The multi-terminal direct current(DC)grid has extinctive superiorities over the traditional alternating current system in integrating large-scale renewable energy.Both the DC circuit breaker(DCCB)and the current flow ...The multi-terminal direct current(DC)grid has extinctive superiorities over the traditional alternating current system in integrating large-scale renewable energy.Both the DC circuit breaker(DCCB)and the current flow controller(CFC)are demanded to ensure the multiterminal DC grid to operates reliably and flexibly.However,since the CFC and the DCCB are all based on fully controlled semiconductor switches(e.g.,insulated gate bipolar transistor,integrated gate commutated thyristor,etc.),their separation configuration in the multiterminal DC grid will lead to unaffordable implementation costs and conduction power losses.To solve these problems,integrated equipment with both current flow control and fault isolation abilities is proposed,which shares the expensive and duplicated components of CFCs and DCCBs among adjacent lines.In addition,the complicated coordination control of CFCs and DCCBs can be avoided by adopting the integrated equipment in themultiterminal DC grid.In order to examine the current flow control and fault isolation abilities of the integrated equipment,the simulation model of a specific meshed four-terminal DC grid is constructed in the PSCAD/EMTDC software.Finally,the comparison between the integrated equipment and the separate solution is presented a specific result or conclusion needs to be added to the abstract.展开更多
As smart grid technology rapidly advances,the vast amount of user data collected by smart meter presents significant challenges in data security and privacy protection.Current research emphasizes data security and use...As smart grid technology rapidly advances,the vast amount of user data collected by smart meter presents significant challenges in data security and privacy protection.Current research emphasizes data security and user privacy concerns within smart grids.However,existing methods struggle with efficiency and security when processing large-scale data.Balancing efficient data processing with stringent privacy protection during data aggregation in smart grids remains an urgent challenge.This paper proposes an AI-based multi-type data aggregation method designed to enhance aggregation efficiency and security by standardizing and normalizing various data modalities.The approach optimizes data preprocessing,integrates Long Short-Term Memory(LSTM)networks for handling time-series data,and employs homomorphic encryption to safeguard user privacy.It also explores the application of Boneh Lynn Shacham(BLS)signatures for user authentication.The proposed scheme’s efficiency,security,and privacy protection capabilities are validated through rigorous security proofs and experimental analysis.展开更多
This article presents a comprehensive framework for advancing sustainable transportation through the integration of next-generation energy technologies.It explores the convergence of Vernova green energy,nuclear fissi...This article presents a comprehensive framework for advancing sustainable transportation through the integration of next-generation energy technologies.It explores the convergence of Vernova green energy,nuclear fission from ARCs(advanced reactor concepts)and SMRs(small modular reactors),and future-focused nuclear fusion methods-MCF(magnetic confinement fusion)and ICF(inertial confinement fusion).Central to this integration is the use of AI(artificial intelligence)to enhance smart grid efficiency,enable real-time optimization,and ensure resilient energy delivery.The synergy between these zero-carbon energy sources and AI-driven infrastructure promises a transformative impact on electric mobility,hydrogen-powered systems,and autonomous transport.By detailing the architecture of an AI-augmented,carbon-neutral transport ecosystem,this paper contributes to the roadmap for future global mobility.展开更多
In conventional fi nite diff erence numerical simulation of seismic waves,regular grids in Cartesian coordinates are used to divide the calculated region.When simulating seismic wave fi elds under an irregular surface...In conventional fi nite diff erence numerical simulation of seismic waves,regular grids in Cartesian coordinates are used to divide the calculated region.When simulating seismic wave fi elds under an irregular surface,such grids are unsuitable to realize the free boundary condition.They also easily generate false scattered waves at the corners of the grids owing to the approximation of the stepped grids.These issues affect the simulation accuracy.This study introduces an orthogonal body-fitted grid generation technique in computational fl uid dynamics for generating grids in