Waveform generation and digitization play essential roles in numerous physics experiments.In traditional distributed systems for large-scale experiments,each frontend node contains an FPGA for data preprocessing,which...Waveform generation and digitization play essential roles in numerous physics experiments.In traditional distributed systems for large-scale experiments,each frontend node contains an FPGA for data preprocessing,which interfaces with various data converters and exchanges data with a backend central processor.However,the streaming readout architecture has become a new paradigm for several experiments benefiting from advancements in data transmission and computing technologies.This paper proposes a scalable distributed waveform generation and digitization system that utilizes fiber optical connections for data transmission between frontend nodes and a central processor.By utilizing transparent transmission on top of the data link layer,the clock and data ports of the converters in the frontend nodes are directly mapped to the FPGA firmware at the backend.This streaming readout architecture reduces the complexity of frontend development and maintains the data conversion in proximity to the detector.Each frontend node uses a local clock for waveform digitization.To translate the timing information of events in each channel into the system clock domain within the backend central processing FPGA,a novel method is proposed and evaluated using a demonstrator system.展开更多
As a matured technique used in many fields,the distributed computer system is still a new management method for the aeronautical electrical power distribution system in our country. In this paper, a novel aircraft ele...As a matured technique used in many fields,the distributed computer system is still a new management method for the aeronautical electrical power distribution system in our country. In this paper, a novel aircraft electrical power distribution system based on the distributed computer system is proposed. The principles, features and structure of the aircraft electrical power distribution system and the distributed computer system named electrical load management system (ELMS) are studied. The ELMS composed of four electrical load management centers (ELMCs) and two power source processors (PSPs) operates in the 1553B buses. Principles of the ELMCs and the PSPs are introduced. With the application of the distributed computer system, the aircraft electrical power distribution system is simple, adaptable and flexible.展开更多
Artificial intelligence(AI)plays a critical role in signal recognition of distributed sensor systems(DSS),boosting its applications in multiple monitoring fields.Due to the domain differences between massive sensors i...Artificial intelligence(AI)plays a critical role in signal recognition of distributed sensor systems(DSS),boosting its applications in multiple monitoring fields.Due to the domain differences between massive sensors in signal acquisition conditions,such as manufacturing process,deployment,and environments,current AI schemes for signal recognition of DSS frequently encounter poor generalization performance.In this paper,an adaptive decentralized artificial intelligence(ADAI)method for signal recognition of DSS is proposed,to improve the entire generalization performance.By fine-tuning pre-trained model with the unlabeled data in each domain,the ADAI scheme can train a series of adaptive AI models for all target domains,significantly reducing the false alarm rate(FAR)and missing alarm rate(MAR)induced by domain differences.The field tests about intrusion signal recognition with distributed optical fiber sensors system demonstrate the efficacy of the ADAI scheme,showcasing a FAR of merely 4.3%and 0%,along with a MAR of only 1.4%and 2.7%within two specific target domains.The ADAI scheme is expected to offer a practical paradigm for signal recognition of DSS in multiple application fields.展开更多
We develop a policy of observer-based dynamic event-triggered state feedback control for distributed parameter systems over a mobile sensor-plus-actuator network.It is assumed that the mobile sensing devices that prov...We develop a policy of observer-based dynamic event-triggered state feedback control for distributed parameter systems over a mobile sensor-plus-actuator network.It is assumed that the mobile sensing devices that provide spatially averaged state measurements can be used to improve state estimation in the network.For the purpose of decreasing the update frequency of controller and unnecessary sampled data transmission, an efficient dynamic event-triggered control policy is constructed.In an event-triggered system, when an error signal exceeds a specified time-varying threshold, it indicates the occurrence of a typical event.The global asymptotic stability of the event-triggered closed-loop system and the boundedness of the minimum inter-event time can be guaranteed.Based on the linear quadratic optimal regulator, the actuator selects the optimal displacement only when an event occurs.A simulation example is finally used to verify that the effectiveness of such a control strategy can enhance the system performance.展开更多
Cell-free systems significantly improve network capacity by enabling joint user service without cell boundaries,eliminating intercell interference.However,to satisfy further capacity demands,it leads to high-cost prob...Cell-free systems significantly improve network capacity by enabling joint user service without cell boundaries,eliminating intercell interference.However,to satisfy further capacity demands,it leads to high-cost problems of both hardware and power consumption.In this paper,we investigate multiple reconfigurable intelligent surfaces(RISs)aided cell-free systems where RISs are introduced to improve spectrum efficiency in an energy-efficient way.To overcome the centralized high complexity and avoid frequent information exchanges,a cooperative distributed beamforming design is proposed to maximize the weighted sum-rate performance.In particular,the alternating optimization method is utilized with the distributed closed-form solution of active beamforming being derived locally at access points,and phase shifts are obtained centrally based on the Riemannian conjugate gradient(RCG)manifold method.Simulation results verify the effectiveness of the proposed design whose performance is comparable to the centralized scheme and show great superiority of the RISs-aided system over the conventional cellular and cell-free system.展开更多
