Active networks is primarily a Defense Advanced Research Projects Agency(DARPA)-funded project focusing on the research of mechanisms, applications, and operating systems to develop a reconfigurable network infrastruc...Active networks is primarily a Defense Advanced Research Projects Agency(DARPA)-funded project focusing on the research of mechanisms, applications, and operating systems to develop a reconfigurable network infrastructure. This letter proposes an Secure Active Tracing System (SATS) to implementing security for active networking in Internet. Unlike currently existing schemes, SATS reduces the computational overloads by executing the filtering operation on selected packet streams only when needed.展开更多
This paper provides a systematic review on the resilience analysis of active distribution networks(ADNs)against hazardous weather events,considering the underlying cyber-physical interdependencies.As cyber-physical sy...This paper provides a systematic review on the resilience analysis of active distribution networks(ADNs)against hazardous weather events,considering the underlying cyber-physical interdependencies.As cyber-physical systems,ADNs are characterized by widespread structural and functional interdependen-cies between cyber(communication,computing,and control)and physical(electric power)subsystems and thus present complex hazardous-weather-related resilience issues.To bridge current research gaps,this paper first classifies diverse hazardous weather events for ADNs according to different time spans and degrees of hazard,with model-based and data-driven methods being utilized to characterize weather evolutions.Then,the adverse impacts of hazardous weather on all aspects of ADNs’sources,physical/cyber networks,and loads are analyzed.This paper further emphasizes the importance of situational awareness and cyber-physical collaboration throughout hazardous weather events,as these enhance the implementation of preventive dispatches,corrective actions,and coordinated restorations.In addition,a generalized quantitative resilience evaluation process is proposed regarding additional considerations about cyber subsystems and cyber-physical connections.Finally,potential hazardous-weather-related resilience challenges for both physical and cyber subsystems are discussed.展开更多
In an active network, users can insert customized active codes into activenodes, to execute. Thus it needs more resources than those required by conventional networks, andthese resources must be effectively monitored ...In an active network, users can insert customized active codes into activenodes, to execute. Thus it needs more resources than those required by conventional networks, andthese resources must be effectively monitored and managed. Management policies in existing OSs aretoo complicated to apply to simple active packets. In this paper, we present new resourcesmanagement policies that are mainly adoped to manage CPU, storage and transmission bandwidth.Namely, we use SPF algorithm to schedule and process active packets, and import an interval queuemethod to allocate transmission bandwidth, and use feedback mechanism to control congestion . At thesame time, we design some experiments on prototype systems with and without resources managementpolicies respectively. The experiments results show that management policies presented by us caneffectively manage resources in active nodes and can improve the performance of active networks.展开更多
In this paper, we propose the dynamically-evolving active overlay network （DEAON）, which is an efficient, scalable yet simple protocol to facilitate applications of decentralized information retrieval in P2P network...In this paper, we propose the dynamically-evolving active overlay network （DEAON）, which is an efficient, scalable yet simple protocol to facilitate applications of decentralized information retrieval in P2P networks. DEAON consists of three novel components ： a Desirable Topology Construction and Adaptation algorithm to guide the evolution of the overlay topology towards a small-world-like graph; a Semantic-based Neighbor Selection scheme to conduct an online neighbor ranking; a Topology-aware Intelligent Search mechanism to forward incoming queries to deliberately selected neighbors. We deploy and compare DEAON with other several existing distributed search techniques over static and dynamic environments. The results indicate that DEAON outperforms its competitors by achieving higher recall rate while using much less network resources, in both of the above environments.展开更多
Considering the uncertainty of grid connection of electric vehicle charging stations and the uncertainty of new energy and residential electricity load,a spatio-temporal decoupling strategy of dynamic reactive power o...Considering the uncertainty of grid connection of electric vehicle charging stations and the uncertainty of new energy and residential electricity load,a spatio-temporal decoupling strategy of dynamic reactive power optimization based on clustering-local relaxation-correction is proposed.Firstly,the k-medoids clustering algorithm is used to divide the reduced power scene into periods.Then,the discrete variables and continuous variables are optimized in the same period of time.Finally,the number of input groups of parallel capacitor banks(CB)in multiple periods is fixed,and then the secondary static reactive power optimization correction is carried out by using the continuous reactive power output device based on the static reactive power compensation device(SVC),the new energy grid-connected inverter,and the electric vehicle charging station.According to the characteristics of the model,a hybrid optimization algorithm with a cross-feedback mechanism is used to solve different types of variables,and an improved artificial hummingbird algorithm based on tent chaotic mapping and adaptive mutation is proposed to improve the solution efficiency.The simulation results show that the proposed decoupling strategy can obtain satisfactory optimization resultswhile strictly guaranteeing the dynamic constraints of discrete variables,and the hybrid algorithm can effectively solve the mixed integer nonlinear optimization problem.展开更多
