In this paper, we adopt Java platform to achieve a multi-tier distributed object enterprise computing model which provides an open, flexible, robust and cross-platform standard for enterprise applications of new gener...In this paper, we adopt Java platform to achieve a multi-tier distributed object enterprise computing model which provides an open, flexible, robust and cross-platform standard for enterprise applications of new generation. In addition to this model, we define remote server objects as session or entity objects according to their roles in a distributed application server, which separate information details from business operations for software reuse. A web store system is implement by using this multi-tier distributed object enterprise computing model.展开更多
With the increasing popularity of blockchain applications, the security of data sources on the blockchain is gradually receiving attention. Providing reliable data for the blockchain safely and efficiently has become ...With the increasing popularity of blockchain applications, the security of data sources on the blockchain is gradually receiving attention. Providing reliable data for the blockchain safely and efficiently has become a research hotspot, and the security of the oracle responsible for providing reliable data has attracted much attention. The most widely used centralized oracles in blockchain, such as Provable and Town Crier, all rely on a single oracle to obtain data, which suffers from a single point of failure and limits the large-scale development of blockchain. To this end, the distributed oracle scheme is put forward, but the existing distributed oracle schemes such as Chainlink and Augur generally have low execution efficiency and high communication overhead, which leads to their poor applicability. To solve the above problems, this paper proposes a trusted distributed oracle scheme based on a share recovery threshold signature. First, a data verification method of distributed oracles is designed based on threshold signature. By aggregating the signatures of oracles, data from different data sources can be mutually verified, leading to a more efficient data verification and aggregation process. Then, a credibility-based cluster head election algorithm is designed, which reduces the communication overhead by clarifying the function distribution and building a hierarchical structure. Considering the good performance of the BLS threshold signature in large-scale applications, this paper combines it with distributed oracle technology and proposes a BLS threshold signature algorithm that supports share recovery in distributed oracles. The share recovery mechanism enables the proposed scheme to solve the key loss issue, and the setting of the threshold value enables the proposed scheme to complete signature aggregation with only a threshold number of oracles, making the scheme more robust. Finally, experimental results indicate that, by using the threshold signature technology and the cluster head election algorithm, our scheme effectively improves the execution efficiency of oracles and solves the problem of a single point of failure, leading to higher scalability and robustness.展开更多
With the increasing integration of large-scale distributed energy resources into the grid,traditional distribution network optimization and dispatch methods struggle to address the challenges posed by both generation ...With the increasing integration of large-scale distributed energy resources into the grid,traditional distribution network optimization and dispatch methods struggle to address the challenges posed by both generation and load.Accounting for these issues,this paper proposes a multi-timescale coordinated optimization dispatch method for distribution networks.First,the probability box theory was employed to determine the uncertainty intervals of generation and load forecasts,based on which,the requirements for flexibility dispatch and capacity constraints of the grid were calculated and analyzed.Subsequently,a multi-timescale optimization framework was constructed,incorporating the generation and load forecast uncertainties.This framework included optimization models for dayahead scheduling,intra-day optimization,and real-time adjustments,aiming to meet flexibility needs across different timescales and improve the economic efficiency of the grid.Furthermore,an improved soft actor-critic algorithm was introduced to enhance the uncertainty exploration capability.Utilizing a centralized training and decentralized execution framework,a multi-agent SAC network model was developed to improve the decision-making efficiency of the agents.Finally,the effectiveness and superiority of the proposed method were validated using a modified IEEE-33 bus test system.展开更多
After a century of relative stability in the electricity sector,the widespread adoption of distributed energy resources,along with recent advancements in computing and communication technologies,has fundamentally alte...After a century of relative stability in the electricity sector,the widespread adoption of distributed energy resources,along with recent advancements in computing and communication technologies,has fundamentally altered how energy is consumed,traded,and utilized.This change signifies a crucial shift as the power system evolves from its traditional hierarchical organization to a more decentralized approach.At the heart of this transformation are innovative energy distribution models,like peer-to-peer(P2P)sharing,which enable communities to collaboratively manage their energy resources.The effectiveness of P2P sharing not only improves the economic prospects for prosumers,who generate and consume energy,but also enhances energy resilience and sustainability.This allows communities to better leverage local resources while fostering a sense of collective responsibility and collaboration in energy management.However,there is still no extensive implementation of such sharing models in today’s electricitymarkets.Research on distributed energy P2P trading is still in the exploratory stage,and it is particularly important to comprehensively understand and analyze the existing distributed energy P2P trading market.This paper contributes with an overview of the P2P markets that starts with the network framework,market structure,technical approach for trading mechanism,and blockchain technology,moving to the outlook in this field.展开更多
