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CSEE Journal of Power and Energy Systems 2023年第5期9卷 1950-1958页

作者： Tong Qian Qianlong Wei Zeyuan Yu Wenhu Tang qing-hua wu School of Electric Power Engineering South China University of TechnologyGuangzhou 510641China

This paper aims to develop an approach to investigating the effect of a particular parameter on the output accuracy of transformer thermal models,i.***.sensitivity analysis,which can not only reveal the most sensitive parameter of a thermal model but also improve model output accuracies.For the first time,the nonlinear time constant(NTC)of transformer oil is proposed to reshape three practical top-oil temperature models based on an expression of nonlinear thermal conductance:the modified IEEE clause 7 model,Swift’s model,and Susa’s model.Then,the multi-parametric sensitivity analysis(MPSA)is undertaken to reveal the effect of each parameter on the model output accuracy.Through onsite data validation,the results show that the accuracy performance of the proposed NTC thermal models are improved significantly by considering the nonlinear effect of oil time constant.Moreover,the derived sensitivity performances can clearly reveal the most dominant parameter of the model,so as to simplify the model parameter identification process by reducing the number of insensitive parameters.Finally,the heat-run test data is used as a reference to validate parameters optimized through a genetic algorithm(GA),which demonstrates that the proposed NTC IEEE model has not only one sensitive parameter but also superior accuracy performance.

关键词： Constant genetic algorithm multi-parametric sensitivity analysis nonlinear oil time transformer thermal model

Stability Analysis of DC-DC Converters with Energy Balance Control

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CSEE Journal of Power and Energy Systems 2023年第5期9卷 1765-1773页

作者： Lei Wang Yang Liu Yongliang Guo qing-hua wu Guangfu Tang School of Electric Power Engineering South China University of TechnologyGuangzhou 510641China State Grid Smart Grid Research Institute Co. Ltd.Beijing 102209China

With variation of parameters,DC-DC converters may change from a stable state to an unstable state,which severely degrades the performances of the converter system.In this article,by establishing the state-space average model,the stability and bifurcation of a boost and a buck-boost converter with energy balance control(EBC)is studied,respectively.Then the stability boundary and stable parameter domains are accurately predicted.The obtained stability region provides a parameter regulating range for converter design.Furthermore,compared with the one-cycle control(OCC)method,the EBC possesses an extended stable parameter domain,while avoiding unstable behaviors such as Hopf bifurcation,Quasi-periodic Oscillation even chaos,etc.The theoretic analysis is well validated through simulation and experiment.

关键词： DC-DC converter energy balance control average model slow-scale stability

Probabilistic Optimal Power Flow Considering the Dependence of Multiple Wind Farms Using Pair Diffusive Kernel Copula

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CSEE Journal of Power and Energy Systems 2023年第5期9卷 1641-1654页

作者： Tianyao Ji Yantai Lin Yuzi Jiang Mengshi Li qing-hua wu the School of Electric Power Engineering South China University of TechnologyGuangzhou 510641China

As wind farms are commonly installed in areas with abundant wind resources,spatial dependence of wind speed among nearby wind farms should be considered when modeling a power system with large-scale wind power.In this paper,a novel bivariate non-parametric copula,and a bivariate diffusive kernel(BDK)copula are proposed to formulate the dependence between random variables.BDK copula is then applied to higher dimension using the pair-copula method and is named as pair diffusive kernel(PDK)copula,offering flexibility to formulate the complicated dependent structure of multiple random variables.Also,a quasi-Monte Carlo method is elaborated in the sampling procedure based on the combination of the Sobol sequence and the Rosen-blatt transformation of the PDK copula,to generate correlated wind speed samples.The proposed method is applied to solve probabilistic optimal power flow(POPF)problems.The effectiveness of the BDK copula is validated in copula definitions.Then,three different data sets are used in various goodness-of-fit tests to verify the superior performance of the PDK copula,which facilitates in formulating the dependence structure of wind speeds at different wind farms.Furthermore,samples obtained from the PDK copula are used to solve POPF problems,which are modeled on three modified IEEE 57-bus power systems.Compared to the Gaussian,T,and parametric-pair copulas,the results obtained from the PDK copula are superior in formulating the complicated dependence,thus solving POPF problems.