This study proposes a method for analyzing the security distance of an Active Distribution Network(ADN)by incorporating the demand response of an Energy Hub(EH).Taking into account the impact of stochastic wind-solar ...This study proposes a method for analyzing the security distance of an Active Distribution Network(ADN)by incorporating the demand response of an Energy Hub(EH).Taking into account the impact of stochastic wind-solar power and flexible loads on the EH,an interactive power model was developed to represent the EH’s operation under these influences.Additionally,an ADN security distance model,integrating an EH with flexible loads,was constructed to evaluate the effect of flexible load variations on the ADN’s security distance.By considering scenarios such as air conditioning(AC)load reduction and base station(BS)load transfer,the security distances of phases A,B,and C increased by 17.1%,17.2%,and 17.7%,respectively.Furthermore,a multi-objective optimal power flow model was formulated and solved using the Forward-Backward Power Flow Algorithm,the NSGA-II multi-objective optimization algo-rithm,and the maximum satisfaction method.The simulation results of the IEEE33 node system example demonstrate that after opti-mization,the total energy cost for one day is reduced by 0.026%,and the total security distance limit of the ADN’s three phases is improved by 0.1 MVA.This method effectively enhances the security distance,facilitates BS load transfer and AC load reduction,and contributes to the energy-saving,economical,and safe operation of the power system.展开更多
Active distribution network(ADN)planning is crucial for achieving a cost-effective transition to modern power systems,yet it poses significant challenges as the system scale increases.The advent of quantum computing o...Active distribution network(ADN)planning is crucial for achieving a cost-effective transition to modern power systems,yet it poses significant challenges as the system scale increases.The advent of quantum computing offers a transformative approach to solve ADN planning.To fully leverage the potential of quantum computing,this paper proposes a photonic quantum acceleration algorithm.First,a quantum-accelerated framework for ADN planning is proposed on the basis of coherent photonic quantum computers.The ADN planning model is then formulated and decomposed into discrete master problems and continuous subproblems to facilitate the quantum optimization process.The photonic quantum-embedded adaptive alternating direction method of multipliers(PQA-ADMM)algorithm is subsequently proposed to equivalently map the discrete master problem onto a quantum-interpretable model,enabling its deployment on a photonic quantum computer.Finally,a comparative analysis with various solvers,including Gurobi,demonstrates that the proposed PQA-ADMM algorithm achieves significant speedup on the modified IEEE 33-node and IEEE 123-node systems,highlighting its effectiveness.展开更多
We introduce a cluster-based secure active network environment (CSANE) which separates the processing of IP packets from that of active packets in active routers. In this environment, the active code authorized or tru...We introduce a cluster-based secure active network environment (CSANE) which separates the processing of IP packets from that of active packets in active routers. In this environment, the active code authorized or trusted by privileged users is executed in the secure execution environment (EE) of the active router, while others are executed in the secure EE of the nodes in the distributed shared memory (DSM) cluster. With the supports of a multi-process Java virtual machine and KeyNote, untrusted active packets are controlled to securely consume resource. The DSM consistency management makes that active packets can be parallely processed in the DSM cluster as if they were processed one by one in ANTS (Active Network Transport System). We demonstrate that CSANE has good security and scalability, but imposing little changes on traditional routers.展开更多
An algorithm of traffic distribution called active multi-path routing(AMR)in active network is proposed.AMR adopts multi-path routing and applies nonlinear optimizeapproximate method to distribute network traffic amon...An algorithm of traffic distribution called active multi-path routing(AMR)in active network is proposed.AMR adopts multi-path routing and applies nonlinear optimizeapproximate method to distribute network traffic among multiple paths.It is combined to bandwidthresource allocation and the congestion restraint mechanism to avoid congestion happening and worsen.So network performance can be improved greatly.The frame of AMR includes adaptive trafficallocation model,the conception of supply bandwidth and its'allocation model,the principle ofcongestion restraint and its'model,and the implement of AMR based on multi-agents system in activenetwork.Through simulations,AMR has distinct effects on network performance.The results show AMRisa valid traffic regulation algorithm.展开更多
This paper presents a data processing strategy for GPS kinematic positioning by using a GPS active network to model the GPS errors in double difference observable.Firstly,the double difference residuals are estimated ...This paper presents a data processing strategy for GPS kinematic positioning by using a GPS active network to model the GPS errors in double difference observable.Firstly,the double difference residuals are estimated between the reference stations in the active network.Then the errors at a user station are predicted as the network corrections to user measurements,based on the location of the user.Finally conventional kinematic positioning algorithms can be applied to determine the position of the user station.As an example,continuous 24_hour GPS data in March 2001 has been processed by this method.It clearly demonstrates that,after applying these corrections to a user within the network,both the success rate for ambiguity resolution and the positioning accuracy have been significantly improved.展开更多
In the graph signal processing(GSP)framework,distributed algorithms are highly desirable in processing signals defined on large-scale networks.However,in most existing distributed algorithms,all nodes homogeneously pe...In the graph signal processing(GSP)framework,distributed algorithms are highly desirable in processing signals defined on large-scale networks.However,in most existing distributed algorithms,all nodes homogeneously perform the local computation,which calls for heavy computational and communication costs.Moreover,in many real-world networks,such as those with straggling nodes,the homogeneous manner may result in serious delay or even failure.To this end,we propose active network decomposition algorithms to select non-straggling nodes(normal nodes)that perform the main computation and communication across the network.To accommodate the decomposition in different kinds of networks,two different approaches are developed,one is centralized decomposition that leverages the adjacency of the network and the other is distributed decomposition that employs the indicator message transmission between neighboring nodes,which constitutes the main contribution of this paper.By incorporating the active decomposition scheme,a distributed Newton method is employed to solve the least squares problem in GSP,where the Hessian inverse is approximately evaluated by patching a series of inverses of local Hessian matrices each of which is governed by one normal node.The proposed algorithm inherits the fast convergence of the second-order algorithms while maintains low computational and communication cost.Numerical examples demonstrate the effectiveness of the proposed algorithm.展开更多