Given the rapid development of advanced information systems,microgrids(MGs)suffer from more potential attacks that affect their operational performance.Conventional distributed secondary control with a small,fixed sam...Given the rapid development of advanced information systems,microgrids(MGs)suffer from more potential attacks that affect their operational performance.Conventional distributed secondary control with a small,fixed sampling time period inevitably causes the wasteful use of communication resources.This paper proposes a self-triggered secondary control scheme under perturbations from false data injection(FDI)attacks.We designed a linear clock for each DG to trigger its controller at aperiodic and intermittent instants.Sub-sequently,a hash-based defense mechanism(HDM)is designed for detecting and eliminating malicious data infiltrated in the MGs.With the aid of HDM,a self-triggered control scheme achieves the secondary control objectives even in the presence of FDI attacks.Rigorous theoretical analyses and simulation results indicate that the introduced secondary control scheme significantly reduces communication costs and enhances the resilience of MGs under FDI attacks.展开更多
Distributed acoustic sensing(DAS)is increasingly used in seismic exploration owing to its wide frequency range,dense sampling and real-time monitoring.DAS radiation patterns help to understand angle response of DAS re...Distributed acoustic sensing(DAS)is increasingly used in seismic exploration owing to its wide frequency range,dense sampling and real-time monitoring.DAS radiation patterns help to understand angle response of DAS records and improve the quality of inversion and imaging.In this paper,we solve the 3D vertical transverse isotropic(VTI)Christoffel equation and obtain the analytical,frst-order,and zero-order Taylor expansion solutions that represent P-,SV-,and SH-wave phase velocities and polarization vectors.These analytical and approximated solutions are used to build the P/S plane-wave expression identical to the far-feld term of seismic wave,from which the strain rate expressions are derived and DAS radiation patterns are thus extracted for anisotropic P/S waves.We observe that the gauge length and phase angle terms control the radiating intensity of DAS records.Additionally,the Bond transformation is adopted to derive the DAS radiation patterns in title transverse isotropic(TTI)media,which exhibits higher complexity than that of VTI media.Several synthetic examples demonstrate the feasibility and effectiveness of our theory.展开更多
This paper presents a novel approach to dynamic pricing and distributed energy management in virtual power plant(VPP)networks using multi-agent reinforcement learning(MARL).As the energy landscape evolves towards grea...This paper presents a novel approach to dynamic pricing and distributed energy management in virtual power plant(VPP)networks using multi-agent reinforcement learning(MARL).As the energy landscape evolves towards greater decentralization and renewable integration,traditional optimization methods struggle to address the inherent complexities and uncertainties.Our proposed MARL framework enables adaptive,decentralized decision-making for both the distribution system operator and individual VPPs,optimizing economic efficiency while maintaining grid stability.We formulate the problem as a Markov decision process and develop a custom MARL algorithm that leverages actor-critic architectures and experience replay.Extensive simulations across diverse scenarios demonstrate that our approach consistently outperforms baseline methods,including Stackelberg game models and model predictive control,achieving an 18.73%reduction in costs and a 22.46%increase in VPP profits.The MARL framework shows particular strength in scenarios with high renewable energy penetration,where it improves system performance by 11.95%compared with traditional methods.Furthermore,our approach demonstrates superior adaptability to unexpected events and mis-predictions,highlighting its potential for real-world implementation.展开更多
In the current noisy intermediate-scale quantum(NISQ)era,a single quantum processing unit(QPU)is insufficient to implement large-scale quantum algorithms;this has driven extensive research into distributed quantum com...In the current noisy intermediate-scale quantum(NISQ)era,a single quantum processing unit(QPU)is insufficient to implement large-scale quantum algorithms;this has driven extensive research into distributed quantum computing(DQC).DQC involves the cooperative operation of multiple QPUs but is concurrently challenged by excessive communication complexity.To address this issue,this paper proposes a quantum circuit partitioning method based on spectral clustering.The approach transforms quantum circuits into weighted graphs and,through computation of the Laplacian matrix and clustering techniques,identifies candidate partition schemes that minimize the total weight of the cut.Additionally,a global gate search tree strategy is introduced to meticulously explore opportunities for merged transfer of global gates,thereby minimizing the transmission cost of distributed quantum circuits and selecting the optimal partition scheme from the candidates.Finally,the proposed method is evaluated through various comparative experiments.The experimental results demonstrate that spectral clustering-based partitioning exhibits robust stability and efficiency in runtime in quantum circuits of different scales.In experiments involving the quantum Fourier transform algorithm and Revlib quantum circuits,the transmission cost achieved by the global gate search tree strategy is significantly optimized.展开更多
Frequent extreme disasters have led to frequent large-scale power outages in recent years.To quickly restore power,it is necessary to understand the damage information of the distribution network accurately.However,th...Frequent extreme disasters have led to frequent large-scale power outages in recent years.To quickly restore power,it is necessary to understand the damage information of the distribution network accurately.However,the public network communication system is easily damaged after disasters,causing the operation center to lose control of the distribution network.In this paper,we considered using satellites to transmit the distribution network data and focus on the resource scheduling problem of the satellite emergency communication system for the distribution network.Specifically,this paper first formulates the satellite beam-pointing problem and the accesschannel joint resource allocation problem.Then,this paper proposes the Priority-based Beam-pointing and Access-Channel joint optimization algorithm(PBAC),which uses convex optimization theory to solve the satellite beam pointing problem,and adopts the block coordinate descent method,Lagrangian dual method,and a greedy algorithm to solve the access-channel joint resource allocation problem,thereby obtaining the optimal resource scheduling scheme for the satellite network.Finally,this paper conducts comparative experiments with existing methods to verify the effec-tiveness of the proposed methods.The results show that the total weighted transmitted data of the proposed algorithm is increased by about 19.29∼26.29%compared with other algorithms.展开更多