transversely isotropic(TI)media under an irregular surface.The fi rst-order velocity-stress equation in curvilinear coordinates is calculated using the optimized nonstaggered grids finite difference method.The point oscillation generated by the nonstaggered grids difference is eliminated by selective filtering.The orthogonal body-fitted grids can accurately describe the irregular surface.Further,the orthogonality of the grids allows the implementation of free boundary conditions without complicated coordinate transformation and interpolation operations.Numerical examples show that the numerical solutions obtained by this method agree well with the analytical solutions.By comparing the simulation results of the proposed method with those of the regular grid difference method,the proposed method can eff ectively eliminate the false scattered waves caused by the stepped grids under the condition of the same grid spacing.Thus,the accuracy of the numerical simulation is improved.In addition,the simulation results of the three-layer TI media model on an irregular surface show that the proposed method is also suitable for complex models.展开更多
Ensuring the reliability of power systems in microgrids is critical,particularly under contingency conditions that can disrupt power flow and system stability.This study investigates the application of Security-Constr...Ensuring the reliability of power systems in microgrids is critical,particularly under contingency conditions that can disrupt power flow and system stability.This study investigates the application of Security-Constrained Optimal Power Flow(SCOPF)using the Line Outage Distribution Factor(LODF)to enhance resilience in a renewable energy-integrated microgrid.The research examines a 30-bus system with 14 generators and an 8669 MW load demand,optimizing both single-objective and multi-objective scenarios.The single-objective opti-mization achieves a total generation cost of$47,738,while the multi-objective approach reduces costs to$47,614 and minimizes battery power output to 165.02 kW.Under contingency conditions,failures in transmission lines 1,22,and 35 lead to complete power loss in those lines,requiring a redistribution strategy.Implementing SCOPF mitigates these disruptions by adjusting power flows,ensuring no line exceeds its capacity.Specifically,in contingency 1,power in channel 4 is reduced from 59 to 32 kW,while overall load shedding is minimized to 0.278 MW.These results demonstrate the effectiveness of SCOPF in maintaining stability and reducing economic losses.Unlike prior studies,this work integrates LODF into SCOPF for large-scale microgrid applications,offering a computationally efficient contingency management framework that enhances grid resilience and supports renewable energy adoption.展开更多
Isolated power systems,such as those on islands,face acute challenges in balancing energy demand with limited generation resources,making them particularly vulnerable to disruptions.This paper addresses these challeng...Isolated power systems,such as those on islands,face acute challenges in balancing energy demand with limited generation resources,making them particularly vulnerable to disruptions.This paper addresses these challenges by proposing a novel control and simulation framework based on a holonic multi-agent architecture,specifically developed as a digital twin for the Mayotte island grid.The primary contribution is a multi-objective optimization model,driven by a genetic algorithm,designed to enhance grid resilience through intelligent,decentralized decisionmaking.The efficacy of this architecture is validated through three distinct simulation scenarios:(1)a baseline scenario establishing nominal grid operation;(2)a critical disruption involving the failure of a major power plant;and(3)a localized fault resulting in the complete disconnection of a regional sub-grid.The major results demonstrate the system’s dual resilience mechanisms.In the plant failure scenario,the top-level holon successfully managed a global energy deficit by optimally reallocating shared resources,prioritizing grid stability over complete demand satisfaction.In the disconnection scenario,the affected holon demonstrated true autonomy,transitioning seamlessly into a selfsufficient islanded microgrid to prevent a cascading failure.Collectively,these findings validate the holonic model as a robust decision-support tool capable of managing both systemic and localized faults,thereby significantly enhancing the operational resilience and stability of isolated smart grids.展开更多