An investigation on the neural networks based active vibration control of flexible redundant manipulators was conducted. The smart links of the manipulator were synthesized with the flexible links to which were attach...An investigation on the neural networks based active vibration control of flexible redundant manipulators was conducted. The smart links of the manipulator were synthesized with the flexible links to which were attached piezoceramic actuators and strain gauge sensors. A nonlinear adaptive control strategy named neural networks based indirect adaptive control (NNIAC) was employed to improve the dynamic performance of the manipulator. The mathematical model of the 4-layered dynamic recurrent neural networks (DRNN) was introduced. The neuro-identifier and the neuro-controller featuring the DRNN topology were designed off line so as to enhance the initial robustness of the NNIAC. By adjusting the neuro-identifier and the neuro-controller alternatively, the manipulator was controlled on line for achieving the desired dynamic performance. Finally, a planar 3R redundant manipulator with one smart link was utilized as an illustrative example. The simulation results proved the validity of the control strategy.展开更多
Active networks are a new kind of packet-switched networks in which packets have code fragments that are executed on the intermediary nodes (routers). The code can extend or modify the foundation architecture of a net...Active networks are a new kind of packet-switched networks in which packets have code fragments that are executed on the intermediary nodes (routers). The code can extend or modify the foundation architecture of a network. In this paper, the authors present a novel active network architecture combined with advantages of two major active networks technology based on extensible services router. The architecture consists of extensible service router, active extensible components server and key distribution center (KDC). Users can write extensible service components with programming interface. At the present time, we have finished the extensible services router prototype system based on Highly Efficient Router Operating System (HEROS), active extensible components server and KDC prototype system based on Linux.展开更多
Recent experimental evidence suggests that some brain activities can be assigned to small-world networks. In this work, we investigate how the topological probability p and connection strength C affect the activities ...Recent experimental evidence suggests that some brain activities can be assigned to small-world networks. In this work, we investigate how the topological probability p and connection strength C affect the activities of discrete neural networks with small-world （SW） connections. Network elements are described by two-dimensional map neurons （2DMNs） with the values of parameters at which no activity occurs. It is found that when the value of p is smaller or larger, there are no active neurons in the network, no matter what the value of connection strength is; for a given appropriate connection strength, there is an intermediate range of topological probability where the activity of 2DMN network is induced and enhanced. On the other hand, for a given intermediate topological probability level, there exists an optimal value of connection strength such that the frequency of activity reaches its maximum. The possible mechanism behind the action of topological probability and connection strength is addressed based on the bifurcation method. Furthermore, the effects of noise and transmission delay on the activity of neural network are also studied.展开更多
In this paper,an active network measurement platform is proposed which is a combination of hardware and software.Its innovation lies in the high performance of hardware combined with features that the software is easy...In this paper,an active network measurement platform is proposed which is a combination of hardware and software.Its innovation lies in the high performance of hardware combined with features that the software is easy to program,which retains software flexibility at the same time.By improving the precision of packet timestamp programmable hardware equipment,it provides packet sending control more accurately and supports the microsecond packet interval.We have implemented a model on the NetMagic platform,and done some experiments to analyze the accuracy difference of the user,the kernel and hardware timestamp.展开更多
In the framework of vigorous promotion of low-carbon power system growth as well as economic globalization,multi-resource penetration in active distribution networks has been advancing fiercely.In particular,distribut...In the framework of vigorous promotion of low-carbon power system growth as well as economic globalization,multi-resource penetration in active distribution networks has been advancing fiercely.In particular,distributed generation(DG)based on renewable energy is critical for active distribution network operation enhancement.To comprehensively analyze the accessing impact of DG in distribution networks from various parts,this paper establishes an optimal DG location and sizing planning model based on active power losses,voltage profile,pollution emissions,and the economics of DG costs as well as meteorological conditions.Subsequently,multiobjective particle swarm optimization(MOPSO)is applied to obtain the optimal Pareto front.Besides,for the sake of avoiding the influence of the subjective setting of the weight coefficient,the decisionmethod based on amodified ideal point is applied to execute a Pareto front decision.Finally,simulation tests based on IEEE33 and IEEE69 nodes are designed.The experimental results show thatMOPSO can achieve wider and more uniformPareto front distribution.In the IEEE33 node test system,power loss,and voltage deviation decreased by 52.23%,and 38.89%,respectively,while taking the economy into account.In the IEEE69 test system,the three indexes decreased by 19.67%,and 58.96%,respectively.展开更多