The cooperative control and stability analysis problems for the multi-agent system with sampled com- munication are investigated. Distributed state feedback controllers are adopted for the cooperation of networked age...The cooperative control and stability analysis problems for the multi-agent system with sampled com- munication are investigated. Distributed state feedback controllers are adopted for the cooperation of networked agents. A theorem in the form of linear matrix inequalities（LMI） is derived to analyze the system stability. An- other theorem in the form of optimization problem subject to LMI constraints is proposed to design the controller, and then the algorithm is presented. The simulation results verify the validity and the effectiveness of the pro- posed approach.展开更多
An attempt has been made to develop a distributed software infrastructure model for onboard data fusion system simulation, which is also applied to netted radar systems, onboard distributed detection systems and advan...An attempt has been made to develop a distributed software infrastructure model for onboard data fusion system simulation, which is also applied to netted radar systems, onboard distributed detection systems and advanced C3I systems. Two architectures are provided and verified: one is based on pure TCP/IP protocol and C/S model, and implemented with Winsock, the other is based on CORBA (common object request broker architecture). The performance of data fusion simulation system, i.e. reliability, flexibility and scalability, is improved and enhanced by two models. The study of them makes valuable explore on incorporating the distributed computation concepts into radar system simulation techniques.展开更多
Fault tolerant ability is an important aspect for overall evaluation of distributed system(DS). This paper discusses three measures for the evaluation: node/edge connectivity, number of spanning trees and synthetic co...Fault tolerant ability is an important aspect for overall evaluation of distributed system(DS). This paper discusses three measures for the evaluation: node/edge connectivity, number of spanning trees and synthetic connectivity. A numerical example for illustration and analysis is given, and the synthetic connectivity measure presented by this paper is proved to be rational and satisfactory.展开更多
Based on MATRIXx, a universal real-time visual distributed simulation system is developed. The system can receive different input data from network or local terminal. Application models in the simulation modules can a...Based on MATRIXx, a universal real-time visual distributed simulation system is developed. The system can receive different input data from network or local terminal. Application models in the simulation modules can automatically get such data to be analyzed and calculated, and then produce real-time simulation control information. Meanwhile, this paper designs relevant simulation components to implement the input and output data, which can guarantee the real-time and universal of the data transmission. Result of the experimental system shows that the real-time performance of the simulation is perfect.展开更多
Spectrum sharing for efficient reuse of licensed spectrum is an important concept for cognitive radio technologies.In a spectrum-sharing system(SSS),deploying the antennas in a distributed manner can offer a new spati...Spectrum sharing for efficient reuse of licensed spectrum is an important concept for cognitive radio technologies.In a spectrum-sharing system(SSS),deploying the antennas in a distributed manner can offer a new spatial dimension for the efficient reuse of licensed frequency bands.To improve the whole performance of multiple secondary users(SUs),this paper addresses the problem of coordinated multi-SU spectrum sharing in a distributed antenna-based SSS.By adopting the Hungarian method,the primal decomposition method and pricing policy,we propose a coordinated multi-user transmission scheme,so as to maximize the sum-rate of SUs.Simulation results show that the proposed method can significantly enhance the system performance,and the computational complexity is low.展开更多
The rapid growth of distributed generator(DG)capacities has introduced additional controllable assets to improve the performance of distribution systems in terms of service restoration.Renewable DGs are of particular ...The rapid growth of distributed generator(DG)capacities has introduced additional controllable assets to improve the performance of distribution systems in terms of service restoration.Renewable DGs are of particular interest to utility companies,but the stochastic nature of intermittent renewable DGs could have a negative impact on the electric grid if they are not properly handled.In this study,we investigate distribution system service restoration using DGs as the primary power source,and we develop an effective approach to handle the uncertainty of renewable DGs under extreme conditions.The distribution system service restoration problem can be described as a mixed-integer second-order cone programming model by modifying the radial topology constraints and power flow equations.The uncertainty of renewable DGs will be modeled using a chance-constrained approach.Furthermore,the forecast errors and noises in real-time operation are solved using a novel model-free control algorithm that can automatically track the trajectory of real-time DG output.The proposed service restoration strategy and model-free control algorithm are validated using an IEEE 123-bus test system.展开更多
To reduce the time required to complete the regeneration process of erasure codes, we propose a Tree-structured Parallel Regeneration (TPR) scheme for multiple data losses in distributed storage systems. Under the sch...To reduce the time required to complete the regeneration process of erasure codes, we propose a Tree-structured Parallel Regeneration (TPR) scheme for multiple data losses in distributed storage systems. Under the scheme, two algorithms are proposed for the construction of multiple regeneration trees, namely the edge-disjoint algorithm and edge-sharing algorithm. The edge-disjoint algorithm constructs multiple independent trees, and is simple and appropriate for environments where newcomers and their providers are distributed over a large area and have few intersections. The edge-sharing algorithm constructs multiple trees that compete to utilize the bandwidth, and make a better utilization of the bandwidth, although it needs to measure the available band-width and deal with the bandwidth changes; it is therefore difficult to implement in practical systems. The parallel regeneration for multiple data losses of TPR primarily includes two optimizations: firstly, transferring the data through the bandwidth optimized-paths in a pipe-line manner; secondly, executing data regeneration over multiple trees in parallel. To evaluate the proposal, we implement an event-based simulator and make a detailed comparison with some popular regeneration methods. The quantitative comparison results show that the use of TPR employing either the edge-disjoint algorithm or edge-sharing algorithm reduces the regeneration time significantly.展开更多