Fibonacci sequence,generated by summing the preceding two terms,is a classical sequence renowned for its elegant properties.In this paper,leveraging properties of generalized Fibonacci sequences and formulas for conse...Fibonacci sequence,generated by summing the preceding two terms,is a classical sequence renowned for its elegant properties.In this paper,leveraging properties of generalized Fibonacci sequences and formulas for consecutive sums of equidistant sub-sequences,we investigate the ratio of the sum of numbers along main-diagonal and sub-diagonal of odd-order grids containing generalized Fibonacci sequences.We show that this ratio is solely dependent on the order of the grid,providing a concise and splendid identity.展开更多
Edge computing has transformed smart grids by lowering latency,reducing network congestion,and enabling real-time decision-making.Nevertheless,devising an optimal task-offloading strategy remains challenging,as it mus...Edge computing has transformed smart grids by lowering latency,reducing network congestion,and enabling real-time decision-making.Nevertheless,devising an optimal task-offloading strategy remains challenging,as it must jointly minimise energy consumption and response time under fluctuating workloads and volatile network conditions.We cast the offloading problem as aMarkov Decision Process(MDP)and solve it with Deep Reinforcement Learning(DRL).Specifically,we present a three-tier architecture—end devices,edge nodes,and a cloud server—and enhance Proximal Policy Optimization(PPO)to learn adaptive,energy-aware policies.A Convolutional Neural Network(CNN)extracts high-level features from system states,enabling the agent to respond continually to changing conditions.Extensive simulations show that the proposed method reduces task latency and energy consumption far more than several baseline algorithms,thereby improving overall system performance.These results demonstrate the effectiveness and robustness of the framework for real-time task offloading in dynamic smart-grid environments.展开更多
To transmit customer power data collected by smart meters(SMs)to utility companies,data must first be transmitted to the corresponding data aggregation point(DAP)of the SM.The number of DAPs installed and the installa...To transmit customer power data collected by smart meters(SMs)to utility companies,data must first be transmitted to the corresponding data aggregation point(DAP)of the SM.The number of DAPs installed and the installation location greatly impact the whole network.For the traditional DAP placement algorithm,the number of DAPs must be set in advance,but determining the best number of DAPs is difficult,which undoubtedly reduces the overall performance of the network.Moreover,the excessive gap between the loads of different DAPs is also an important factor affecting the quality of the network.To address the above problems,this paper proposes a DAP placement algorithm,APSSA,based on the improved affinity propagation(AP)algorithm and sparrow search(SSA)algorithm,which can select the appropriate number of DAPs to be installed and the corresponding installation locations according to the number of SMs and their distribution locations in different environments.The algorithm adds an allocation mechanism to optimize the subnetwork in the SSA.APSSA is evaluated under three different areas and compared with other DAP placement algorithms.The experimental results validated that the method in this paper can reduce the network cost,shorten the average transmission distance,and reduce the load gap.展开更多
Compared with other migration methods, reverse-time migration is based on a precise wave equation, not an approximation, and performs extrapolation in the depth domain rather than the time domain. It is highly accurat...Compared with other migration methods, reverse-time migration is based on a precise wave equation, not an approximation, and performs extrapolation in the depth domain rather than the time domain. It is highly accurate and not affected by strong subsurface structure complexity and horizontal velocity variations. The difference method based on triangular grids maintains the simplicity of the difference method and the precision of the finite element method. It can be used directly for forward modeling on models with complex top surfaces and migration without statics preprocessing. We apply a finite difference method based on triangular grids for post-stack reverse-time migration for the first time. Tests on model data verify that the combination of the two methods can achieve near-perfect results in application.展开更多