In recent years,the large-scale grid connection of various distributed power sources has made the planning and operation of distribution grids increasingly complex.Consequently,a large number of active distribution ne...In recent years,the large-scale grid connection of various distributed power sources has made the planning and operation of distribution grids increasingly complex.Consequently,a large number of active distribution network reconfiguration techniques have emerged to reduce system losses,improve system safety,and enhance power quality via switching switches to change the system topology while ensuring the radial structure of the network.While scholars have previously reviewed these methods,they all have obvious shortcomings,such as a lack of systematic integration of methods,vague classification,lack of constructive suggestions for future study,etc.Therefore,this paper attempts to provide a comprehensive and profound review of 52 methods and applications of active distribution network reconfiguration through systematic method classification and enumeration.Specifically,these methods are classified into five categories,i.e.,traditional methods,mathematical methods,meta-heuristic algorithms,machine learning methods,and hybrid methods.A thorough comparison of the various methods is also scored in terms of their practicality,complexity,number of switching actions,performance improvement,advantages,and disadvantages.Finally,four summaries and four future research prospects are presented.In summary,this paper aims to provide an up-to-date and well-rounded manual for subsequent researchers and scholars engaged in related fields.展开更多
A blockchain-based power transaction method is proposed for Active Distribution Network(ADN),considering the poor security and high cost of a centralized power trading system.Firstly,the decentralized blockchain struc...A blockchain-based power transaction method is proposed for Active Distribution Network(ADN),considering the poor security and high cost of a centralized power trading system.Firstly,the decentralized blockchain structure of the ADN power transaction is built and the transaction information is kept in blocks.Secondly,considering the transaction needs between users and power suppliers in ADN,an energy request mechanism is proposed,and the optimization objective function is designed by integrating cost aware requests and storage aware requests.Finally,the particle swarm optimization algorithm is used for multi-objective optimal search to find the power trading scheme with the minimum power purchase cost of users and the maximum power sold by power suppliers.The experimental demonstration of the proposed method based on the experimental platform shows that when the number of participants is no more than 10,the transaction delay time is 0.2 s,and the transaction cost fluctuates at 200,000 yuan,which is better than other comparison methods.展开更多
With the prevalence of renewable distributed energy resources(DERs)such as photovoltaics(PVs),modern active distribution networks(ADNs)suffer from voltage deviation and power quality issues.However,traditional voltage...With the prevalence of renewable distributed energy resources(DERs)such as photovoltaics(PVs),modern active distribution networks(ADNs)suffer from voltage deviation and power quality issues.However,traditional voltage control methods often face a trade-off between efficiency and effectiveness,and rarely ensure robust voltage safety under typical state perturbations in practical distribution grids.In this paper,a robust model-free voltage regulation approach is proposed which simultaneously takes security and robustness into account.In this context,the voltage control problem is formulated as a constrained Markov decision process(CMDP).A safety-augmented multiagent deep deterministic policy gradient(MADDPG)algorithm is the trained to enable real-time collaborative optimization of ADNs,aiming to maintain nodal voltages within safe operational limits while minimizing total line losses.Moreover,a robust regulation loss is introduced to ensure reliable performance under various state perturbations in practical voltage controls.The proposed regulation algorithm effectively balance efficiency,safety,and robustness,and also demonstrates potential for generalizing these characteristics to other applications.Numerical studies vali-date the robustness of the proposed method under varying state perturbations on the IEEE test cases and the optimal integrated control performance when compared to other benchmarks.展开更多
Thermal storage electric heating(TSEH),as a prevalent variable load resource,offers significant potential for enhancing system flexibility when aggregated into a cluster.To address the uncertainties of renewable energ...Thermal storage electric heating(TSEH),as a prevalent variable load resource,offers significant potential for enhancing system flexibility when aggregated into a cluster.To address the uncertainties of renewable energy and load forecasting in active distribution networks(ADN),this paper proposes a multi-timescale coordinated optimal dispatch strategy that incorporates TSEH clusters.It utilizes the thermal storage characteristics and short-term regulation capabilities of TSEH,along with the rapid and gradual response characteristics of resources in active distribution grids,to develop a coordinated optimization dispatch mechanism for day-ahead,intraday,and real-time stages.It provides a coordinated optimized dispatch technique across several timescales for active distribution grids,taking into account the integration of TSEH clusters.The proposed method is validated on a modified IEEE 33-node system.Simulation results demonstrate that the participation of TSEH in collaborative optimization significantly reduces the total system operating cost by 8.71%compared to the scenario without TSEH.This cost reduction is attributed to a 10.84%decrease in interaction costs with the main grid and a 47.41%reduction in network loss costs,validating effective peak shaving and valley filling.The multi-timescale framework further enhances economic efficiency,with overall operating costs progressively decreasing by 3.91%(intraday)and 4.59%(real-time),and interaction costs further reduced by 5.34%and 9.25%,respectively.Moreover,the approach enhances system stability by effectively suppressing node voltage fluctuations and ensuring all voltages remain within safe operating limits during real-time operation.Therefore,the proposed approach achieves rational coordination of diverse resources,significantly improving the economic efficiency and stability of ADNs.展开更多
文摘Active networks is primarily a Defense Advanced Research Projects Agency(DARPA)-funded project focusing on the research of mechanisms, applications, and operating systems to develop a reconfigurable network infrastructure. This letter proposes an Secure Active Tracing System (SATS) to implementing security for active networking in Internet. Unlike currently existing schemes, SATS reduces the computational overloads by executing the filtering operation on selected packet streams only when needed.