The distributed permutation flow shop scheduling problem(DPFSP)has received increasing attention in recent years.The iterated greedy algorithm(IGA)serves as a powerful optimizer for addressing such a problem because o...The distributed permutation flow shop scheduling problem(DPFSP)has received increasing attention in recent years.The iterated greedy algorithm(IGA)serves as a powerful optimizer for addressing such a problem because of its straightforward,single-solution evolution framework.However,a potential draw-back of IGA is the lack of utilization of historical information,which could lead to an imbalance between exploration and exploitation,especially in large-scale DPFSPs.As a consequence,this paper develops an IGA with memory and learning mechanisms(MLIGA)to efficiently solve the DPFSP targeted at the mini-malmakespan.InMLIGA,we incorporate a memory mechanism to make a more informed selection of the initial solution at each stage of the search,by extending,reconstructing,and reinforcing the information from previous solutions.In addition,we design a twolayer cooperative reinforcement learning approach to intelligently determine the key parameters of IGA and the operations of the memory mechanism.Meanwhile,to ensure that the experience generated by each perturbation operator is fully learned and to reduce the prior parameters of MLIGA,a probability curve-based acceptance criterion is proposed by combining a cube root function with custom rules.At last,a discrete adaptive learning rate is employed to enhance the stability of the memory and learningmechanisms.Complete ablation experiments are utilized to verify the effectiveness of the memory mechanism,and the results show that this mechanism is capable of improving the performance of IGA to a large extent.Furthermore,through comparative experiments involving MLIGA and five state-of-the-art algorithms on 720 benchmarks,we have discovered that MLI-GA demonstrates significant potential for solving large-scale DPFSPs.This indicates that MLIGA is well-suited for real-world distributed flow shop scheduling.展开更多
In this paper,we investigate the periodic traveling wave solutions problem for a single population model with advection and distributed delay.By the bifurcation analysis method,we can obtain periodic traveling wave so...In this paper,we investigate the periodic traveling wave solutions problem for a single population model with advection and distributed delay.By the bifurcation analysis method,we can obtain periodic traveling wave solutions for this model under the influence of advection term and distributed delay.The obtained results indicate that weak kernel and strong kernel can both deduce the existence of periodic traveling wave solutions.Finally,we apply the main results in this paper to Logistic model and Nicholson’s blowflies model.展开更多
Energy access remains a critical challenge in rural South Sudan,with communities heavily relying on expensive and unfriendly environmental energy sources such as diesel generators and biomass.This study addresses the ...Energy access remains a critical challenge in rural South Sudan,with communities heavily relying on expensive and unfriendly environmental energy sources such as diesel generators and biomass.This study addresses the predicament by evaluating the feasibility of renewable energy-based decentralized electrification in the selected village ofDoleibHill,UpperNile,South Sudan.Using a demand assessment and theMulti-Tier Framework(MTF)approach,it categorizes households,public facilities,private sector,Non-GovernmentalOrganizations(NGOs)and business energy needs and designs an optimized hybrid energy system incorporating solar Photovoltaic(PV),wind turbines,batteries,and a generator.The proposed system,simulated in Hybrid Optimization Model Electric Renewable(HOMER)Pro,demonstrates strong economic viability,with a present worth of$292,145,an annual worth of$22,854,a return on investment(ROI)of 36.5%,and an internal rate of return(IRR)of 42.1%.The simple payback period is 2.31 years,and the discounted payback period is 2.62 years.The system achieves a levelized cost of energy(LCOE)of$0.276/kWh and significantly reduces dependence on diesel,producing 798,800 kWh annually fromwind energy.This research provides a replicable model for cost-effective,sustainable rural electrification,offering valuable insights for policymakers and energy planners seeking to expand electricity access in off-grid communities.展开更多
The word“spatial”fundamentally relates to human existence,evolution,and activity in terrestrial and even celestial spaces.After reviewing the spatial features of many areas,the paper describes basics of high level m...The word“spatial”fundamentally relates to human existence,evolution,and activity in terrestrial and even celestial spaces.After reviewing the spatial features of many areas,the paper describes basics of high level model and technology called Spatial Grasp for dealing with large distributed systems,which can provide spatial vision,awareness,management,control,and even consciousness.The technology description includes its key Spatial Grasp Language(SGL),self-evolution of recursive SGL scenarios,and implementation of SGL interpreter converting distributed networked systems into powerful spatial engines.Examples of typical spatial scenarios in SGL include finding shortest path tree and shortest path between network nodes,collecting proper information throughout the whole world,elimination of multiple targets by intelligent teams of chasers,and withstanding cyber attacks in distributed networked systems.Also this paper compares Spatial Grasp model with traditional algorithms,confirming universality of the former for any spatial systems,while the latter just tools for concrete applications.展开更多
Fraction repetition(FR)codes are integral in distributed storage systems(DSS)with exact repair-by-transfer,while pliable fraction repetition codes are vital for DSSs in which both the per-node storage and repetition d...Fraction repetition(FR)codes are integral in distributed storage systems(DSS)with exact repair-by-transfer,while pliable fraction repetition codes are vital for DSSs in which both the per-node storage and repetition degree can easily be adjusted simultaneously.This paper introduces a new type of pliable FR codes,called absolute balanced pliable FR(ABPFR)codes,in which the access balancing in DSS is considered.Additionally,the equivalence between pliable FR codes and resolvable transversal packings in combinatorial design theory is presented.Then constructions of pliable FR codes and ABPFR codes based on resolvable transversal packings are presented.展开更多
Dear Editor,This letter presents a solution to the problem of seeking Nash equilibrium(NE)in a class of non-cooperative games of multi-agent systems(MASs)subject to the input disturbance and the networked communicatio...Dear Editor,This letter presents a solution to the problem of seeking Nash equilibrium(NE)in a class of non-cooperative games of multi-agent systems(MASs)subject to the input disturbance and the networked communication.To this end,a novel distributed robust predefined-time algorithm is proposed,which ensures the precise convergence of agent states to the NE within a settling time that can be directly determined by adjusting one or more parameters.The proposed algorithm employs an integral sliding mode strategy to effectively reject disturbances.Additionally,a consensus-based estimator is designed to overcome the challenge of limited information availability,where each agent can only access information from its directly connected neighbors,which conflicts with the computation of the cost function that requires information from all agents.Finally,a numerical example is provided to demonstrate the algorithm's effectiveness and performance.展开更多
