In this paper, a mathematical model consisting of forward and backward models is built on parallel genetic algorithms (PGAs) for fault diagnosis in a transmission power system. A new method to reduce the scale of faul...In this paper, a mathematical model consisting of forward and backward models is built on parallel genetic algorithms (PGAs) for fault diagnosis in a transmission power system. A new method to reduce the scale of fault sections is developed in the forward model and the message passing interface (MPI) approach is chosen to parallel the genetic algorithms by global sin-gle-population master-slave method (GPGAs). The proposed approach is applied to a sample system consisting of 28 sections, 84 protective relays and 40 circuit breakers. Simulation results show that the new model based on GPGAs can achieve very fast computation in online applications of large-scale power systems.展开更多
A novel planning tool for optimizing the placement of electric springs(ESs)in unbalanced distribution networks is introduced in this study.The total voltage deviation is used as the optimization criterion and is calcu...A novel planning tool for optimizing the placement of electric springs(ESs)in unbalanced distribution networks is introduced in this study.The total voltage deviation is used as the optimization criterion and is calculated when the ESs operate at their maximum reactive power either in the inductive or capacitive modes.The power rating of the ES is adjusted on the basis of the available active power at the bus.And in the optimization problem,it is expressed as the power ratio of the noncritical load(NCL)and critical load(CL).The implemented ES model is flexible,which can be used on any bus and any phase.The model determines the output voltage from the parameters and operating conditions at the point of common coupling(PCC).These conditions are integrated using the backward/forward sweep method(BFSM)and are updated during power flow calculations.The problem is described as a mixed-integer nonlinear problem and solved efficiently using an improved BFSM-based genetic algorithm,which computes power flow and ES placement simultaneously.The effectiveness of this method is evaluated through testing in IEEE 13-bus and 34-bus systems.展开更多
Objective To study the key technologies in the field of ginsenosides and to offer a guide for the future development ginsenosides through the main path identification method based on genetic knowledge persistence algo...Objective To study the key technologies in the field of ginsenosides and to offer a guide for the future development ginsenosides through the main path identification method based on genetic knowledge persistence algorithm(GKPA).Methods The global ginsenoside invention authorized patents were used as the data source to construct a ginsenoside patent self-citation network,and to identify high knowledge persistent patents(HKPP)of ginsenoside technology based on the GKPA,and extract its high knowledge persistence main path(HKPMP).Finally,the genetic forward and backward path(GFBP)was used to search the nodes on the main path,and draw the genetic forward and backward main path(GFBMP)of ginsenoside technology.Results and Conclusion The algorithm was applied to the field of ginsenosides.The research results show the milestone patents in ginsenosides technology and the main evolution process of three key technologies,which points out the future direction for the technological development of ginsenosides.The results obtained by this algorithm are more interpretable,comprehensive and scientific.展开更多
基金the National Natural Science Foundation of China (No. 50677062)the New Century Excellent Talents in Uni-versity of China (No. NCET-07-0745)the Natural Science Foundation of Zhejiang Province, China (No. R107062)
文摘In this paper, a mathematical model consisting of forward and backward models is built on parallel genetic algorithms (PGAs) for fault diagnosis in a transmission power system. A new method to reduce the scale of fault sections is developed in the forward model and the message passing interface (MPI) approach is chosen to parallel the genetic algorithms by global sin-gle-population master-slave method (GPGAs). The proposed approach is applied to a sample system consisting of 28 sections, 84 protective relays and 40 circuit breakers. Simulation results show that the new model based on GPGAs can achieve very fast computation in online applications of large-scale power systems.
基金supported by Consejo Nacional de Humanidades,Ciencia y Tecnología(CONAHCYT)—México(No.863547)the fellowship 2021-000001-01NACF-00604 given to the G.H.Valencia-Riverathe scholarships 175599,64698,253652,and 296574,given to G.Tapia-Tinoco,A.Garcia-Perez,D.Granados-Lieberman,and M.Valtierra-Rodriguez,respectively,through the Sistema Nacional de Investigadoras e Investigadores(SNII)-CONAHCYT-México.
文摘A novel planning tool for optimizing the placement of electric springs(ESs)in unbalanced distribution networks is introduced in this study.The total voltage deviation is used as the optimization criterion and is calculated when the ESs operate at their maximum reactive power either in the inductive or capacitive modes.The power rating of the ES is adjusted on the basis of the available active power at the bus.And in the optimization problem,it is expressed as the power ratio of the noncritical load(NCL)and critical load(CL).The implemented ES model is flexible,which can be used on any bus and any phase.The model determines the output voltage from the parameters and operating conditions at the point of common coupling(PCC).These conditions are integrated using the backward/forward sweep method(BFSM)and are updated during power flow calculations.The problem is described as a mixed-integer nonlinear problem and solved efficiently using an improved BFSM-based genetic algorithm,which computes power flow and ES placement simultaneously.The effectiveness of this method is evaluated through testing in IEEE 13-bus and 34-bus systems.
文摘Objective To study the key technologies in the field of ginsenosides and to offer a guide for the future development ginsenosides through the main path identification method based on genetic knowledge persistence algorithm(GKPA).Methods The global ginsenoside invention authorized patents were used as the data source to construct a ginsenoside patent self-citation network,and to identify high knowledge persistent patents(HKPP)of ginsenoside technology based on the GKPA,and extract its high knowledge persistence main path(HKPMP).Finally,the genetic forward and backward path(GFBP)was used to search the nodes on the main path,and draw the genetic forward and backward main path(GFBMP)of ginsenoside technology.Results and Conclusion The algorithm was applied to the field of ginsenosides.The research results show the milestone patents in ginsenosides technology and the main evolution process of three key technologies,which points out the future direction for the technological development of ginsenosides.The results obtained by this algorithm are more interpretable,comprehensive and scientific.