基金supported by the National Natural Science Foundation of China(52477132 and U2066601).
文摘This paper provides a systematic review on the resilience analysis of active distribution networks(ADNs)against hazardous weather events,considering the underlying cyber-physical interdependencies.As cyber-physical systems,ADNs are characterized by widespread structural and functional interdependen-cies between cyber(communication,computing,and control)and physical(electric power)subsystems and thus present complex hazardous-weather-related resilience issues.To bridge current research gaps,this paper first classifies diverse hazardous weather events for ADNs according to different time spans and degrees of hazard,with model-based and data-driven methods being utilized to characterize weather evolutions.Then,the adverse impacts of hazardous weather on all aspects of ADNs’sources,physical/cyber networks,and loads are analyzed.This paper further emphasizes the importance of situational awareness and cyber-physical collaboration throughout hazardous weather events,as these enhance the implementation of preventive dispatches,corrective actions,and coordinated restorations.In addition,a generalized quantitative resilience evaluation process is proposed regarding additional considerations about cyber subsystems and cyber-physical connections.Finally,potential hazardous-weather-related resilience challenges for both physical and cyber subsystems are discussed.
文摘In an active network, users can insert customized active codes into activenodes, to execute. Thus it needs more resources than those required by conventional networks, andthese resources must be effectively monitored and managed. Management policies in existing OSs aretoo complicated to apply to simple active packets. In this paper, we present new resourcesmanagement policies that are mainly adoped to manage CPU, storage and transmission bandwidth.Namely, we use SPF algorithm to schedule and process active packets, and import an interval queuemethod to allocate transmission bandwidth, and use feedback mechanism to control congestion . At thesame time, we design some experiments on prototype systems with and without resources managementpolicies respectively. The experiments results show that management policies presented by us caneffectively manage resources in active nodes and can improve the performance of active networks.
文摘In this paper, we propose the dynamically-evolving active overlay network （DEAON）, which is an efficient, scalable yet simple protocol to facilitate applications of decentralized information retrieval in P2P networks. DEAON consists of three novel components ： a Desirable Topology Construction and Adaptation algorithm to guide the evolution of the overlay topology towards a small-world-like graph; a Semantic-based Neighbor Selection scheme to conduct an online neighbor ranking; a Topology-aware Intelligent Search mechanism to forward incoming queries to deliberately selected neighbors. We deploy and compare DEAON with other several existing distributed search techniques over static and dynamic environments. The results indicate that DEAON outperforms its competitors by achieving higher recall rate while using much less network resources, in both of the above environments.
基金funded by the“Research and Application Project of Collaborative Optimization Control Technology for Distribution Station Area for High Proportion Distributed PV Consumption(4000-202318079A-1-1-ZN)”of the Headquarters of the State Grid Corporation.
文摘Considering the uncertainty of grid connection of electric vehicle charging stations and the uncertainty of new energy and residential electricity load,a spatio-temporal decoupling strategy of dynamic reactive power optimization based on clustering-local relaxation-correction is proposed.Firstly,the k-medoids clustering algorithm is used to divide the reduced power scene into periods.Then,the discrete variables and continuous variables are optimized in the same period of time.Finally,the number of input groups of parallel capacitor banks(CB)in multiple periods is fixed,and then the secondary static reactive power optimization correction is carried out by using the continuous reactive power output device based on the static reactive power compensation device(SVC),the new energy grid-connected inverter,and the electric vehicle charging station.According to the characteristics of the model,a hybrid optimization algorithm with a cross-feedback mechanism is used to solve different types of variables,and an improved artificial hummingbird algorithm based on tent chaotic mapping and adaptive mutation is proposed to improve the solution efficiency.The simulation results show that the proposed decoupling strategy can obtain satisfactory optimization resultswhile strictly guaranteeing the dynamic constraints of discrete variables,and the hybrid algorithm can effectively solve the mixed integer nonlinear optimization problem.
基金supported in part by the National Nat-ural Science Foundation of China(No.51977012,No.52307080).