Reconfiguration,as well as optimal utilization of distributed generation sources and capacitor banks,are highly effective methods for reducing losses and improving the voltage profile,or in other words,the power quali...Reconfiguration,as well as optimal utilization of distributed generation sources and capacitor banks,are highly effective methods for reducing losses and improving the voltage profile,or in other words,the power quality in the power distribution system.Researchers have considered the use of distributed generation resources in recent years.There are numerous advantages to utilizing these resources,the most significant of which are the reduction of network losses and enhancement of voltage stability.Non-dominated Sorting Genetic Algorithm II(NSGA-II),Multi-Objective Particle Swarm Optimization(MOPSO),and Intersect Mutation Differential Evolution(IMDE)algorithms are used in this paper to perform optimal reconfiguration,simultaneous location,and capacity determination of distributed generation resources and capacitor banks.Three scenarios were used to replicate the studies.The reconfiguration of the switches,as well as the location and determination of the capacitor bank’s optimal capacity,were investigated in this scenario.However,in the third scenario,reconfiguration,and determining the location and capacity of the Distributed Generation(DG)resources and capacitor banks have been carried out simultaneously.Finally,the simulation results of these three algorithms are compared.The results indicate that the proposed NSGAII algorithm outperformed the other two multi-objective algorithms and was capable of maintaining smaller objective functions in all scenarios.Specifically,the energy losses were reduced from 211 to 51.35 kW(a 75.66%reduction),119.13 kW(a 43.54%reduction),and 23.13 kW(an 89.04%reduction),while the voltage stability index(VSI)decreased from 6.96 to 2.105,1.239,and 1.257,respectively,demonstrating significant improvement in the voltage profile.展开更多
Understanding the evolutionary processes that influence the distribution of genetic diversity in natural populations is a key issue in evolutionary biology. Both species' distribution ranges and environmental grad...Understanding the evolutionary processes that influence the distribution of genetic diversity in natural populations is a key issue in evolutionary biology. Both species' distribution ranges and environmental gradients can influence this diversity through mechanisms such as gene flow, selection, and genetic drift. To explore how these forces interact, we assessed neutral and adaptive genetic variation in three widely distributed and two narrowly distributed bird species co-occurring along the Cauca River canyon in Antioquia, Colombia—a region of pronounced environmental heterogeneity. We sampled individuals across eight sites spanning the canyon's gradient and analyzed genetic diversity and structure using microsatellites and toll-like receptors (TLRs), a gene family involved in innate immunity. Widely distributed species consistently exhibited higher genetic diversity at both marker types compared to their narrowly distributed counterparts. Although we did not find a significant relationship between microsatellite heterozygosity and TLR heterozygosity, we evidenced a negative trend for widely distributed species and a positive trend for narrowly distributed species. This result suggests that there is a stronger effect of genetic drift in narrowly distributed species. Our results highlight the role of distribution range in maintaining genetic diversity and suggest that environmental gradients, by interacting with gene flow and selection, may influence patterns of adaptive variation.展开更多
Dear Editor,This letter studies the distributed Nash equilibrium seeking problem of aggregative game,in which the decision of each player obeys second-order dynamics and is constrained by nonidentical convex sets.To s...Dear Editor,This letter studies the distributed Nash equilibrium seeking problem of aggregative game,in which the decision of each player obeys second-order dynamics and is constrained by nonidentical convex sets.To seek the generalized Nash equilibrium(GNE),a projectionbased distributed algorithm via constant step-sizes is developed with linear convergence.In particular,a variable tracking technique is incorporated to estimate the aggregative function,and an event-triggered mechanism is designed to reduce the communication cost.Finally,a numerical example demonstrates the theoretical results.展开更多
The petal-shaped distribution network has high power supply reliability.However,the closed-loop operation mode and the access of inverter-interfaced distributed generators(IIDGs)bring great challenges to the protectio...The petal-shaped distribution network has high power supply reliability.However,the closed-loop operation mode and the access of inverter-interfaced distributed generators(IIDGs)bring great challenges to the protection schemes.The current amplitude differential protection is an effective means to solve this problem,but the existing criterions rarely consider both sensitivity to high-resistance faults and low requirements for data synchronization.Therefore,the general variation laws of the amplitude difference between the current steady-state components at both terminals and the phase differences between current fault components at both terminals are revealed.For external faults,the steady-state-component current amplitude difference is around zero and the fault-component current phase difference is around 180◦.For internal faults,either the amplitude difference is large or the phase difference is small.Accordingly,a current differential protection scheme based on the pre-fault and postfault steady-state current is proposed.The amplitude and phase of current at both terminals of the protected line are required in the proposed scheme,which has low requirements for data synchronization.The simulation results show that the proposed protection scheme is not affected by the fault type,position,resistance and capacity of the IIDGs.It can also be applied to radial distribution networks with IIDGs.展开更多