For a complex flow about multi-element airfoils a mixed grid method is set up. C-type grids are produced on each element′s body and in their wakes at first, O-type grids are given in the outmost area, and H-type grid...For a complex flow about multi-element airfoils a mixed grid method is set up. C-type grids are produced on each element′s body and in their wakes at first, O-type grids are given in the outmost area, and H-type grids are used in middle additional areas. An algebra method is used to produce the initial grids in each area. And the girds are optimized by elliptical differential equation method. Then C-O-H zonal patched grids around multi-element airfoils are produced automatically and efficiently. A time accurate finite-volume integration method is used to solve the compressible laminar and turbulent Navier-Stokes (N-S) equations on the grids. Computational results prove the method to be effective.展开更多
In this paper the growing process of China power grid from formation of local power grids to nationwide interconnection is reviewed. The scale and structure of power grid construction in the near future, especially th...In this paper the growing process of China power grid from formation of local power grids to nationwide interconnection is reviewed. The scale and structure of power grid construction in the near future, especially the planning on sending power from west to east, North-South supplementation and nationwide interconnection are introduced. In addition, the technologies to be extended in future grid development are briefed, such as HVDC, FACTS and compact transmission line, etc.展开更多
To achieve high quality of service （QoS） on computational grids, the QoS-aware job scheduling is investigated for a hierarchical decentralized grid architecture that consists of multilevel schedulers. An integrated ...To achieve high quality of service （QoS） on computational grids, the QoS-aware job scheduling is investigated for a hierarchical decentralized grid architecture that consists of multilevel schedulers. An integrated QoS-aware job dispatching policy is proposed, which correlates priorities of incoming jobs used for job selecting at the local scheduler of the grid node with the job dispatching policies at the global scheduler for computational grids. The stochastic high-level Petri net （SHLPN） model of a two-level hierarchy computational grid architecture is presented, and a model refinement is made to reduce the complexity of the model solution. A performance analysis technique based on the SHLPN is proposed to investigate the QoS-aware job scheduling policy. Numerical results show that the QoS-aware job dispatching policy outperforms the QoS-unaware job dispatching policy in balancing the high-priority jobs, and thus enables priority-based QoS.展开更多
The informatization of the grid,i.e.,the incorporation of sensing,communications,data platforms,analytics,and automation in the running of power systems,has turned out to be a vital facilitator of environmental mitiga...The informatization of the grid,i.e.,the incorporation of sensing,communications,data platforms,analytics,and automation in the running of power systems,has turned out to be a vital facilitator of environmental mitigation as power systems increasingly take up larger proportions of variable renewables,distributed energy resources(DERs),and electrified end uses.The review summarizes the worldwide evidence related to the ability of informatization-based smart grid applications to lower the environmental impact in six pathways,namely efficiency improvement,flexibility activation,renewable integration,DER coordination,electrification management,and resilience enhancement.Across regions,the most consistently reported benefits arise from reducing waste and improving operational control,including loss reduction,volt/VAR optimization,conservation voltage reduction,and distribution automation,particularly in systems with high baseline losses or frequent outages.Demand response,dynamic pricing,and managed electric vehicle(EV)charging can further lower emissions when they displace high-emitting marginal generation or align consumption with time-varying low-carbon supply;however,outcomes are highly sensitive to marginal emissions profiles and accounting methods.In highrenewable systems,forecasting,congestion management,and curtailment reduction emerge as high-leverage mechanisms,while distributed energy resource management systems/virtual power plant(DERMS/VPP)-enabled coordination can expand hosting capacity and substitute distributed flexibility for carbon-intensive balancing,contingent on interoperability and constraint-aware control.The review also highlights trade-offs that shape net benefits,including embodied impacts and e-waste from digital hardware,information and communication technologies(ICT)energy use,rebound and equity effects,and cyber-physical risks.We conclude with governance and research priorities for verifiable,secure,and lifecyclesustainable informatization.展开更多
