As an open network architecture,Wireless Computing PowerNetworks(WCPN)pose newchallenges for achieving efficient and secure resource management in networks,because of issues such as insecure communication channels and...As an open network architecture,Wireless Computing PowerNetworks(WCPN)pose newchallenges for achieving efficient and secure resource management in networks,because of issues such as insecure communication channels and untrusted device terminals.Blockchain,as a shared,immutable distributed ledger,provides a secure resource management solution for WCPN.However,integrating blockchain into WCPN faces challenges like device heterogeneity,monitoring communication states,and dynamic network nature.Whereas Digital Twins(DT)can accurately maintain digital models of physical entities through real-time data updates and self-learning,enabling continuous optimization of WCPN,improving synchronization performance,ensuring real-time accuracy,and supporting smooth operation of WCPN services.In this paper,we propose a DT for blockchain-empowered WCPN architecture that guarantees real-time data transmission between physical entities and digital models.We adopt an enumeration-based optimal placement algorithm(EOPA)and an improved simulated annealing-based near-optimal placement algorithm(ISAPA)to achieve minimum average DT synchronization latency under the constraint of DT error.Numerical results show that the proposed solution in this paper outperforms benchmarks in terms of average synchronization latency.展开更多
Along with the increasing integration of renewable energy generation in AC-DC power networks,investigating the dynamic behaviors of this complex system with a proper equivalent model is significant.This paper presents...Along with the increasing integration of renewable energy generation in AC-DC power networks,investigating the dynamic behaviors of this complex system with a proper equivalent model is significant.This paper presents an equivalent modeling method for the AC-DC power networks with doubly-fed induction generator(DFIG)based wind farms to decrease the simulation scale and computational burden.For the AC-DC power networks,the equivalent modeling strategy in accordance with the physical structure simplification is stated.Regarding the DFIG-based wind farms,the equivalent modeling based on the sequential identification of multi-machine parameters using the improved chaotic cuckoo search algorithm(ICCSA)is conducted.In light of the MATLAB simulation platform,a two-zone four-DC interconnected power grid with wind farms is built to check the efficacy of the proposed equivalentmodelingmethod.Fromthe simulation analyses and comparative validation in different algorithms and cases,the proposed method can precisely reflect the steady and dynamic performance of the demonstrated system under N-1 and N-2 fault scenarios,and it can efficiently achieve the parameter identification of the wind farms and fulfill the equivalent modeling.Consequently,the proposed approach’s effectiveness and suitability are confirmed.展开更多
In 6G era,service forms in which computing power acts as the core will be ubiquitous in the network.At the same time,the collaboration among edge computing,cloud computing and network is needed to support edge computi...In 6G era,service forms in which computing power acts as the core will be ubiquitous in the network.At the same time,the collaboration among edge computing,cloud computing and network is needed to support edge computing service with strong demand for computing power,so as to realize the optimization of resource utilization.Based on this,the article discusses the research background,key techniques and main application scenarios of computing power network.Through the demonstration,it can be concluded that the technical solution of computing power network can effectively meet the multi-level deployment and flexible scheduling needs of the future 6G business for computing,storage and network,and adapt to the integration needs of computing power and network in various scenarios,such as user oriented,government enterprise oriented,computing power open and so on.展开更多
Rural power network planning is a complicated nonlinear optimized combination problem which based on load forecasting results, and its actual load is affected by many uncertain factors, which influenced optimization r...Rural power network planning is a complicated nonlinear optimized combination problem which based on load forecasting results, and its actual load is affected by many uncertain factors, which influenced optimization results of rural power network planning. To solve the problems, the interval algorithm was used to modify the initial search method of uncertainty load mathematics model in rural network planning. Meanwhile, the genetic/tabu search combination algorithm was adopted to optimize the initialized network. The sample analysis results showed that compared with the certainty planning, the improved method was suitable for urban medium-voltage distribution network planning with consideration of uncertainty load and the planning results conformed to the reality.展开更多