Curved geostructures,such as tunnels,are commonly encountered in geotechnical engineering and are critical to maintaining structural stability.Ensuring their proper performance through field monitoring during their se...Curved geostructures,such as tunnels,are commonly encountered in geotechnical engineering and are critical to maintaining structural stability.Ensuring their proper performance through field monitoring during their service life is essential for the overall functionality of geotechnical infrastructure.Distributed Brillouin sensing(DBS)is increasingly applied in geotechnical projects due to its ability to acquire spatially continuous strain and temperature distributions over distances of up to 150 km using a single optical fibre.However,limited by the complex operations of distributed optic fibre sensing(DFOS)sensors in curved structures,previous reports about exploiting DBS in geotechnical structural health monitoring(SHM)have mostly been focused on flat surfaces.The lack of suitable DFOS installation methods matched to the spatial characteristics of continuous monitoring is one of the major factors that hinder the further application of this technique in curved structures.This review paper starts with a brief introduction of the fundamental working principle of DBS and the inherent limitations of DBS being used on monitoring curved surfaces.Subsequently,the state-of-the-art installation methods of optical fibres in curved structures are reviewed and compared to address the most suitable scenario of each method and their advantages and disadvantages.The installation challenges of optical fibres that can highly affect measurement accuracy are also discussed in the paper.展开更多
To generate a neutron beam exhibiting a Maxwellian energy distribution with narrow emission angles for measuring the neutron capture reaction rates of the s-process nuclides,a monoenergetic 3.4 MeV proton beam produce...To generate a neutron beam exhibiting a Maxwellian energy distribution with narrow emission angles for measuring the neutron capture reaction rates of the s-process nuclides,a monoenergetic 3.4 MeV proton beam produced by the tandem-accelerator in the China Institute of Atomic Energy was utilized.The proton beam was first transmitted through a 60.5μm aluminum foil and then impinged on a natural LiF target to produce neutron beam via^(7)Li(p,n)7Be reaction.The quasi-Gaussian energy distribution of protons in the LiF target resulted in neutron energy spectra that agreed with a Maxwellian energy distribution at kT=(22±2)keV,which was achieved by integrating neutrons detected within an emission angle of 65.0°±2.6°using a ^(6)Li glass detector positioned at 65°relative to the proton beam direction.The narrow angular spread of the Maxwelliandistributed neutron beam enables direct measurement of neutron capture cross-sections for most s-process nuclides,overcoming previous experimental limitations associated with broad angular distributions.展开更多
Dear Editor,The letter deals with the distributed state and fault estimation of the whole physical layer for cyber-physical systems(CPSs) when the cyber layer suffers from DoS attacks. With the advancement of embedded...Dear Editor,The letter deals with the distributed state and fault estimation of the whole physical layer for cyber-physical systems(CPSs) when the cyber layer suffers from DoS attacks. With the advancement of embedded computing, communication and related hardware technologies, CPSs have attracted extensive attention and have been widely used in power system, traffic network, refrigeration system and other fields.展开更多
This article proposes a multi-tiered fault detection system for series-connected lithium-ion battery modules.Improper use of batteries can lead to electrolyte decomposition,resulting in the formation of lithium dendri...This article proposes a multi-tiered fault detection system for series-connected lithium-ion battery modules.Improper use of batteries can lead to electrolyte decomposition,resulting in the formation of lithium dendrites.These dendrites may pierce the separator,leading to the failure of the insulation layer between electrodes and causing micro short circuits.When a micro short circuit occurs,the electrolyte typically undergoes exothermic reactions,leading to thermal runaway and posing a safety risk to users.Relying solely on temperature-based judgment mechanisms within the battery management system often results in delayed intervention.To address this issue,the article develops a multi-tiered fault detection algorithm for series-connected lithium-ion batteries.This algorithm can effectively diagnose micro short circuits,aging,and normal batteries using minimal battery data,thereby improving diagnostic accuracy and enhancing the flexibility of fault detection.Simulations and experiments conducted under various levels of micro short circuits validate the effectiveness of the algorithm,demonstrating its ability to distinguish between short-circuited,aged,and normal batteries under different conditions.This technology can be applied to electric vehicles and energy storage systems,enabling early warnings to ensure safety and prevent thermal runaway.展开更多
Dear Editor,This letter addresses distributed optimization for resource allocation problems with time-varying objective functions and time-varying constraints.Inspired by the distributed average tracking(DAT)approach,...Dear Editor,This letter addresses distributed optimization for resource allocation problems with time-varying objective functions and time-varying constraints.Inspired by the distributed average tracking(DAT)approach,a distributed control protocol is proposed for optimal resource allocation.The convergence to a time-varying optimal solution within a predefined time is proved.Two numerical examples are given to illustrate the effectiveness of the proposed approach.展开更多
A distributed bearing-only target tracking algorithm based on variational Bayesian inference(VBI)under random measurement anomalies is proposed for the problem of adverse effect of random measurement anomalies on the ...A distributed bearing-only target tracking algorithm based on variational Bayesian inference(VBI)under random measurement anomalies is proposed for the problem of adverse effect of random measurement anomalies on the state estimation accuracy of moving targets in bearing-only tracking scenarios.Firstly,the measurement information of each sensor is complemented by using triangulation under the distributed framework.Secondly,the Student-t distribution is selected to model the measurement likelihood probability density function,and the joint posteriori probability density function of the estimated variables is approximately decoupled by VBI.Finally,the estimation results of each local filter are sent to the fusion center and fed back to each local filter.The simulation results show that the proposed distributed bearing-only target tracking algorithm based on VBI in the presence of abnormal measurement noise comprehensively considers the influence of system nonlinearity and random anomaly of measurement noise,and has higher estimation accuracy and robustness than other existing algorithms in the above scenarios.展开更多
文摘In this paper, we adopt Java platform to achieve a multi-tier distributed object enterprise computing model which provides an open, flexible, robust and cross-platform standard for enterprise applications of new generation. In addition to this model, we define remote server objects as session or entity objects according to their roles in a distributed application server, which separate information details from business operations for software reuse. A web store system is implement by using this multi-tier distributed object enterprise computing model.