https://www.sciencedirect.com/journal/energy-and-buildings/vol/354/suppl/C Volume 354,1 March 2026[OA](1)Rule-based peak shaving strategy with battery storage:Evaluating socio-economic impacts in regional grids by Md ...https://www.sciencedirect.com/journal/energy-and-buildings/vol/354/suppl/C Volume 354,1 March 2026[OA](1)Rule-based peak shaving strategy with battery storage:Evaluating socio-economic impacts in regional grids by Md Masud Rana,Huadong Mo,Mohd Fakhizan Romlie,et al,Article 116983 Abstract:The Australian electricity framework includes several demand tariff structures,with peak demand charges constituting a significant cost component for consumers.Efficient peak load shaving techniques can mitigate these charges,leading to substantial economic benefits to the power suppliers,consumers,and society.展开更多
The fast-changing trajectory of energy systems toward renewables requires flexible,low-emission technologies that can buffer supply intermittently and offer large-scale energy storage systems.Moreso,hydrogen is increa...The fast-changing trajectory of energy systems toward renewables requires flexible,low-emission technologies that can buffer supply intermittently and offer large-scale energy storage systems.Moreso,hydrogen is increasingly viewed as a multi-scale flexibility resource capable of supporting deep decarbonization in renewable-dominated power systems,yet existing reviews often treat production,storage,and conversion technologies in isolation.Hydrogen offers the ability to convert,store and reconvert energy on various timescales.This review critically analyses the current literature of hydrogen production and storage in relation to power systems integration,synthesizing technical,economic and operational advances.The study synthesizes recent advances in electrolysis,particularly PEM and high-temperature SOEC systems,together with emerging PEC routes,biomass-to-hydrogen processes,and long-duration storage technologies.It considers,for storage,the performance and maturity of compressed gas,liquid hydrogen,metal and complex hydrides,liquid organic hydrogen carriers,and geological formations.Integration studies show that the value of hydrogen is enhanced as the share of renewables increases,providing seasonal storage,grid balancing,and sector coupling via power-to-hydrogen-to-power configurations.Yet technical,economic and other hurdles such as conversion losses,infrastructure requirements,and safety considerations are still holding back widespread implementation.The review also underlines the value of policy frameworks,such as country-level hydrogen strategies,carbon pricing,tax incentives,and harmonized safety standards to speed up adoption and reduce barriers to costs.The review synthesizes offer planners,operators,and policymakers a clear roadmap for aligning hydrogen deployment strategies with evolving technical requirements and high-renewable power-system conditions.By summarizing what is known and discussing opportunities for the future,this review is intended to be a roadmap towards maximizing hydrogen in reaching a flexible,resilient and carbon free power system.展开更多
Electron beam injectors are pivotal components of large-scale scientific instruments,such as synchrotron radiation sources,free-electron lasers,and electron-positron colliders.The quality of the electron beam produced...Electron beam injectors are pivotal components of large-scale scientific instruments,such as synchrotron radiation sources,free-electron lasers,and electron-positron colliders.The quality of the electron beam produced by the injector critically influences the performance of the entire accelerator-based scientific research apparatus.The injectors of such facilities usually use photocathode and thermionic-cathode electron guns.Although the photocathode injector can produce electron beams of excellent quality,its associated laser system is massive and intricate.The thermionic-cathode electron gun,especially the gridded electron gun injector,has a simple structure capable of generating numerous electron beams.However,its emittance is typically high.In this study,methods to reduce beam emittance are explored through a comprehensive analysis of various grid structures and preliminary design results,examining the evolution of beam phase space at different grid positions.An optimization method for reducing the emittance of a gridded thermionic-cathode electron gun is proposed through theoretical derivation,electromagnetic-field simulation,and beam-dynamics simulation.A 50%reduction in emittance was achieved for a 50 keV,1.7 A electron gun,laying the foundation for the subsequent design of a high-current,low-emittance injector.展开更多