In view of the serious reactive power loss in the rural network, improved ant colony optimization algorithm (ACOA) was used to optimize the reactive power compensation for the rural distribution system. In this stud...In view of the serious reactive power loss in the rural network, improved ant colony optimization algorithm (ACOA) was used to optimize the reactive power compensation for the rural distribution system. In this study, the traditional ACOA was improved in two aspects: one was the local search strategy, and the other was pheromone mutation and re-initialization strategies. The reactive power optimization for a county's distribution network showed that the improved ACOA was practicable.展开更多
The autotransformer(AT)neutral current ratio method is widely used for fault location in the AT traction power network.With the development of high-speed electrified railways,a large number of data show that the relat...The autotransformer(AT)neutral current ratio method is widely used for fault location in the AT traction power network.With the development of high-speed electrified railways,a large number of data show that the relation between the AT neutral current ratio and the distance from the beginning of the fault AT section to the fault point(Q-L relation)is mostly nonlinear.Therefore,the linear Q-L relation in the traditional fault location method always leads to large errors.To solve this problem,a large number of load-related current data that can be used to describe the Q-L relation are obtained through the load test of the electric multiple unit(EMU).Thus,an improved fault location method based on the back propagation(BP)neural network is proposed in this paper.On this basis,a comparison between the improved method and the traditional method shows that the maximum absolute error and the average absolute error of the improved method are 0.651 km and 0.334 km lower than those of the traditional method,respectively,which demonstrates that the improved method can effectively eliminate the influence of nonlinear factors and greatly improve the accuracy of fault location for the AT traction power network.Finally,combined with a shortcircuit test,the accuracy of the improved method is verified.展开更多
The features of three modes of AT-fed traction power networks (TPNs) have been briefly described in the existing literature, which is not adequate yet. In this paper, these three modes of TPNs are compared mainly on T...The features of three modes of AT-fed traction power networks (TPNs) have been briefly described in the existing literature, which is not adequate yet. In this paper, these three modes of TPNs are compared mainly on TPN capacity, transformer capacity, rail potential and voltage level, etc., and conclusions are drawn.展开更多
In this paper, we adopt a novel topological approach to fault diagnosis. In our researches, global information will be introduced into electric power network, we are using mainly BFS of graph theory algorithms and lin...In this paper, we adopt a novel topological approach to fault diagnosis. In our researches, global information will be introduced into electric power network, we are using mainly BFS of graph theory algorithms and linear discriminant principle to resolve fast and exact analysis of faulty components and faulty sections, and finally accomplish fault diagnosis. The results of BFS and linear discriminant are identical. The main technical contributions and innovations in this paper include, introducing global information into electric power network, developing a novel topological analysis to fault diagnosis. Graph theory algorithms can be used to model many different physical and abstract systems such as transportation and communication networks, models for business administration, political science, and psychology and so on. And the linear discriminant is a procedure used to classify an object into one of several a priori groupings dependent on the individual characteristics of the object. In the study of fault diagnosis in electric power network, graph theory algorithms and linear discriminant technology must also have a good prospect of application.展开更多
基金supported by the National Natural Science Foundation of China under Grant 62272391in part by the Key Industry Innovation Chain of Shaanxi under Grant 2021ZDLGY05-08.
文摘As an open network architecture,Wireless Computing PowerNetworks(WCPN)pose newchallenges for achieving efficient and secure resource management in networks,because of issues such as insecure communication channels and untrusted device terminals.Blockchain,as a shared,immutable distributed ledger,provides a secure resource management solution for WCPN.However,integrating blockchain into WCPN faces challenges like device heterogeneity,monitoring communication states,and dynamic network nature.Whereas Digital Twins(DT)can accurately maintain digital models of physical entities through real-time data updates and self-learning,enabling continuous optimization of WCPN,improving synchronization performance,ensuring real-time accuracy,and supporting smooth operation of WCPN services.In this paper,we propose a DT for blockchain-empowered WCPN architecture that guarantees real-time data transmission between physical entities and digital models.We adopt an enumeration-based optimal placement algorithm(EOPA)and an improved simulated annealing-based near-optimal placement algorithm(ISAPA)to achieve minimum average DT synchronization latency under the constraint of DT error.Numerical results show that the proposed solution in this paper outperforms benchmarks in terms of average synchronization latency.
基金supported by the Science and Technology Project of Central China Branch of State Grid Corporation of China under 5214JS220010.