基金supported by the National Natural Science Foundation of China(Grant No.62102449)the Central Plains Talent Program under Grant No.224200510003.
文摘With the increasing popularity of blockchain applications, the security of data sources on the blockchain is gradually receiving attention. Providing reliable data for the blockchain safely and efficiently has become a research hotspot, and the security of the oracle responsible for providing reliable data has attracted much attention. The most widely used centralized oracles in blockchain, such as Provable and Town Crier, all rely on a single oracle to obtain data, which suffers from a single point of failure and limits the large-scale development of blockchain. To this end, the distributed oracle scheme is put forward, but the existing distributed oracle schemes such as Chainlink and Augur generally have low execution efficiency and high communication overhead, which leads to their poor applicability. To solve the above problems, this paper proposes a trusted distributed oracle scheme based on a share recovery threshold signature. First, a data verification method of distributed oracles is designed based on threshold signature. By aggregating the signatures of oracles, data from different data sources can be mutually verified, leading to a more efficient data verification and aggregation process. Then, a credibility-based cluster head election algorithm is designed, which reduces the communication overhead by clarifying the function distribution and building a hierarchical structure. Considering the good performance of the BLS threshold signature in large-scale applications, this paper combines it with distributed oracle technology and proposes a BLS threshold signature algorithm that supports share recovery in distributed oracles. The share recovery mechanism enables the proposed scheme to solve the key loss issue, and the setting of the threshold value enables the proposed scheme to complete signature aggregation with only a threshold number of oracles, making the scheme more robust. Finally, experimental results indicate that, by using the threshold signature technology and the cluster head election algorithm, our scheme effectively improves the execution efficiency of oracles and solves the problem of a single point of failure, leading to higher scalability and robustness.
基金funded by Jilin Province Science and Technology Development Plan Project,grant number 20220203163SF.
文摘With the increasing integration of large-scale distributed energy resources into the grid,traditional distribution network optimization and dispatch methods struggle to address the challenges posed by both generation and load.Accounting for these issues,this paper proposes a multi-timescale coordinated optimization dispatch method for distribution networks.First,the probability box theory was employed to determine the uncertainty intervals of generation and load forecasts,based on which,the requirements for flexibility dispatch and capacity constraints of the grid were calculated and analyzed.Subsequently,a multi-timescale optimization framework was constructed,incorporating the generation and load forecast uncertainties.This framework included optimization models for dayahead scheduling,intra-day optimization,and real-time adjustments,aiming to meet flexibility needs across different timescales and improve the economic efficiency of the grid.Furthermore,an improved soft actor-critic algorithm was introduced to enhance the uncertainty exploration capability.Utilizing a centralized training and decentralized execution framework,a multi-agent SAC network model was developed to improve the decision-making efficiency of the agents.Finally,the effectiveness and superiority of the proposed method were validated using a modified IEEE-33 bus test system.
基金funded by the National Natural Science Foundation of China(52167013)the Key Program of Natural Science Foundation of Gansu Province(24JRRA225)Natural Science Foundation of Gansu Province(23JRRA891).
文摘After a century of relative stability in the electricity sector,the widespread adoption of distributed energy resources,along with recent advancements in computing and communication technologies,has fundamentally altered how energy is consumed,traded,and utilized.This change signifies a crucial shift as the power system evolves from its traditional hierarchical organization to a more decentralized approach.At the heart of this transformation are innovative energy distribution models,like peer-to-peer(P2P)sharing,which enable communities to collaboratively manage their energy resources.The effectiveness of P2P sharing not only improves the economic prospects for prosumers,who generate and consume energy,but also enhances energy resilience and sustainability.This allows communities to better leverage local resources while fostering a sense of collective responsibility and collaboration in energy management.However,there is still no extensive implementation of such sharing models in today’s electricitymarkets.Research on distributed energy P2P trading is still in the exploratory stage,and it is particularly important to comprehensively understand and analyze the existing distributed energy P2P trading market.This paper contributes with an overview of the P2P markets that starts with the network framework,market structure,technical approach for trading mechanism,and blockchain technology,moving to the outlook in this field.
基金supported in part by the National Key Research and Development Program of China under Grant No.2021YFF0901300in part by the National Natural Science Foundation of China under Grant Nos.62173076 and 72271048.