According to the dynamic interaction process between cyber flow and power flow in grid cyber-physical systems(GCPS),attackers could gradually trigger large-scale power failures through cooperative cyber-attacks,subseq...According to the dynamic interaction process between cyber flow and power flow in grid cyber-physical systems(GCPS),attackers could gradually trigger large-scale power failures through cooperative cyber-attacks,subsequently forming cross-domain cascading failures(CDCF)that cross cyber-domain and power-domain and endanger the stable running of GCPS.To reveal the evolutionary mechanism of CDCF,an optimal attack scheme evaluation method is proposed,considering the spatiotemporal synergy of multiple attack-event-chains.First,in accordance with the spatiotemporal synergy of multiple attack-event-chains,the CDCF evolutionary mechanism is analyzed from the attackers'perspective,and a CDCF mathematical model is established.Furthermore,an attack graph model of CDCF evolution and its hazard calculation method are proposed.Then,the attackers'decision-making process for the optimal attack scheme of CDCF is deduced based on the attack graph model.Finally,both the evaluation and implementation processes of the optimal attack scheme are simulated in the GCPS experimental system based on IEEE-39 bus systems.展开更多
For 5G millimeter wave(mm-Wave)user equipments(UEs),all test cases must be evaluated in Over-The-Air(OTA)manner.Test time increases dramatically compared to Sub-6 GHz.Therefore,test time reduction is of great signific...For 5G millimeter wave(mm-Wave)user equipments(UEs),all test cases must be evaluated in Over-The-Air(OTA)manner.Test time increases dramatically compared to Sub-6 GHz.Therefore,test time reduction is of great significance for 5G mm-Wave OTA testing.Among all test cases,beam peak search is the most time-consuming,taking up the majority of the overall test time.Therefore,the objective of this work is to determine a suitable beam peak search grid for 5G mm-Wave UEs with satisfactory accuracy and efficiency.Through radiation property investigation of 5G mm-Wave commercial UEs,more reasonable reference array configuration(4×2)and reference deployment scenario(composite beam)are proposed for beam peak search grid analysis.The effect of different grid configurations on beam peak search precision are characterized quantitatively.The determination of associated measurement uncertainty(MU)term along with quantitative analysis approach are proposed based on statistical analysis.Finally,the recommended minimum number of beam peak search grid points is 182 based on the proposed 4×2 array under composite beam scenario.Compared with currently-required 1106 points in 3GPP/CTIA specifications,over 80%reduction can be achieved without increasing the MU limit.The feasibility of the proposed MU analysis as well as the recommended grids is demonstrated through measurements.展开更多
In the development of coalbed methane(CBM)reservoirs using multistage fractured horizontal wells,there often exist areas that are either repeatedly stimulated or completely unstimulated between fracturing stages,leadi...In the development of coalbed methane(CBM)reservoirs using multistage fractured horizontal wells,there often exist areas that are either repeatedly stimulated or completely unstimulated between fracturing stages,leading to suboptimal reservoir performance.Currently,there is no well-established method for accurately evaluating the effectiveness of such stimulation.This study introduces,for the first time,the concept of the Fracture Network Bridging Coefficient(FNBC)as a novel metric to assess stimulation performance.By quantitatively coupling the proportions of unstimulated and overstimulated volumes,the FNBC effectively characterizes the connectivity and efficiency of the fracture network.A background grid calibration method is developed to quantify the stage-controlled volume,effectively stimulated volume,unstimulated volume,and repeatedly stimulated volume among different stages of horizontal wells.Furthermore,an optimization model is constructed by taking the FNBC as the objective function and the fracturing injection rate and fluid volume as optimization variables.The Simultaneous Perturbation Stochastic Approximation(SPSA)algorithm is employed to iteratively perturb and optimize these variables,progressively improving the FNBC until the optimal displacement rate and fluid volume corresponding to the maximum FNBC are obtained.Field application in a typical CBM multistage fractured horizontal well in China demonstrates that the FNBC increased from 0.358 to 0.539(a 50.6% improvement),with the injection rate rising from 16 m^(3)/min to 24 m^(3)/min and the average fluid volume per stage increasing from 2490 m^(3) to 3192 m^(3),significantly enhancing the stimulation effectiveness.This research provides theoretical support for designing high-efficiency stimulation strategies in unconventional reservoirs under dynamic limits.展开更多
基金supported in part by Natural Science Foundation of Jiangsu Province under Grant BK20230255Natural Science Foundation of Shandong Province under Grant ZR2023QE281.