关键词： Bivariate diffusive kernel copula correlated wind speeds pair diffusive kernel copula probabilistic optimal power flow quasi-Monte Carlo Rosenblatt transformation

Many-objective Optimization Method Based on Dimension Reduction for Operation of Large-scale Cooling Energy Systems

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CSEE Journal of Power and Energy Systems 2023年第3期9卷 884-895页

作者： Peng Zhu Lixiao Wang Cuiqing wu Jinyu Yu Zhigang Li Jiehui Zheng qing-hua wu School of Electric Power Engineering South China University of TechnologyGuangzhou 510640China

Large-scale cooling energy system has developed well in the past decade.However,its optimization is still a problem to be tackled due to the nonlinearity and large scale of existing systems.Reducing the scale of problems without oversimplifying the actual system model is a big challenge nowadays.This paper proposes a dimension reduction-based many-objective optimization(DRMO)method to solve an accurate nonlinear model of a practical large-scale cooling energy system.In the first stage,many-objective and many-variable of the large system are pre-processed to reduce the overall scale of the optimization problem.The relationships between many objectives are analyzed to find a few representative objectives.Key control variables are extracted to reduce the dimension of variables and the number of equality constraints.In the second stage,the manyobjective group search optimization(GSO)method is used to solve the low-dimensional nonlinear model,and a Pareto-front is obtained.In the final stage,candidate solutions along the Paretofront are graded on many-objective levels of system operators.The candidate solution with the highest average utility value is selected as the best running mode.Simulations are carried out on a 619-node-614-branch cooling system,and results show the ability of the proposed method in solving large-scale system operation problems.

关键词： Dimension reduction group search optimization large-scale cooling energy system many-objective optimization

Transient Stability Analysis of Large-scale Power Systems:A Survey

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CSEE Journal of Power and Energy Systems 2023年第4期9卷 1284-1300页

作者： qing-hua wu Yuqing Lin Chao Hong Yinsheng Su Tianhao Wen Yang Liu School of Electric Power Engineering South China University of TechnologyGuangzhou 510640China the Power Dispatching and Control Center China Southern Power GridGuangzhou 510530China

Transient stability analysis is a key problem in power system operation and planning.This paper aims at giving a comprehensive review on the modeling ideas and analysis methods for transient stability of large-scale power systems.For model construction,the general modeling of traditional power systems and special modeling for renewable generations and high-voltage direct-current transmissions are introduced.For transient stability analysis,Lyapunov based methods and non-Lyapunov based methods are thoroughly reviewed.In Lya-punov based methods,we focus on the energy function method,the sum-of-squares based method and decentralized stability analysis methods.Meanwhile,in non-Lyapunov based methods,the time-domain simulation,extended equal-area criterion and data-driven based methods are considered.The basic working principles,features and recent research progresses of all the above-mentioned methods are described in detail.In particular,their performances on several aspects,such as computational speed,conservativeness of stability region estimation or stability margin calculation,and adaptability to various types of system models,are mentioned.Finally,a brief discussion of potential directions for future research on transient stability analysis of large-scale power systems is included.Index Terms-connective stability,large-scale system analysis,Lyapunov functions,power systems,transient stability analysis.

关键词： connective stability large-scale system analysis Lyapunov functions power systems transient stability analysis

Control and Stability of Large-scale Power System with Highly Distributed Renewable Energy Generation:Viewpoints from Six Aspects

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CSEE Journal of Power and Energy Systems 2023年第1期9卷 8-14页

作者： qing-hua wu Anjan Bose Chanan Singh Joe H.Chow Gang Mu Yuanzhang Sun Zhaoxi Liu Zhigang Li Yang Liu School of Electric Power Engineering South China University of TechnologyGuangzhou 510640China School of Electrical Engineering&Computer Science Washington State UniversityPullmanWA 99164USA Department of Electrical and Computer Engineering Texas A&M UniversityCollege StationTX 77843USA Department of Electrical Computer and Systems EngineeringRensselaer Polytechnic Institute(RPI)TroyNYUSA Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education(Northeast Electric Power University)Jilin 132012China School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China

Power systems are moving toward a low-carbon or carbon-neutral future where high penetration of renewables is expected.With conventional fossil-fueled synchronous generators in the transmission network being replaced by renewable energy generation which is highly distributed across the entire grid,new challenges are emerging to the control and stability of large-scale power systems.New analysis and control methods are needed for power systems to cope with the ongoing transformation.In the CSEE JPES forum,six leading experts were invited to deliver keynote speeches,and the participating researchers and professionals had extensive exchanges and discussions on the control and stability of power systems.Specifically,potential changes and challenges of power systems with high penetration of renewable energy generation were introduced and explained,and advanced control methods were proposed and analyzed for the transient stability enhancement of power grids.