文摘Along with the increasing integration of renewable energy generation in AC-DC power networks,investigating the dynamic behaviors of this complex system with a proper equivalent model is significant.This paper presents an equivalent modeling method for the AC-DC power networks with doubly-fed induction generator(DFIG)based wind farms to decrease the simulation scale and computational burden.For the AC-DC power networks,the equivalent modeling strategy in accordance with the physical structure simplification is stated.Regarding the DFIG-based wind farms,the equivalent modeling based on the sequential identification of multi-machine parameters using the improved chaotic cuckoo search algorithm(ICCSA)is conducted.In light of the MATLAB simulation platform,a two-zone four-DC interconnected power grid with wind farms is built to check the efficacy of the proposed equivalentmodelingmethod.Fromthe simulation analyses and comparative validation in different algorithms and cases,the proposed method can precisely reflect the steady and dynamic performance of the demonstrated system under N-1 and N-2 fault scenarios,and it can efficiently achieve the parameter identification of the wind farms and fulfill the equivalent modeling.Consequently,the proposed approach’s effectiveness and suitability are confirmed.
基金This work was supported by the National Key R&D Program of China No.2019YFB1802800.
文摘In 6G era,service forms in which computing power acts as the core will be ubiquitous in the network.At the same time,the collaboration among edge computing,cloud computing and network is needed to support edge computing service with strong demand for computing power,so as to realize the optimization of resource utilization.Based on this,the article discusses the research background,key techniques and main application scenarios of computing power network.Through the demonstration,it can be concluded that the technical solution of computing power network can effectively meet the multi-level deployment and flexible scheduling needs of the future 6G business for computing,storage and network,and adapt to the integration needs of computing power and network in various scenarios,such as user oriented,government enterprise oriented,computing power open and so on.
文摘Rural power network planning is a complicated nonlinear optimized combination problem which based on load forecasting results, and its actual load is affected by many uncertain factors, which influenced optimization results of rural power network planning. To solve the problems, the interval algorithm was used to modify the initial search method of uncertainty load mathematics model in rural network planning. Meanwhile, the genetic/tabu search combination algorithm was adopted to optimize the initialized network. The sample analysis results showed that compared with the certainty planning, the improved method was suitable for urban medium-voltage distribution network planning with consideration of uncertainty load and the planning results conformed to the reality.
基金Supported by China Postdoctoral Science Foundation(20090460873)
文摘In view of the serious reactive power loss in the rural network, improved ant colony optimization algorithm (ACOA) was used to optimize the reactive power compensation for the rural distribution system. In this study, the traditional ACOA was improved in two aspects: one was the local search strategy, and the other was pheromone mutation and re-initialization strategies. The reactive power optimization for a county's distribution network showed that the improved ACOA was practicable.
基金supported by the National Key Research and Development Program of China(No.2021YFB2601500)the Natural Science Foundation of Sichuan Province(No.2022NSFSC0405)。
文摘The autotransformer(AT)neutral current ratio method is widely used for fault location in the AT traction power network.With the development of high-speed electrified railways,a large number of data show that the relation between the AT neutral current ratio and the distance from the beginning of the fault AT section to the fault point(Q-L relation)is mostly nonlinear.Therefore,the linear Q-L relation in the traditional fault location method always leads to large errors.To solve this problem,a large number of load-related current data that can be used to describe the Q-L relation are obtained through the load test of the electric multiple unit(EMU).Thus,an improved fault location method based on the back propagation(BP)neural network is proposed in this paper.On this basis,a comparison between the improved method and the traditional method shows that the maximum absolute error and the average absolute error of the improved method are 0.651 km and 0.334 km lower than those of the traditional method,respectively,which demonstrates that the improved method can effectively eliminate the influence of nonlinear factors and greatly improve the accuracy of fault location for the AT traction power network.Finally,combined with a shortcircuit test,the accuracy of the improved method is verified.
文摘The features of three modes of AT-fed traction power networks (TPNs) have been briefly described in the existing literature, which is not adequate yet. In this paper, these three modes of TPNs are compared mainly on TPN capacity, transformer capacity, rail potential and voltage level, etc., and conclusions are drawn.
文摘In this paper, we adopt a novel topological approach to fault diagnosis. In our researches, global information will be introduced into electric power network, we are using mainly BFS of graph theory algorithms and linear discriminant principle to resolve fast and exact analysis of faulty components and faulty sections, and finally accomplish fault diagnosis. The results of BFS and linear discriminant are identical. The main technical contributions and innovations in this paper include, introducing global information into electric power network, developing a novel topological analysis to fault diagnosis. Graph theory algorithms can be used to model many different physical and abstract systems such as transportation and communication networks, models for business administration, political science, and psychology and so on. And the linear discriminant is a procedure used to classify an object into one of several a priori groupings dependent on the individual characteristics of the object. In the study of fault diagnosis in electric power network, graph theory algorithms and linear discriminant technology must also have a good prospect of application.