Satellite mobile system and space-airground integrated network have a prominent superiority in global coverage which plays a critical role in remote and non-land regions, as well as emergency communications. However, ...Satellite mobile system and space-airground integrated network have a prominent superiority in global coverage which plays a critical role in remote and non-land regions, as well as emergency communications. However, due to the gradual angle attenuations of the satellite antennas, it is difficult to achieve full frequency multiplex among different beams as terrestrial 5G network. Multi-color frequency reuse is widely adopted in both academic and industry. Beam hopping scheme has attracted the attention of researchers recently due to the allocation flexibility. In this paper, we focus on analyzing the performance benefits of beam hopping compared with multi-color frequency reuse scheme in non-uniform user and traffic distributions in satellite system. Aerial networks are also introduced to form a space-airground integrated network for coverage enhancement,and the capacity improvement is analyzed. Besides,additional improved techniques are provided to make comprehensive analysis and comparisons. Theoretical analysis and simulation results indicate that the beam hopping scheme has a prominent superiority in the system capacity compared with the traditional multicolor frequency reuse scheme in both satellite mobile system and future space-air-ground integrated network.展开更多
The coordinated optimization problem of the electricity-gas-heat integrated energy system(IES)has the characteristics of strong coupling,non-convexity,and nonlinearity.The centralized optimization method has a high co...The coordinated optimization problem of the electricity-gas-heat integrated energy system(IES)has the characteristics of strong coupling,non-convexity,and nonlinearity.The centralized optimization method has a high cost of communication and complex modeling.Meanwhile,the traditional numerical iterative solution cannot deal with uncertainty and solution efficiency,which is difficult to apply online.For the coordinated optimization problem of the electricity-gas-heat IES in this study,we constructed a model for the distributed IES with a dynamic distribution factor and transformed the centralized optimization problem into a distributed optimization problem in the multi-agent reinforcement learning environment using multi-agent deep deterministic policy gradient.Introducing the dynamic distribution factor allows the system to consider the impact of changes in real-time supply and demand on system optimization,dynamically coordinating different energy sources for complementary utilization and effectively improving the system economy.Compared with centralized optimization,the distributed model with multiple decision centers can achieve similar results while easing the pressure on system communication.The proposed method considers the dual uncertainty of renewable energy and load in the training.Compared with the traditional iterative solution method,it can better cope with uncertainty and realize real-time decision making of the system,which is conducive to the online application.Finally,we verify the effectiveness of the proposed method using an example of an IES coupled with three energy hub agents.展开更多
Distributed energy resources have been proven to be an effective and promising solution to enhance power system resilience and improve household-level reliability.In this paper,we propose a method to evaluate the reli...Distributed energy resources have been proven to be an effective and promising solution to enhance power system resilience and improve household-level reliability.In this paper,we propose a method to evaluate the reliability value of a photovoltaic(PV)energy system with a battery storage system(BSS)by considering the probability of grid outages causing household blackouts.Considering this reliability value,which is the economic profit and capital cost of PV+BSS,a simple formula is derived to calculate the optimal planning strategy.This strategy can provide household-level customers with a simple and straightforward expression for invested PV+BSS capacity.Case studies on 600 households located in eight zones of the US for the period of 2006 to 2015 demonstrate that adding the reliability value to economic profit allows households to invest in a larger PV+BSS and avoid loss of load caused by blackouts.Owing to the differences in blackout hours,households from the 8 zones express distinct willingness to install PV+BSS.The greater the probability of blackout,the greater revenue that household can get from the PV+BSS.The simulation example shows that the planning strategy obtained by proposed model has good economy in the actual operation and able to reduce the economic risk of power failure of the household users.This model can provide household with an easy and straightforward investment strategy of PV+BSS capacity.展开更多
基金supported by the National Key Research and Development Program of China(No.2022YFA1604703)the National Natural Science Foundation of China(No.12375189)the National Key Research and Development Program of China(No.2021YFA1601300)。
文摘Waveform generation and digitization play essential roles in numerous physics experiments.In traditional distributed systems for large-scale experiments,each frontend node contains an FPGA for data preprocessing,which interfaces with various data converters and exchanges data with a backend central processor.However,the streaming readout architecture has become a new paradigm for several experiments benefiting from advancements in data transmission and computing technologies.This paper proposes a scalable distributed waveform generation and digitization system that utilizes fiber optical connections for data transmission between frontend nodes and a central processor.By utilizing transparent transmission on top of the data link layer,the clock and data ports of the converters in the frontend nodes are directly mapped to the FPGA firmware at the backend.This streaming readout architecture reduces the complexity of frontend development and maintains the data conversion in proximity to the detector.Each frontend node uses a local clock for waveform digitization.To translate the timing information of events in each channel into the system clock domain within the backend central processing FPGA,a novel method is proposed and evaluated using a demonstrator system.