文摘The distributed permutation flow shop scheduling problem(DPFSP)has received increasing attention in recent years.The iterated greedy algorithm(IGA)serves as a powerful optimizer for addressing such a problem because of its straightforward,single-solution evolution framework.However,a potential draw-back of IGA is the lack of utilization of historical information,which could lead to an imbalance between exploration and exploitation,especially in large-scale DPFSPs.As a consequence,this paper develops an IGA with memory and learning mechanisms(MLIGA)to efficiently solve the DPFSP targeted at the mini-malmakespan.InMLIGA,we incorporate a memory mechanism to make a more informed selection of the initial solution at each stage of the search,by extending,reconstructing,and reinforcing the information from previous solutions.In addition,we design a twolayer cooperative reinforcement learning approach to intelligently determine the key parameters of IGA and the operations of the memory mechanism.Meanwhile,to ensure that the experience generated by each perturbation operator is fully learned and to reduce the prior parameters of MLIGA,a probability curve-based acceptance criterion is proposed by combining a cube root function with custom rules.At last,a discrete adaptive learning rate is employed to enhance the stability of the memory and learningmechanisms.Complete ablation experiments are utilized to verify the effectiveness of the memory mechanism,and the results show that this mechanism is capable of improving the performance of IGA to a large extent.Furthermore,through comparative experiments involving MLIGA and five state-of-the-art algorithms on 720 benchmarks,we have discovered that MLI-GA demonstrates significant potential for solving large-scale DPFSPs.This indicates that MLIGA is well-suited for real-world distributed flow shop scheduling.
基金Supported by the National Natural Science Foundation of China(12261050)Science and Technology Project of Department of Education of Jiangxi Province(GJJ2201612 and GJJ211027)Natural Science Foundation of Jiangxi Province of China(20212BAB202021)。
文摘In this paper,we investigate the periodic traveling wave solutions problem for a single population model with advection and distributed delay.By the bifurcation analysis method,we can obtain periodic traveling wave solutions for this model under the influence of advection term and distributed delay.The obtained results indicate that weak kernel and strong kernel can both deduce the existence of periodic traveling wave solutions.Finally,we apply the main results in this paper to Logistic model and Nicholson’s blowflies model.
文摘Energy access remains a critical challenge in rural South Sudan,with communities heavily relying on expensive and unfriendly environmental energy sources such as diesel generators and biomass.This study addresses the predicament by evaluating the feasibility of renewable energy-based decentralized electrification in the selected village ofDoleibHill,UpperNile,South Sudan.Using a demand assessment and theMulti-Tier Framework(MTF)approach,it categorizes households,public facilities,private sector,Non-GovernmentalOrganizations(NGOs)and business energy needs and designs an optimized hybrid energy system incorporating solar Photovoltaic(PV),wind turbines,batteries,and a generator.The proposed system,simulated in Hybrid Optimization Model Electric Renewable(HOMER)Pro,demonstrates strong economic viability,with a present worth of$292,145,an annual worth of$22,854,a return on investment(ROI)of 36.5%,and an internal rate of return(IRR)of 42.1%.The simple payback period is 2.31 years,and the discounted payback period is 2.62 years.The system achieves a levelized cost of energy(LCOE)of$0.276/kWh and significantly reduces dependence on diesel,producing 798,800 kWh annually fromwind energy.This research provides a replicable model for cost-effective,sustainable rural electrification,offering valuable insights for policymakers and energy planners seeking to expand electricity access in off-grid communities.
文摘The word“spatial”fundamentally relates to human existence,evolution,and activity in terrestrial and even celestial spaces.After reviewing the spatial features of many areas,the paper describes basics of high level model and technology called Spatial Grasp for dealing with large distributed systems,which can provide spatial vision,awareness,management,control,and even consciousness.The technology description includes its key Spatial Grasp Language(SGL),self-evolution of recursive SGL scenarios,and implementation of SGL interpreter converting distributed networked systems into powerful spatial engines.Examples of typical spatial scenarios in SGL include finding shortest path tree and shortest path between network nodes,collecting proper information throughout the whole world,elimination of multiple targets by intelligent teams of chasers,and withstanding cyber attacks in distributed networked systems.Also this paper compares Spatial Grasp model with traditional algorithms,confirming universality of the former for any spatial systems,while the latter just tools for concrete applications.
基金Supported in part by the National Key R&D Program of China(No.2020YFA0712300)NSFC(No.61872353)。
文摘Fraction repetition(FR)codes are integral in distributed storage systems(DSS)with exact repair-by-transfer,while pliable fraction repetition codes are vital for DSSs in which both the per-node storage and repetition degree can easily be adjusted simultaneously.This paper introduces a new type of pliable FR codes,called absolute balanced pliable FR(ABPFR)codes,in which the access balancing in DSS is considered.Additionally,the equivalence between pliable FR codes and resolvable transversal packings in combinatorial design theory is presented.Then constructions of pliable FR codes and ABPFR codes based on resolvable transversal packings are presented.
基金supported by the National Natural Science Foundation of China(62373162,U24A20268,624B2055).
文摘Dear Editor,This letter presents a solution to the problem of seeking Nash equilibrium(NE)in a class of non-cooperative games of multi-agent systems(MASs)subject to the input disturbance and the networked communication.To this end,a novel distributed robust predefined-time algorithm is proposed,which ensures the precise convergence of agent states to the NE within a settling time that can be directly determined by adjusting one or more parameters.The proposed algorithm employs an integral sliding mode strategy to effectively reject disturbances.Additionally,a consensus-based estimator is designed to overcome the challenge of limited information availability,where each agent can only access information from its directly connected neighbors,which conflicts with the computation of the cost function that requires information from all agents.Finally,a numerical example is provided to demonstrate the algorithm's effectiveness and performance.