文摘This study proposes a method for analyzing the security distance of an Active Distribution Network(ADN)by incorporating the demand response of an Energy Hub(EH).Taking into account the impact of stochastic wind-solar power and flexible loads on the EH,an interactive power model was developed to represent the EH’s operation under these influences.Additionally,an ADN security distance model,integrating an EH with flexible loads,was constructed to evaluate the effect of flexible load variations on the ADN’s security distance.By considering scenarios such as air conditioning(AC)load reduction and base station(BS)load transfer,the security distances of phases A,B,and C increased by 17.1%,17.2%,and 17.7%,respectively.Furthermore,a multi-objective optimal power flow model was formulated and solved using the Forward-Backward Power Flow Algorithm,the NSGA-II multi-objective optimization algo-rithm,and the maximum satisfaction method.The simulation results of the IEEE33 node system example demonstrate that after opti-mization,the total energy cost for one day is reduced by 0.026%,and the total security distance limit of the ADN’s three phases is improved by 0.1 MVA.This method effectively enhances the security distance,facilitates BS load transfer and AC load reduction,and contributes to the energy-saving,economical,and safe operation of the power system.
基金supported in part by the National Natural Science Foundation of China under Grant 52307134the Fundamental Research Funds for the Central Universities(xzy012025022)。
文摘Active distribution network(ADN)planning is crucial for achieving a cost-effective transition to modern power systems,yet it poses significant challenges as the system scale increases.The advent of quantum computing offers a transformative approach to solve ADN planning.To fully leverage the potential of quantum computing,this paper proposes a photonic quantum acceleration algorithm.First,a quantum-accelerated framework for ADN planning is proposed on the basis of coherent photonic quantum computers.The ADN planning model is then formulated and decomposed into discrete master problems and continuous subproblems to facilitate the quantum optimization process.The photonic quantum-embedded adaptive alternating direction method of multipliers(PQA-ADMM)algorithm is subsequently proposed to equivalently map the discrete master problem onto a quantum-interpretable model,enabling its deployment on a photonic quantum computer.Finally,a comparative analysis with various solvers,including Gurobi,demonstrates that the proposed PQA-ADMM algorithm achieves significant speedup on the modified IEEE 33-node and IEEE 123-node systems,highlighting its effectiveness.
文摘We introduce a cluster-based secure active network environment (CSANE) which separates the processing of IP packets from that of active packets in active routers. In this environment, the active code authorized or trusted by privileged users is executed in the secure execution environment (EE) of the active router, while others are executed in the secure EE of the nodes in the distributed shared memory (DSM) cluster. With the supports of a multi-process Java virtual machine and KeyNote, untrusted active packets are controlled to securely consume resource. The DSM consistency management makes that active packets can be parallely processed in the DSM cluster as if they were processed one by one in ANTS (Active Network Transport System). We demonstrate that CSANE has good security and scalability, but imposing little changes on traditional routers.
基金Supported by the National Natural Science Foun dation of China(90204008)
文摘An algorithm of traffic distribution called active multi-path routing(AMR)in active network is proposed.AMR adopts multi-path routing and applies nonlinear optimizeapproximate method to distribute network traffic among multiple paths.It is combined to bandwidthresource allocation and the congestion restraint mechanism to avoid congestion happening and worsen.So network performance can be improved greatly.The frame of AMR includes adaptive trafficallocation model,the conception of supply bandwidth and its'allocation model,the principle ofcongestion restraint and its'model,and the implement of AMR based on multi-agents system in activenetwork.Through simulations,AMR has distinct effects on network performance.The results show AMRisa valid traffic regulation algorithm.
文摘This paper presents a data processing strategy for GPS kinematic positioning by using a GPS active network to model the GPS errors in double difference observable.Firstly,the double difference residuals are estimated between the reference stations in the active network.Then the errors at a user station are predicted as the network corrections to user measurements,based on the location of the user.Finally conventional kinematic positioning algorithms can be applied to determine the position of the user station.As an example,continuous 24_hour GPS data in March 2001 has been processed by this method.It clearly demonstrates that,after applying these corrections to a user within the network,both the success rate for ambiguity resolution and the positioning accuracy have been significantly improved.
基金supported by National Natural Science Foundation of China(Grant No.61761011)Natural Science Foundation of Guangxi(Grant No.2020GXNSFBA297078).
文摘In the graph signal processing(GSP)framework,distributed algorithms are highly desirable in processing signals defined on large-scale networks.However,in most existing distributed algorithms,all nodes homogeneously perform the local computation,which calls for heavy computational and communication costs.Moreover,in many real-world networks,such as those with straggling nodes,the homogeneous manner may result in serious delay or even failure.To this end,we propose active network decomposition algorithms to select non-straggling nodes(normal nodes)that perform the main computation and communication across the network.To accommodate the decomposition in different kinds of networks,two different approaches are developed,one is centralized decomposition that leverages the adjacency of the network and the other is distributed decomposition that employs the indicator message transmission between neighboring nodes,which constitutes the main contribution of this paper.By incorporating the active decomposition scheme,a distributed Newton method is employed to solve the least squares problem in GSP,where the Hessian inverse is approximately evaluated by patching a series of inverses of local Hessian matrices each of which is governed by one normal node.The proposed algorithm inherits the fast convergence of the second-order algorithms while maintains low computational and communication cost.Numerical examples demonstrate the effectiveness of the proposed algorithm.