关键词： Distributed energy resources high converter penetration power system control renewable energy generation stability control transient stability

Peripheral leukocyte count and risk of bleeding in patients with non-valvular atrial fibrillation taking dabigatran: a real-world study

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Chinese Medical Journal 2019年第18期132卷 2150-2156页

作者： Wei Zhou Tao Wang Ling-Juan Zhu Ming-hua Wen Li-hua Hu Xiao huang Chun-Jiao You Ju-Xiang Li Yan-qing wu qing-hua wu Hui-Hui Bao Xiao-Shu Cheng Center for Prevention and Treatment of Cardiovascular Diseases The Second Affiliated Hospital of Nanchang University Nanchang Jiangxi 330006 China Department of Cardiovascular Medicine The Second Affiliated Hospital of Nanchang University Nanchang Jiangxi 330006 China

Background: The association between peripheral leukocyte count and bleeding events in nonvalvular atrial fibrillation (NVAF) patients treated with dabigatran remains unclear. This study aimed to explore the association between leukocyte count and bleeding events after excluding other confounders in NVAF patients taking dabigatran. Methods: A total of 851 NVAF patients treated with dabigatran (110 mg bid) were recruited from 12 centers in China from February 2015 to December 2017. Follow-up was completed by May 2018. The exposure and outcome variables were leukocyte count measured at baseline and the number of bleeding events within the subsequent 6 months. Multivariate Cox proportional hazards models were constructed to analyze independent associations, and a Cox proportional hazards regression with cubic spline functions and smooth curve fitting (penalized spline method) was used to address nonlinearity between leukocyte count and bleeding. The inflection point was calculated using a recursive algorithm, and then a two-piecewise Cox proportional hazards model for both sides of the inflection point was constructed. Results: During 6-month follow-up, 87 participants occurred bleeding events. For every 1×10^9/L increase in leukocyte count, the risk of bleeding increased by 11%(hazard ratio [HR]: 1.11, 95% confidence interval [CI]: 0.99–1.25). The smooth curve showed nonlinear relationship between leukocyte count and bleeding events. The inflection point of the leukocyte count was 6.75×10^9/L. For leukocyte counts < 6.75×10^9/L, the HR (95% CI) was 0.88 (0.69–1.13), and for leukocyte counts ≥ 6.75×10^9/L, the HR (95% CI) was 1.28 (1.09–1.51). Conclusion: This study found a J-shaped association between baseline leukocyte count and risk of bleeding in NVAF patients treated with dabigatran.

关键词： Peripheral leukocyte count Bleeding Nonvalvular atrial fibrillation Threshold effect

Treatment of chronic heart failure in the 21st century: A new era of biomedical engineering has come

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Chronic Diseases and Translational Medicine 2019年第2期5卷 75-88页

作者： Chun-Song Hu qing-hua wu Da-Yi Hu Tengiz Tkebuchava Jiangxi Academy of Medical Science Hospital of Nanchang University Nanchang University Nanchang Jiangxi 330006 China Institute of Cardiovascular Diseases Nanchang University Nanchang Jiangxi 330006 China Department of Cardiology People's Hospital of Peking University Beijing 100044 China Department of Cardiology Tongji University School of Medicine Shanghai 200032 China Boston TransTec LLC Boston MA 02459 USA

Chronic heart failure (CHF) is a challenging burden on public health. Therapeutic strategies for CHF have developed rapidly in the past decades from conventional medical therapy, which mainly includes administration of angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, beta-blockers, and aldosterone antagonists, to biomedical engineering methods, which include interventional engineering, such as percutaneous balloon mitral valvotomy, percutaneous coronary intervention, catheter ablation, biventricular pacing or cardiac resynchronization therapy (CRT) and CRT-defibrillator use, and implantable cardioverter defibrillator use;mechanical engineering, such as left ventricular assistant device use, internal artery balloon counteq^ulsation, cardiac support device use, and total artificial heart implantation;surgical engineering, such as coronary artery bypass graft, valve replacement or repair of rheumatic or congenital heart diseases, and heart transplantation (HT);regenerate engineering, which includes gene therapy, stem cell transplantation, and tissue engineering;and rehabilitating engineering, which includes exercise training, low-salt diet, nursing, psychological interventions, health education, and external counterpulsation/enhanced external counterpulsation in the outpatient department. These biomedical engineering therapies have greatly improved the symptoms of CHF and life expectancy. To date, pharmacotherapy, which is based on evidence-based medicine, large-scale, multi-center, randomized controlled clinical trials, is still a major treatment option for CHF;the current interventional and mechanical device engineering treatment for advanced CHF is not enough owing to its individual status. In place of HT or the use of a total artificial heart, stem cell technology and gene therapy in regenerate engineering for CHF are very promising. However, each therapy has its advantages and disadvantages, and it is currently possible to select better therapeutic strategies for patients with CHF accord

关键词： Chronic heart failure Biomedical engineering Treatment

Development and validation of a deep learning model to screen hypokalemia from electrocardiogram in emergency patients

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Chinese Medical Journal 2021年第19期134卷 2333-2339页

