The optical, thermal and electrical properties of ultra-thin two-dimensional （2D） crystal materials are highly related to their thickness. Therefore, identifying the atomic planes of few-layer crystal materials rapi...The optical, thermal and electrical properties of ultra-thin two-dimensional （2D） crystal materials are highly related to their thickness. Therefore, identifying the atomic planes of few-layer crystal materials rapidly is crucial to fundamental study. Here, a simple technique was demonstrated based on optical contrast for counting atomic planes （n） of few-layer MoSe2 on SiO2/Si substrates. It is found that the optical contrast of single-layer MoSe2 depends on light wavelength and thickness of SiO2 on Si substrate. The data calculated based on a Fresnel law-based model as well as atomic force microscopy （AFM） mea- surements fit well with the values measured by spectro- scopic ellipsometer. Furthermore, the calculated and measured contrasts were integral and plotted, which can be used to determine the MoSe2 atomic planes （1 ≤ n ≤ 4） accurately and rapidly.展开更多
Winding is one of themost important components in power transformers.Ensuring the health state of the winding is of great importance to the stable operation of the power system.To efficiently and accurately diagnose t...Winding is one of themost important components in power transformers.Ensuring the health state of the winding is of great importance to the stable operation of the power system.To efficiently and accurately diagnose the disc space variation(DSV)fault degree of transformer winding,this paper presents a diagnostic method of winding fault based on the K-Nearest Neighbor(KNN)algorithmand the frequency response analysis(FRA)method.First,a laboratory winding model is used,and DSV faults with four different degrees are achieved by changing disc space of the discs in the winding.Then,a series of FRA tests are conducted to obtain the FRA results and set up the FRA dataset.Second,ten different numerical indices are utilized to obtain features of FRA curves of faulted winding.Third,the 10-fold cross-validation method is employed to determine the optimal k-value of KNN.In addition,to improve the accuracy of the KNN model,a comparative analysis is made between the accuracy of the KNN algorithm and k-value under four distance functions.After getting the most appropriate distance metric and kvalue,the fault classificationmodel based on theKNN and FRA is constructed and it is used to classify the degrees of DSV faults.The identification accuracy rate of the proposed model is up to 98.30%.Finally,the performance of the model is presented by comparing with the support vector machine(SVM),SVM optimized by the particle swarmoptimization(PSO-SVM)method,and randomforest(RF).The results show that the diagnosis accuracy of the proposed model is the highest and the model can be used to accurately diagnose the DSV fault degrees of the winding.展开更多
The quality as well as reliability of electrical energy transmitted to consumers is one of the main parameters of successful operation of the power system. The searching of optimal coefficient＇s combination of PSS （...The quality as well as reliability of electrical energy transmitted to consumers is one of the main parameters of successful operation of the power system. The searching of optimal coefficient＇s combination of PSS （power system stabilizer） is the main goal of this article. The possibility of application of the new combined approach for the optimal excitation＇s settings search is presented. MC （Monte Carlo） method, in order to search and select the optimal combination of excitation system, was applied. The proposed method has been researched with a mathematical model of the power system. This model has been built using Matlab/Simulink software. Paper shows advantages and disadvantages of the proposed methods.展开更多
In restructured power systems,the traditional approaches of unit maintenance scheduling(UMS)need to undergo major changes in order to be compatible with new competitive structures.Performing the maintenance on generat...In restructured power systems,the traditional approaches of unit maintenance scheduling(UMS)need to undergo major changes in order to be compatible with new competitive structures.Performing the maintenance on generating units may decrease the security level of transmission network and result in electricity shortage in power system;as a result,it can impose a kind of cost on transmission network as called security cost.Moreover,taking off line a generating unit for performing maintenance can change power flow in some transmission lines,and may lead to network congestion.In this study,generating unit maintenance is scheduled considering security and congestion cost with N-1 examination for transmission lines random failures.The proposed UMS approach would lead to optimum operation of power system in terms of economy and security.To achieve this goal,the optimal power flow(OPF)compatible with market mechanism is implemented.Moreover,the electricity price discovery mechanism as locational marginal pricing(LMP)is restated to analyze the impacts of UMS on nodal electricity price.Considering security and congestion cost simultaneously,this novel approach can reveal some new costs which are imposed to transmission network on behalf of generation units;as a result,it provides a great opportunity to perform maintenance in a fair environment for both generating companies(GenCo)and transmission companies(TransCo).At the end,simulation results on nine-bus test power system demonstrate that by using this method,the proposed UMS can guarantee fairness among market participants including GenCos and TransCo and ensure power system security.展开更多
基金financially supported by the Research Funds of Renmin University of China(Nos.13XNLF02 and 14XNLQ07)the National Natural Science Foundation of China(Nos.11304381,11004245,11174366 and 51202200)
文摘The optical, thermal and electrical properties of ultra-thin two-dimensional （2D） crystal materials are highly related to their thickness. Therefore, identifying the atomic planes of few-layer crystal materials rapidly is crucial to fundamental study. Here, a simple technique was demonstrated based on optical contrast for counting atomic planes （n） of few-layer MoSe2 on SiO2/Si substrates. It is found that the optical contrast of single-layer MoSe2 depends on light wavelength and thickness of SiO2 on Si substrate. The data calculated based on a Fresnel law-based model as well as atomic force microscopy （AFM） mea- surements fit well with the values measured by spectro- scopic ellipsometer. Furthermore, the calculated and measured contrasts were integral and plotted, which can be used to determine the MoSe2 atomic planes （1 ≤ n ≤ 4） accurately and rapidly.