文摘As a matured technique used in many fields,the distributed computer system is still a new management method for the aeronautical electrical power distribution system in our country. In this paper, a novel aircraft electrical power distribution system based on the distributed computer system is proposed. The principles, features and structure of the aircraft electrical power distribution system and the distributed computer system named electrical load management system (ELMS) are studied. The ELMS composed of four electrical load management centers (ELMCs) and two power source processors (PSPs) operates in the 1553B buses. Principles of the ELMCs and the PSPs are introduced. With the application of the distributed computer system, the aircraft electrical power distribution system is simple, adaptable and flexible.
基金financial supports from the National Natural Science Foundation of China(NSFC)(No.61922033&U22A20206)Zhejiang Provincial Market Supervision Bureau Young Eagle Plan project under Grant CY2022228.
文摘Artificial intelligence(AI)plays a critical role in signal recognition of distributed sensor systems(DSS),boosting its applications in multiple monitoring fields.Due to the domain differences between massive sensors in signal acquisition conditions,such as manufacturing process,deployment,and environments,current AI schemes for signal recognition of DSS frequently encounter poor generalization performance.In this paper,an adaptive decentralized artificial intelligence(ADAI)method for signal recognition of DSS is proposed,to improve the entire generalization performance.By fine-tuning pre-trained model with the unlabeled data in each domain,the ADAI scheme can train a series of adaptive AI models for all target domains,significantly reducing the false alarm rate(FAR)and missing alarm rate(MAR)induced by domain differences.The field tests about intrusion signal recognition with distributed optical fiber sensors system demonstrate the efficacy of the ADAI scheme,showcasing a FAR of merely 4.3%and 0%,along with a MAR of only 1.4%and 2.7%within two specific target domains.The ADAI scheme is expected to offer a practical paradigm for signal recognition of DSS in multiple application fields.
基金Project supported by the National Natural Science Foundation of China (Grant No.62073045)。
文摘We develop a policy of observer-based dynamic event-triggered state feedback control for distributed parameter systems over a mobile sensor-plus-actuator network.It is assumed that the mobile sensing devices that provide spatially averaged state measurements can be used to improve state estimation in the network.For the purpose of decreasing the update frequency of controller and unnecessary sampled data transmission, an efficient dynamic event-triggered control policy is constructed.In an event-triggered system, when an error signal exceeds a specified time-varying threshold, it indicates the occurrence of a typical event.The global asymptotic stability of the event-triggered closed-loop system and the boundedness of the minimum inter-event time can be guaranteed.Based on the linear quadratic optimal regulator, the actuator selects the optimal displacement only when an event occurs.A simulation example is finally used to verify that the effectiveness of such a control strategy can enhance the system performance.
文摘Cell-free systems significantly improve network capacity by enabling joint user service without cell boundaries,eliminating intercell interference.However,to satisfy further capacity demands,it leads to high-cost problems of both hardware and power consumption.In this paper,we investigate multiple reconfigurable intelligent surfaces(RISs)aided cell-free systems where RISs are introduced to improve spectrum efficiency in an energy-efficient way.To overcome the centralized high complexity and avoid frequent information exchanges,a cooperative distributed beamforming design is proposed to maximize the weighted sum-rate performance.In particular,the alternating optimization method is utilized with the distributed closed-form solution of active beamforming being derived locally at access points,and phase shifts are obtained centrally based on the Riemannian conjugate gradient(RCG)manifold method.Simulation results verify the effectiveness of the proposed design whose performance is comparable to the centralized scheme and show great superiority of the RISs-aided system over the conventional cellular and cell-free system.
基金supported by Hainan Provincial Natural Science Foundation of China(No.524RC532)Research Startup Funding from Hainan Institute of Zhejiang University(No.0210-6602-A12202)Project of Sanya Yazhou Bay Science and Technology City(No.SKJC-2022-PTDX-009/010/011).