文摘Reconfiguration,as well as optimal utilization of distributed generation sources and capacitor banks,are highly effective methods for reducing losses and improving the voltage profile,or in other words,the power quality in the power distribution system.Researchers have considered the use of distributed generation resources in recent years.There are numerous advantages to utilizing these resources,the most significant of which are the reduction of network losses and enhancement of voltage stability.Non-dominated Sorting Genetic Algorithm II(NSGA-II),Multi-Objective Particle Swarm Optimization(MOPSO),and Intersect Mutation Differential Evolution(IMDE)algorithms are used in this paper to perform optimal reconfiguration,simultaneous location,and capacity determination of distributed generation resources and capacitor banks.Three scenarios were used to replicate the studies.The reconfiguration of the switches,as well as the location and determination of the capacitor bank’s optimal capacity,were investigated in this scenario.However,in the third scenario,reconfiguration,and determining the location and capacity of the Distributed Generation(DG)resources and capacitor banks have been carried out simultaneously.Finally,the simulation results of these three algorithms are compared.The results indicate that the proposed NSGAII algorithm outperformed the other two multi-objective algorithms and was capable of maintaining smaller objective functions in all scenarios.Specifically,the energy losses were reduced from 211 to 51.35 kW(a 75.66%reduction),119.13 kW(a 43.54%reduction),and 23.13 kW(an 89.04%reduction),while the voltage stability index(VSI)decreased from 6.96 to 2.105,1.239,and 1.257,respectively,demonstrating significant improvement in the voltage profile.
基金funded by the Empresas Públicas de Medellín and Universidad de Antioquia.
文摘Understanding the evolutionary processes that influence the distribution of genetic diversity in natural populations is a key issue in evolutionary biology. Both species' distribution ranges and environmental gradients can influence this diversity through mechanisms such as gene flow, selection, and genetic drift. To explore how these forces interact, we assessed neutral and adaptive genetic variation in three widely distributed and two narrowly distributed bird species co-occurring along the Cauca River canyon in Antioquia, Colombia—a region of pronounced environmental heterogeneity. We sampled individuals across eight sites spanning the canyon's gradient and analyzed genetic diversity and structure using microsatellites and toll-like receptors (TLRs), a gene family involved in innate immunity. Widely distributed species consistently exhibited higher genetic diversity at both marker types compared to their narrowly distributed counterparts. Although we did not find a significant relationship between microsatellite heterozygosity and TLR heterozygosity, we evidenced a negative trend for widely distributed species and a positive trend for narrowly distributed species. This result suggests that there is a stronger effect of genetic drift in narrowly distributed species. Our results highlight the role of distribution range in maintaining genetic diversity and suggest that environmental gradients, by interacting with gene flow and selection, may influence patterns of adaptive variation.
基金supported by the National Natural Science Foundation of China(62473048,61925303,62088101,62273195,U19B2029).
文摘Dear Editor,This letter studies the distributed Nash equilibrium seeking problem of aggregative game,in which the decision of each player obeys second-order dynamics and is constrained by nonidentical convex sets.To seek the generalized Nash equilibrium(GNE),a projectionbased distributed algorithm via constant step-sizes is developed with linear convergence.In particular,a variable tracking technique is incorporated to estimate the aggregative function,and an event-triggered mechanism is designed to reduce the communication cost.Finally,a numerical example demonstrates the theoretical results.
基金supported in part by Science and Technology Project of State Grid Corporation of China:Research on Key Protection Technologies for New-type Urban Distribution Network with Controllable Sources and Loads.
文摘The petal-shaped distribution network has high power supply reliability.However,the closed-loop operation mode and the access of inverter-interfaced distributed generators(IIDGs)bring great challenges to the protection schemes.The current amplitude differential protection is an effective means to solve this problem,but the existing criterions rarely consider both sensitivity to high-resistance faults and low requirements for data synchronization.Therefore,the general variation laws of the amplitude difference between the current steady-state components at both terminals and the phase differences between current fault components at both terminals are revealed.For external faults,the steady-state-component current amplitude difference is around zero and the fault-component current phase difference is around 180◦.For internal faults,either the amplitude difference is large or the phase difference is small.Accordingly,a current differential protection scheme based on the pre-fault and postfault steady-state current is proposed.The amplitude and phase of current at both terminals of the protected line are required in the proposed scheme,which has low requirements for data synchronization.The simulation results show that the proposed protection scheme is not affected by the fault type,position,resistance and capacity of the IIDGs.It can also be applied to radial distribution networks with IIDGs.
基金support provided by Science Foundation Ireland Frontiers for the Future Programme,21/FFP-P/10090.