基金Supported by National Natural Science Foundation of China(No.59975001 and 50205019).
文摘An investigation on the neural networks based active vibration control of flexible redundant manipulators was conducted. The smart links of the manipulator were synthesized with the flexible links to which were attached piezoceramic actuators and strain gauge sensors. A nonlinear adaptive control strategy named neural networks based indirect adaptive control (NNIAC) was employed to improve the dynamic performance of the manipulator. The mathematical model of the 4-layered dynamic recurrent neural networks (DRNN) was introduced. The neuro-identifier and the neuro-controller featuring the DRNN topology were designed off line so as to enhance the initial robustness of the NNIAC. By adjusting the neuro-identifier and the neuro-controller alternatively, the manipulator was controlled on line for achieving the desired dynamic performance. Finally, a planar 3R redundant manipulator with one smart link was utilized as an illustrative example. The simulation results proved the validity of the control strategy.
文摘Active networks are a new kind of packet-switched networks in which packets have code fragments that are executed on the intermediary nodes (routers). The code can extend or modify the foundation architecture of a network. In this paper, the authors present a novel active network architecture combined with advantages of two major active networks technology based on extensible services router. The architecture consists of extensible service router, active extensible components server and key distribution center (KDC). Users can write extensible service components with programming interface. At the present time, we have finished the extensible services router prototype system based on Highly Efficient Router Operating System (HEROS), active extensible components server and KDC prototype system based on Linux.
基金Project supported by the Key Program of National Natural Science Foundation of China (Grant No. 50937001),the National Natural Science Foundation of China (Grant Nos. 50877028, 10947011 and 10862001)the High Technology Research and Development Program of China (Grant No. 2007AA05Z229)+1 种基金the Science Foundation of Guangdong Province, China (Grant No. 8251064101000014)the Construction of Key Laboratories in Universities of Guangxi Province, China (Grant No. 200912)
文摘Recent experimental evidence suggests that some brain activities can be assigned to small-world networks. In this work, we investigate how the topological probability p and connection strength C affect the activities of discrete neural networks with small-world （SW） connections. Network elements are described by two-dimensional map neurons （2DMNs） with the values of parameters at which no activity occurs. It is found that when the value of p is smaller or larger, there are no active neurons in the network, no matter what the value of connection strength is; for a given appropriate connection strength, there is an intermediate range of topological probability where the activity of 2DMN network is induced and enhanced. On the other hand, for a given intermediate topological probability level, there exists an optimal value of connection strength such that the frequency of activity reaches its maximum. The possible mechanism behind the action of topological probability and connection strength is addressed based on the bifurcation method. Furthermore, the effects of noise and transmission delay on the activity of neural network are also studied.
基金Supported by the National High Technology Research and Development Programme of China(No.2007AA01Z416)"New Start" Academic Research Projects of Beijing Union University(No.ZK201204)
文摘In this paper,an active network measurement platform is proposed which is a combination of hardware and software.Its innovation lies in the high performance of hardware combined with features that the software is easy to program,which retains software flexibility at the same time.By improving the precision of packet timestamp programmable hardware equipment,it provides packet sending control more accurately and supports the microsecond packet interval.We have implemented a model on the NetMagic platform,and done some experiments to analyze the accuracy difference of the user,the kernel and hardware timestamp.
基金The authors gratefully acknowledge the support of the Enhancement Strategy of Multi-Type Energy Integration of Active Distribution Network(YNKJXM20220113).
文摘In the framework of vigorous promotion of low-carbon power system growth as well as economic globalization,multi-resource penetration in active distribution networks has been advancing fiercely.In particular,distributed generation(DG)based on renewable energy is critical for active distribution network operation enhancement.To comprehensively analyze the accessing impact of DG in distribution networks from various parts,this paper establishes an optimal DG location and sizing planning model based on active power losses,voltage profile,pollution emissions,and the economics of DG costs as well as meteorological conditions.Subsequently,multiobjective particle swarm optimization(MOPSO)is applied to obtain the optimal Pareto front.Besides,for the sake of avoiding the influence of the subjective setting of the weight coefficient,the decisionmethod based on amodified ideal point is applied to execute a Pareto front decision.Finally,simulation tests based on IEEE33 and IEEE69 nodes are designed.The experimental results show thatMOPSO can achieve wider and more uniformPareto front distribution.In the IEEE33 node test system,power loss,and voltage deviation decreased by 52.23%,and 38.89%,respectively,while taking the economy into account.In the IEEE69 test system,the three indexes decreased by 19.67%,and 58.96%,respectively.
基金funding from the National Natural Science Foundation of China(62263014)Yunnan Provincial Basic Research Project(202401AT070344,202301AT070443)Science and Technology Commission of Shanghai Municipality(STCSM)Sailing Program(22YF1414400).