文摘Given the rapid development of advanced information systems,microgrids(MGs)suffer from more potential attacks that affect their operational performance.Conventional distributed secondary control with a small,fixed sampling time period inevitably causes the wasteful use of communication resources.This paper proposes a self-triggered secondary control scheme under perturbations from false data injection(FDI)attacks.We designed a linear clock for each DG to trigger its controller at aperiodic and intermittent instants.Sub-sequently,a hash-based defense mechanism(HDM)is designed for detecting and eliminating malicious data infiltrated in the MGs.With the aid of HDM,a self-triggered control scheme achieves the secondary control objectives even in the presence of FDI attacks.Rigorous theoretical analyses and simulation results indicate that the introduced secondary control scheme significantly reduces communication costs and enhances the resilience of MGs under FDI attacks.
基金supported by the National Key R&D Program of China under grant No.2021YFA0716800。
文摘Distributed acoustic sensing(DAS)is increasingly used in seismic exploration owing to its wide frequency range,dense sampling and real-time monitoring.DAS radiation patterns help to understand angle response of DAS records and improve the quality of inversion and imaging.In this paper,we solve the 3D vertical transverse isotropic(VTI)Christoffel equation and obtain the analytical,frst-order,and zero-order Taylor expansion solutions that represent P-,SV-,and SH-wave phase velocities and polarization vectors.These analytical and approximated solutions are used to build the P/S plane-wave expression identical to the far-feld term of seismic wave,from which the strain rate expressions are derived and DAS radiation patterns are thus extracted for anisotropic P/S waves.We observe that the gauge length and phase angle terms control the radiating intensity of DAS records.Additionally,the Bond transformation is adopted to derive the DAS radiation patterns in title transverse isotropic(TTI)media,which exhibits higher complexity than that of VTI media.Several synthetic examples demonstrate the feasibility and effectiveness of our theory.
基金supported by the Science and Technology Project of State Grid Sichuan Electric Power Company Chengdu Power Supply Company under Grant No.521904240005.
文摘This paper presents a novel approach to dynamic pricing and distributed energy management in virtual power plant(VPP)networks using multi-agent reinforcement learning(MARL).As the energy landscape evolves towards greater decentralization and renewable integration,traditional optimization methods struggle to address the inherent complexities and uncertainties.Our proposed MARL framework enables adaptive,decentralized decision-making for both the distribution system operator and individual VPPs,optimizing economic efficiency while maintaining grid stability.We formulate the problem as a Markov decision process and develop a custom MARL algorithm that leverages actor-critic architectures and experience replay.Extensive simulations across diverse scenarios demonstrate that our approach consistently outperforms baseline methods,including Stackelberg game models and model predictive control,achieving an 18.73%reduction in costs and a 22.46%increase in VPP profits.The MARL framework shows particular strength in scenarios with high renewable energy penetration,where it improves system performance by 11.95%compared with traditional methods.Furthermore,our approach demonstrates superior adaptability to unexpected events and mis-predictions,highlighting its potential for real-world implementation.
基金supported by the National Natural Science Foundation of China(Grant No.62072259)in part by the Natural Science Foundation of Jiangsu Province(Grant No.BK20221411)+1 种基金the PhD Start-up Fund of Nantong University(Grant No.23B03)the Postgraduate Research&Practice Innovation Program of School of Information Science and Technology,Nantong University(Grant No.NTUSISTPR2405).
文摘In the current noisy intermediate-scale quantum(NISQ)era,a single quantum processing unit(QPU)is insufficient to implement large-scale quantum algorithms;this has driven extensive research into distributed quantum computing(DQC).DQC involves the cooperative operation of multiple QPUs but is concurrently challenged by excessive communication complexity.To address this issue,this paper proposes a quantum circuit partitioning method based on spectral clustering.The approach transforms quantum circuits into weighted graphs and,through computation of the Laplacian matrix and clustering techniques,identifies candidate partition schemes that minimize the total weight of the cut.Additionally,a global gate search tree strategy is introduced to meticulously explore opportunities for merged transfer of global gates,thereby minimizing the transmission cost of distributed quantum circuits and selecting the optimal partition scheme from the candidates.Finally,the proposed method is evaluated through various comparative experiments.The experimental results demonstrate that spectral clustering-based partitioning exhibits robust stability and efficiency in runtime in quantum circuits of different scales.In experiments involving the quantum Fourier transform algorithm and Revlib quantum circuits,the transmission cost achieved by the global gate search tree strategy is significantly optimized.
基金supported by the Science and Technology Project of the State Grid Corporation of China(5400-202255158A-1-1-ZN).
文摘Frequent extreme disasters have led to frequent large-scale power outages in recent years.To quickly restore power,it is necessary to understand the damage information of the distribution network accurately.However,the public network communication system is easily damaged after disasters,causing the operation center to lose control of the distribution network.In this paper,we considered using satellites to transmit the distribution network data and focus on the resource scheduling problem of the satellite emergency communication system for the distribution network.Specifically,this paper first formulates the satellite beam-pointing problem and the accesschannel joint resource allocation problem.Then,this paper proposes the Priority-based Beam-pointing and Access-Channel joint optimization algorithm(PBAC),which uses convex optimization theory to solve the satellite beam pointing problem,and adopts the block coordinate descent method,Lagrangian dual method,and a greedy algorithm to solve the access-channel joint resource allocation problem,thereby obtaining the optimal resource scheduling scheme for the satellite network.Finally,this paper conducts comparative experiments with existing methods to verify the effec-tiveness of the proposed methods.The results show that the total weighted transmitted data of the proposed algorithm is increased by about 19.29∼26.29%compared with other algorithms.
