on polynomial chaos expansion for an electric-heat-gas integrated energy system.The method accurately and efficiently calculated the over-limit probability of the system state variables,considering the coupling conditions of electricity,heat,and gas,as well as uncertainties and correlations in renewable energy unit outputs and multiple types of loads.To further evaluate and quantify the impact of uncertainty factors on the over-limit risk,a global sensitivity analysis method for the integrated energy system based on the analysis of covariance theory is proposed.This method considered the source-load correlation and aimed to identify the key uncertainty factors that influence stable operation.Simulation results demonstrated that the proposed method achieved accuracy to that of the Monte Carlo method while significantly reducing calculation time.It effectively quantified the over-limit risk under the presence of multiple source-load uncertainties.