文摘In recent years,the large-scale grid connection of various distributed power sources has made the planning and operation of distribution grids increasingly complex.Consequently,a large number of active distribution network reconfiguration techniques have emerged to reduce system losses,improve system safety,and enhance power quality via switching switches to change the system topology while ensuring the radial structure of the network.While scholars have previously reviewed these methods,they all have obvious shortcomings,such as a lack of systematic integration of methods,vague classification,lack of constructive suggestions for future study,etc.Therefore,this paper attempts to provide a comprehensive and profound review of 52 methods and applications of active distribution network reconfiguration through systematic method classification and enumeration.Specifically,these methods are classified into five categories,i.e.,traditional methods,mathematical methods,meta-heuristic algorithms,machine learning methods,and hybrid methods.A thorough comparison of the various methods is also scored in terms of their practicality,complexity,number of switching actions,performance improvement,advantages,and disadvantages.Finally,four summaries and four future research prospects are presented.In summary,this paper aims to provide an up-to-date and well-rounded manual for subsequent researchers and scholars engaged in related fields.
基金supported by the Postdoctoral Research Funding Program of Jiangsu Province under Grant 2021K622C.
文摘A blockchain-based power transaction method is proposed for Active Distribution Network(ADN),considering the poor security and high cost of a centralized power trading system.Firstly,the decentralized blockchain structure of the ADN power transaction is built and the transaction information is kept in blocks.Secondly,considering the transaction needs between users and power suppliers in ADN,an energy request mechanism is proposed,and the optimization objective function is designed by integrating cost aware requests and storage aware requests.Finally,the particle swarm optimization algorithm is used for multi-objective optimal search to find the power trading scheme with the minimum power purchase cost of users and the maximum power sold by power suppliers.The experimental demonstration of the proposed method based on the experimental platform shows that when the number of participants is no more than 10,the transaction delay time is 0.2 s,and the transaction cost fluctuates at 200,000 yuan,which is better than other comparison methods.
基金supported in part by the National Natural Science Foundation of China(No.52177109)Key R&D Program of Hubei Province,China(No.2020BAB109).
文摘With the prevalence of renewable distributed energy resources(DERs)such as photovoltaics(PVs),modern active distribution networks(ADNs)suffer from voltage deviation and power quality issues.However,traditional voltage control methods often face a trade-off between efficiency and effectiveness,and rarely ensure robust voltage safety under typical state perturbations in practical distribution grids.In this paper,a robust model-free voltage regulation approach is proposed which simultaneously takes security and robustness into account.In this context,the voltage control problem is formulated as a constrained Markov decision process(CMDP).A safety-augmented multiagent deep deterministic policy gradient(MADDPG)algorithm is the trained to enable real-time collaborative optimization of ADNs,aiming to maintain nodal voltages within safe operational limits while minimizing total line losses.Moreover,a robust regulation loss is introduced to ensure reliable performance under various state perturbations in practical voltage controls.The proposed regulation algorithm effectively balance efficiency,safety,and robustness,and also demonstrates potential for generalizing these characteristics to other applications.Numerical studies vali-date the robustness of the proposed method under varying state perturbations on the IEEE test cases and the optimal integrated control performance when compared to other benchmarks.
基金supported by Integrated Distribution Network Planning and Operational Enhancement Using Flexibility Domains Under Deep Human-Vehicle-Charger-Road-Grid Coupling(U22B20105).
文摘Thermal storage electric heating(TSEH),as a prevalent variable load resource,offers significant potential for enhancing system flexibility when aggregated into a cluster.To address the uncertainties of renewable energy and load forecasting in active distribution networks(ADN),this paper proposes a multi-timescale coordinated optimal dispatch strategy that incorporates TSEH clusters.It utilizes the thermal storage characteristics and short-term regulation capabilities of TSEH,along with the rapid and gradual response characteristics of resources in active distribution grids,to develop a coordinated optimization dispatch mechanism for day-ahead,intraday,and real-time stages.It provides a coordinated optimized dispatch technique across several timescales for active distribution grids,taking into account the integration of TSEH clusters.The proposed method is validated on a modified IEEE 33-node system.Simulation results demonstrate that the participation of TSEH in collaborative optimization significantly reduces the total system operating cost by 8.71%compared to the scenario without TSEH.This cost reduction is attributed to a 10.84%decrease in interaction costs with the main grid and a 47.41%reduction in network loss costs,validating effective peak shaving and valley filling.The multi-timescale framework further enhances economic efficiency,with overall operating costs progressively decreasing by 3.91%(intraday)and 4.59%(real-time),and interaction costs further reduced by 5.34%and 9.25%,respectively.Moreover,the approach enhances system stability by effectively suppressing node voltage fluctuations and ensuring all voltages remain within safe operating limits during real-time operation.Therefore,the proposed approach achieves rational coordination of diverse resources,significantly improving the economic efficiency and stability of ADNs.