基金Supported by the National Natural Science Foundation of China(91016017)the National Aviation Found of China(20115868009)~~
文摘The cooperative control and stability analysis problems for the multi-agent system with sampled com- munication are investigated. Distributed state feedback controllers are adopted for the cooperation of networked agents. A theorem in the form of linear matrix inequalities（LMI） is derived to analyze the system stability. An- other theorem in the form of optimization problem subject to LMI constraints is proposed to design the controller, and then the algorithm is presented. The simulation results verify the validity and the effectiveness of the pro- posed approach.
文摘An attempt has been made to develop a distributed software infrastructure model for onboard data fusion system simulation, which is also applied to netted radar systems, onboard distributed detection systems and advanced C3I systems. Two architectures are provided and verified: one is based on pure TCP/IP protocol and C/S model, and implemented with Winsock, the other is based on CORBA (common object request broker architecture). The performance of data fusion simulation system, i.e. reliability, flexibility and scalability, is improved and enhanced by two models. The study of them makes valuable explore on incorporating the distributed computation concepts into radar system simulation techniques.
文摘Fault tolerant ability is an important aspect for overall evaluation of distributed system(DS). This paper discusses three measures for the evaluation: node/edge connectivity, number of spanning trees and synthetic connectivity. A numerical example for illustration and analysis is given, and the synthetic connectivity measure presented by this paper is proved to be rational and satisfactory.
文摘Based on MATRIXx, a universal real-time visual distributed simulation system is developed. The system can receive different input data from network or local terminal. Application models in the simulation modules can automatically get such data to be analyzed and calculated, and then produce real-time simulation control information. Meanwhile, this paper designs relevant simulation components to implement the input and output data, which can guarantee the real-time and universal of the data transmission. Result of the experimental system shows that the real-time performance of the simulation is perfect.
基金supported in part by the National Science Foundation of China for Young Scholars under grant No.61201186The National Basic Research Program undergrant No.2012AA01A502+5 种基金National Natural Science Foundation of China under grant No.61201192National S&T Major Project under grant No.2014ZX03003003-002Tsinghua-HUAWEI Joint R&D on Soft Defined Protocol StackTsinghua-HUAWEI Joint Research on 5G Air Interface TechnicalTsinghua-Qualcom joint research programIndependent innovation on Future Virtualization Platform under grant No.015Z02-3
文摘Spectrum sharing for efficient reuse of licensed spectrum is an important concept for cognitive radio technologies.In a spectrum-sharing system(SSS),deploying the antennas in a distributed manner can offer a new spatial dimension for the efficient reuse of licensed frequency bands.To improve the whole performance of multiple secondary users(SUs),this paper addresses the problem of coordinated multi-SU spectrum sharing in a distributed antenna-based SSS.By adopting the Hungarian method,the primal decomposition method and pricing policy,we propose a coordinated multi-user transmission scheme,so as to maximize the sum-rate of SUs.Simulation results show that the proposed method can significantly enhance the system performance,and the computational complexity is low.
基金the National Renewable Energy Laboratory(NREL)operated by Alliance for Sustainable Energy,LLC,for the U.S.Department of Energy(DOE)under Contract No.DE-AC36-08GO28308the U.S.Department of Energy Office of Electricity AOP Distribution Grid Resilience Project.The views expressed in the article do not necessarily represent the views of the DOE or the U.S.Government.The U.S.Government retains and the publisher,by accepting the article for publication,acknowledges that the U.S.Government retains a nonexclusive,paid-up,irrevocable,worldwide license to publish or reproduce the published form of this work,or allow others to do so,for U.S.Government purposes.
文摘The rapid growth of distributed generator(DG)capacities has introduced additional controllable assets to improve the performance of distribution systems in terms of service restoration.Renewable DGs are of particular interest to utility companies,but the stochastic nature of intermittent renewable DGs could have a negative impact on the electric grid if they are not properly handled.In this study,we investigate distribution system service restoration using DGs as the primary power source,and we develop an effective approach to handle the uncertainty of renewable DGs under extreme conditions.The distribution system service restoration problem can be described as a mixed-integer second-order cone programming model by modifying the radial topology constraints and power flow equations.The uncertainty of renewable DGs will be modeled using a chance-constrained approach.Furthermore,the forecast errors and noises in real-time operation are solved using a novel model-free control algorithm that can automatically track the trajectory of real-time DG output.The proposed service restoration strategy and model-free control algorithm are validated using an IEEE 123-bus test system.