基金supported in part by Shaanxi Natural Science Foundation Project (2023-JC-QN-0438)in part by Fundamental Research Funds for the Central Universities (2452021050).
文摘Winding is one of themost important components in power transformers.Ensuring the health state of the winding is of great importance to the stable operation of the power system.To efficiently and accurately diagnose the disc space variation(DSV)fault degree of transformer winding,this paper presents a diagnostic method of winding fault based on the K-Nearest Neighbor(KNN)algorithmand the frequency response analysis(FRA)method.First,a laboratory winding model is used,and DSV faults with four different degrees are achieved by changing disc space of the discs in the winding.Then,a series of FRA tests are conducted to obtain the FRA results and set up the FRA dataset.Second,ten different numerical indices are utilized to obtain features of FRA curves of faulted winding.Third,the 10-fold cross-validation method is employed to determine the optimal k-value of KNN.In addition,to improve the accuracy of the KNN model,a comparative analysis is made between the accuracy of the KNN algorithm and k-value under four distance functions.After getting the most appropriate distance metric and kvalue,the fault classificationmodel based on theKNN and FRA is constructed and it is used to classify the degrees of DSV faults.The identification accuracy rate of the proposed model is up to 98.30%.Finally,the performance of the model is presented by comparing with the support vector machine(SVM),SVM optimized by the particle swarmoptimization(PSO-SVM)method,and randomforest(RF).The results show that the diagnosis accuracy of the proposed model is the highest and the model can be used to accurately diagnose the DSV fault degrees of the winding.
文摘The quality as well as reliability of electrical energy transmitted to consumers is one of the main parameters of successful operation of the power system. The searching of optimal coefficient＇s combination of PSS （power system stabilizer） is the main goal of this article. The possibility of application of the new combined approach for the optimal excitation＇s settings search is presented. MC （Monte Carlo） method, in order to search and select the optimal combination of excitation system, was applied. The proposed method has been researched with a mathematical model of the power system. This model has been built using Matlab/Simulink software. Paper shows advantages and disadvantages of the proposed methods.
文摘In restructured power systems,the traditional approaches of unit maintenance scheduling(UMS)need to undergo major changes in order to be compatible with new competitive structures.Performing the maintenance on generating units may decrease the security level of transmission network and result in electricity shortage in power system;as a result,it can impose a kind of cost on transmission network as called security cost.Moreover,taking off line a generating unit for performing maintenance can change power flow in some transmission lines,and may lead to network congestion.In this study,generating unit maintenance is scheduled considering security and congestion cost with N-1 examination for transmission lines random failures.The proposed UMS approach would lead to optimum operation of power system in terms of economy and security.To achieve this goal,the optimal power flow(OPF)compatible with market mechanism is implemented.Moreover,the electricity price discovery mechanism as locational marginal pricing(LMP)is restated to analyze the impacts of UMS on nodal electricity price.Considering security and congestion cost simultaneously,this novel approach can reveal some new costs which are imposed to transmission network on behalf of generation units;as a result,it provides a great opportunity to perform maintenance in a fair environment for both generating companies(GenCo)and transmission companies(TransCo).At the end,simulation results on nine-bus test power system demonstrate that by using this method,the proposed UMS can guarantee fairness among market participants including GenCos and TransCo and ensure power system security.