文摘Curved geostructures,such as tunnels,are commonly encountered in geotechnical engineering and are critical to maintaining structural stability.Ensuring their proper performance through field monitoring during their service life is essential for the overall functionality of geotechnical infrastructure.Distributed Brillouin sensing(DBS)is increasingly applied in geotechnical projects due to its ability to acquire spatially continuous strain and temperature distributions over distances of up to 150 km using a single optical fibre.However,limited by the complex operations of distributed optic fibre sensing(DFOS)sensors in curved structures,previous reports about exploiting DBS in geotechnical structural health monitoring(SHM)have mostly been focused on flat surfaces.The lack of suitable DFOS installation methods matched to the spatial characteristics of continuous monitoring is one of the major factors that hinder the further application of this technique in curved structures.This review paper starts with a brief introduction of the fundamental working principle of DBS and the inherent limitations of DBS being used on monitoring curved surfaces.Subsequently,the state-of-the-art installation methods of optical fibres in curved structures are reviewed and compared to address the most suitable scenario of each method and their advantages and disadvantages.The installation challenges of optical fibres that can highly affect measurement accuracy are also discussed in the paper.
基金National Natural Science Foundation of China(12125509,11961141003,12275361,U2267205,12175152,12175121)National Key Research and Development Project(2022YFA1602301)Continuous-support Basic Scientific Research Project。
文摘To generate a neutron beam exhibiting a Maxwellian energy distribution with narrow emission angles for measuring the neutron capture reaction rates of the s-process nuclides,a monoenergetic 3.4 MeV proton beam produced by the tandem-accelerator in the China Institute of Atomic Energy was utilized.The proton beam was first transmitted through a 60.5μm aluminum foil and then impinged on a natural LiF target to produce neutron beam via^(7)Li(p,n)7Be reaction.The quasi-Gaussian energy distribution of protons in the LiF target resulted in neutron energy spectra that agreed with a Maxwellian energy distribution at kT=(22±2)keV,which was achieved by integrating neutrons detected within an emission angle of 65.0°±2.6°using a ^(6)Li glass detector positioned at 65°relative to the proton beam direction.The narrow angular spread of the Maxwelliandistributed neutron beam enables direct measurement of neutron capture cross-sections for most s-process nuclides,overcoming previous experimental limitations associated with broad angular distributions.
基金supported by the National Natural Science Foundation of China(62303273,62373226)the National Research Foundation,Singapore through the Medium Sized Center for Advanced Robotics Technology Innovation(WP2.7)
文摘Dear Editor,The letter deals with the distributed state and fault estimation of the whole physical layer for cyber-physical systems(CPSs) when the cyber layer suffers from DoS attacks. With the advancement of embedded computing, communication and related hardware technologies, CPSs have attracted extensive attention and have been widely used in power system, traffic network, refrigeration system and other fields.
文摘This article proposes a multi-tiered fault detection system for series-connected lithium-ion battery modules.Improper use of batteries can lead to electrolyte decomposition,resulting in the formation of lithium dendrites.These dendrites may pierce the separator,leading to the failure of the insulation layer between electrodes and causing micro short circuits.When a micro short circuit occurs,the electrolyte typically undergoes exothermic reactions,leading to thermal runaway and posing a safety risk to users.Relying solely on temperature-based judgment mechanisms within the battery management system often results in delayed intervention.To address this issue,the article develops a multi-tiered fault detection algorithm for series-connected lithium-ion batteries.This algorithm can effectively diagnose micro short circuits,aging,and normal batteries using minimal battery data,thereby improving diagnostic accuracy and enhancing the flexibility of fault detection.Simulations and experiments conducted under various levels of micro short circuits validate the effectiveness of the algorithm,demonstrating its ability to distinguish between short-circuited,aged,and normal batteries under different conditions.This technology can be applied to electric vehicles and energy storage systems,enabling early warnings to ensure safety and prevent thermal runaway.
基金supported by National Key Research and Development Program of China(2024YFE0214000)National Natural Science Foundation of China(62173308)+3 种基金Natural Science Foundation of Zhejiang Province of China(LRG25F030002)Zhejiang Province Leading Geese Plan(2025C01056)Jinhua Science and Technology Project(2022-1-042)Natural Science Foundation of Jiangsu Province(BK20240009).
文摘Dear Editor,This letter addresses distributed optimization for resource allocation problems with time-varying objective functions and time-varying constraints.Inspired by the distributed average tracking(DAT)approach,a distributed control protocol is proposed for optimal resource allocation.The convergence to a time-varying optimal solution within a predefined time is proved.Two numerical examples are given to illustrate the effectiveness of the proposed approach.
基金Supported by the Science and Technology Key Project of Science and Technology Department of Henan Province(No.252102211041)the Key Research and Development Projects of Henan Province(No.231111212500).
文摘A distributed bearing-only target tracking algorithm based on variational Bayesian inference(VBI)under random measurement anomalies is proposed for the problem of adverse effect of random measurement anomalies on the state estimation accuracy of moving targets in bearing-only tracking scenarios.Firstly,the measurement information of each sensor is complemented by using triangulation under the distributed framework.Secondly,the Student-t distribution is selected to model the measurement likelihood probability density function,and the joint posteriori probability density function of the estimated variables is approximately decoupled by VBI.Finally,the estimation results of each local filter are sent to the fusion center and fed back to each local filter.The simulation results show that the proposed distributed bearing-only target tracking algorithm based on VBI in the presence of abnormal measurement noise comprehensively considers the influence of system nonlinearity and random anomaly of measurement noise,and has higher estimation accuracy and robustness than other existing algorithms in the above scenarios.