基金supported by the National Grand Fundamental Research of China (973 Program) under Grant No. 2011CB302601the National High Technology Research and Development of China (863 Program) under GrantNo. 2013AA01A213+2 种基金the National Natural Science Foundation of China under Grant No. 60873215the Natural Science Foundation for Distinguished Young Scholars of Hunan Province under Grant No. S2010J5050Specialized Research Fund for the Doctoral Program of Higher Education under Grant No. 20124307110015
文摘To reduce the time required to complete the regeneration process of erasure codes, we propose a Tree-structured Parallel Regeneration (TPR) scheme for multiple data losses in distributed storage systems. Under the scheme, two algorithms are proposed for the construction of multiple regeneration trees, namely the edge-disjoint algorithm and edge-sharing algorithm. The edge-disjoint algorithm constructs multiple independent trees, and is simple and appropriate for environments where newcomers and their providers are distributed over a large area and have few intersections. The edge-sharing algorithm constructs multiple trees that compete to utilize the bandwidth, and make a better utilization of the bandwidth, although it needs to measure the available band-width and deal with the bandwidth changes; it is therefore difficult to implement in practical systems. The parallel regeneration for multiple data losses of TPR primarily includes two optimizations: firstly, transferring the data through the bandwidth optimized-paths in a pipe-line manner; secondly, executing data regeneration over multiple trees in parallel. To evaluate the proposal, we implement an event-based simulator and make a detailed comparison with some popular regeneration methods. The quantitative comparison results show that the use of TPR employing either the edge-disjoint algorithm or edge-sharing algorithm reduces the regeneration time significantly.
基金the Natural Science Foundation of China under Grant 61801319Sichuan Science and Technology Program under Grant 2020JDJQ0061+1 种基金the Education Agency Project of Sichuan Province under Grant 18ZB0419the Sichuan University of Science and Engineering Talent Introduction Project under Grant 2020RC33。
文摘Satellite mobile system and space-airground integrated network have a prominent superiority in global coverage which plays a critical role in remote and non-land regions, as well as emergency communications. However, due to the gradual angle attenuations of the satellite antennas, it is difficult to achieve full frequency multiplex among different beams as terrestrial 5G network. Multi-color frequency reuse is widely adopted in both academic and industry. Beam hopping scheme has attracted the attention of researchers recently due to the allocation flexibility. In this paper, we focus on analyzing the performance benefits of beam hopping compared with multi-color frequency reuse scheme in non-uniform user and traffic distributions in satellite system. Aerial networks are also introduced to form a space-airground integrated network for coverage enhancement,and the capacity improvement is analyzed. Besides,additional improved techniques are provided to make comprehensive analysis and comparisons. Theoretical analysis and simulation results indicate that the beam hopping scheme has a prominent superiority in the system capacity compared with the traditional multicolor frequency reuse scheme in both satellite mobile system and future space-air-ground integrated network.
基金supported by The National Key R&D Program of China(2020YFB0905900):Research on artificial intelligence application of power internet of things.
文摘The coordinated optimization problem of the electricity-gas-heat integrated energy system(IES)has the characteristics of strong coupling,non-convexity,and nonlinearity.The centralized optimization method has a high cost of communication and complex modeling.Meanwhile,the traditional numerical iterative solution cannot deal with uncertainty and solution efficiency,which is difficult to apply online.For the coordinated optimization problem of the electricity-gas-heat IES in this study,we constructed a model for the distributed IES with a dynamic distribution factor and transformed the centralized optimization problem into a distributed optimization problem in the multi-agent reinforcement learning environment using multi-agent deep deterministic policy gradient.Introducing the dynamic distribution factor allows the system to consider the impact of changes in real-time supply and demand on system optimization,dynamically coordinating different energy sources for complementary utilization and effectively improving the system economy.Compared with centralized optimization,the distributed model with multiple decision centers can achieve similar results while easing the pressure on system communication.The proposed method considers the dual uncertainty of renewable energy and load in the training.Compared with the traditional iterative solution method,it can better cope with uncertainty and realize real-time decision making of the system,which is conducive to the online application.Finally,we verify the effectiveness of the proposed method using an example of an IES coupled with three energy hub agents.
基金supported by National Natural Science Foundation of China(Project 51907064)in part by China State Key Lab.of Power System(SKLD19KM09)in part by State Grid Corporation of China(1400202024222A-0-0-00)
文摘Distributed energy resources have been proven to be an effective and promising solution to enhance power system resilience and improve household-level reliability.In this paper,we propose a method to evaluate the reliability value of a photovoltaic(PV)energy system with a battery storage system(BSS)by considering the probability of grid outages causing household blackouts.Considering this reliability value,which is the economic profit and capital cost of PV+BSS,a simple formula is derived to calculate the optimal planning strategy.This strategy can provide household-level customers with a simple and straightforward expression for invested PV+BSS capacity.Case studies on 600 households located in eight zones of the US for the period of 2006 to 2015 demonstrate that adding the reliability value to economic profit allows households to invest in a larger PV+BSS and avoid loss of load caused by blackouts.Owing to the differences in blackout hours,households from the 8 zones express distinct willingness to install PV+BSS.The greater the probability of blackout,the greater revenue that household can get from the PV+BSS.The simulation example shows that the planning strategy obtained by proposed model has good economy in the actual operation and able to reduce the economic risk of power failure of the household users.This model can provide household with an easy and straightforward investment strategy of PV+BSS capacity.