作者： Chen-Xi Wang Yi-Chu Zhang Qi-Lin Kong Zu-Xiang wu Ping-Ping Yang Cai-hua Zhu Shou-Lin Chen Tao wu qing-hua wu Qi Chen Department of Cardiovascular Medicine The Second Affiliated Hospital of Nanchang UniversityNanchang University School of MedicineNanchangJiangxi 330006China Department of Anesthesiology The Second Affiliated Hospital of Nanchang UniversityNanchang University School of MedicineNanchangJiangxi 330006China

Background:A deep learning model(DLM)that enables non-invasive hypokalemia screening from an electrocardiogram(ECG)may improve the detection of this life-threatening condition.This study aimed to develop and evaluate the performance of a DLM for the detection of hypokalemia from the ECGs of emergency patients.Methods:We used a total of 9908 ECG data from emergency patients who were admitted at the Second Affiliated Hospital of Nanchang University,Jiangxi,China,from September 2017 to October 2020.The DLM was trained using 12 ECG leads(lead Ⅰ,Ⅱ,Ⅲ,aVR,aVL,aVF,and V1–6)to detect patients with serum potassium concentrations<3.5 mmol/L and was validated using retrospective data from the Jiangling branch of the Second Affiliated Hospital of Nanchang University.The blood draw was completed within 10 min before and after the ECG examination,and there was no new or ongoing infusion during this period.Results:We used 6904 ECGs and 1726 ECGs as development and internal validation data sets,respectively.In addition,1278 ECGs from the Jiangling branch of the Second Affiliated Hospital of Nanchang University were used as external validation data sets.Using 12 ECG leads(leads Ⅰ,Ⅱ,Ⅲ,aVR,aVL,aVF,and V1–6),the area under the receiver operating characteristic curve(AUC)of the DLM was 0.80(95%confidence interval[CI]:0.77–0.82)for the internal validation data set.Using an optimal operating point yielded a sensitivity of 71.4%and a specificity of 77.1%.Using the same 12 ECG leads,the external validation data set resulted in an AUC for the DLM of 0.77(95%CI:0.75–0.79).Using an optimal operating point yielded a sensitivity of 70.0%and a specificity of 69.1%.Conclusions:In this study,using 12 ECG leads,a DLM detected hypokalemia in emergency patients with an AUC of 0.77 to 0.80.Artificial intelligence could be used to analyze an ECG to quickly screen for hypokalemia.

关键词： Deep learning Hypokalemia Electrocardiogram Artificial intelligence

Procyanidin B2 protects against diet-induced obesity and non-alcoholic fatty liver disease via the modulation of the gut microbiota in rabbits

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World Journal of Gastroenterology 2019年第8期25卷 955-966页

作者： Ya-Wei Xing Guang-Tao Lei qing-hua wu Yu Jiang Man-Xiang huang Department of Gastroenterology The Second Xiangya HospitalCentral South UniversityChangsha 410011Hunan ProvinceChina Department of Cardiovascular Medicine The Second Affiliated Hospital of Nanchang UniversityNanchang 330006Jiangxi ProvinceChina

BACKGROUND Procyanidins have beneficial effects on metabolic syndrome and antimicrobial activity,but the mechanisms underlying these effects are unclear.AIM To investigate the effects of procyanidin B2(PB2)on non-alcoholic fatty liver disease and to explore the possible mechanism.METHODS Thirty male New Zealand white rabbits were randomized into three groups.All of them were fed either a high-fat-cholesterol diet(HCD)or chow diet.HCD-fed rabbits were treated with vehicle or PB2 daily for 12 wk.Body weight and food intake were evaluated once a week.Serum biomarkers,such as total cholesterols,triglycerides,and aspartate transaminase,were detected.All rabbits were sacrificed and histological parameters of liver were assessed by hematoxylin and eosin-stained sections.Moreover,several lipogenic genes and gut microbiota(by 16S rRNA sequencing)were investigated to explore the possible mechanism.RESULTS The HCD group had higher body weight,liver index,serum lipid profile,insulin resistance,serum glucose,and hepatic steatosis compared to the CHOW group.PB2 treatment prevented HCD-induced increases in body weight and hypertriglyceridemia in association with triglyceride accumulation in the liver.PB2 also ameliorated low-grade inflammation,which was reflected by serum lipopolysaccharides and improved insulin resistance.In rabbit liver,PB2 prevented the upregulation of steroid response element binding protein 1c and fatty acid synthase and the downregulation of carnitine palmitoyltransferase,compared to the HCD group.Moreover,HCD led to a decrease of Bacteroidetes in gut microbiota.PB2 significantly improved the proportions of Bacteroidetes at the phylum level and Akkermansia at the genus level.CONCLUSION Our results indicate the possible mechanism of PB2 to improve HCD-induced features of metabolic syndrome and provide a new dietary supplement.

关键词： Procyanidin Rabbit Non-alcoholic fatty liver disease Gut microbiota 16S rRNA