文摘The multi-terminal direct current(DC)grid has extinctive superiorities over the traditional alternating current system in integrating large-scale renewable energy.Both the DC circuit breaker(DCCB)and the current flow controller(CFC)are demanded to ensure the multiterminal DC grid to operates reliably and flexibly.However,since the CFC and the DCCB are all based on fully controlled semiconductor switches(e.g.,insulated gate bipolar transistor,integrated gate commutated thyristor,etc.),their separation configuration in the multiterminal DC grid will lead to unaffordable implementation costs and conduction power losses.To solve these problems,integrated equipment with both current flow control and fault isolation abilities is proposed,which shares the expensive and duplicated components of CFCs and DCCBs among adjacent lines.In addition,the complicated coordination control of CFCs and DCCBs can be avoided by adopting the integrated equipment in themultiterminal DC grid.In order to examine the current flow control and fault isolation abilities of the integrated equipment,the simulation model of a specific meshed four-terminal DC grid is constructed in the PSCAD/EMTDC software.Finally,the comparison between the integrated equipment and the separate solution is presented a specific result or conclusion needs to be added to the abstract.
基金supported by the National Key R&D Program of China(No.2023YFB2703700)the National Natural Science Foundation of China(Nos.U21A20465,62302457,62402444,62172292)+4 种基金the Fundamental Research Funds of Zhejiang Sci-Tech University(Nos.23222092-Y,22222266-Y)the Program for Leading Innovative Research Team of Zhejiang Province(No.2023R01001)the Zhejiang Provincial Natural Science Foundation of China(Nos.LQ24F020008,LQ24F020012)the Foundation of State Key Laboratory of Public Big Data(No.[2022]417)the“Pioneer”and“Leading Goose”R&D Program of Zhejiang(No.2023C01119).
文摘As smart grid technology rapidly advances,the vast amount of user data collected by smart meter presents significant challenges in data security and privacy protection.Current research emphasizes data security and user privacy concerns within smart grids.However,existing methods struggle with efficiency and security when processing large-scale data.Balancing efficient data processing with stringent privacy protection during data aggregation in smart grids remains an urgent challenge.This paper proposes an AI-based multi-type data aggregation method designed to enhance aggregation efficiency and security by standardizing and normalizing various data modalities.The approach optimizes data preprocessing,integrates Long Short-Term Memory(LSTM)networks for handling time-series data,and employs homomorphic encryption to safeguard user privacy.It also explores the application of Boneh Lynn Shacham(BLS)signatures for user authentication.The proposed scheme’s efficiency,security,and privacy protection capabilities are validated through rigorous security proofs and experimental analysis.
文摘This article presents a comprehensive framework for advancing sustainable transportation through the integration of next-generation energy technologies.It explores the convergence of Vernova green energy,nuclear fission from ARCs(advanced reactor concepts)and SMRs(small modular reactors),and future-focused nuclear fusion methods-MCF(magnetic confinement fusion)and ICF(inertial confinement fusion).Central to this integration is the use of AI(artificial intelligence)to enhance smart grid efficiency,enable real-time optimization,and ensure resilient energy delivery.The synergy between these zero-carbon energy sources and AI-driven infrastructure promises a transformative impact on electric mobility,hydrogen-powered systems,and autonomous transport.By detailing the architecture of an AI-augmented,carbon-neutral transport ecosystem,this paper contributes to the roadmap for future global mobility.
基金supported by the National Key Research and Development Program of China (Grant No.2023YFC3206501 and 2022YFFO802600)the National Natural Science Foundation of China (Grant No.52369003,42262010 and 42374166)+6 种基金the Natural Science Foundation of Inner Mongolia Autonomous Region of China (Grant No.2023LHMS04011 and2022MS04009)the Application Technology Research and Development Project of Jungar Banner (Grant No.2023YY-18 and 2023YY-19)the First-class Academic Subjects Special Research Project of the Education Department of Inner Mongolia Autonomous Region (Grant No.YLXKZX-NND-010)the Inner Mongolia Autonomous Region Science and Technology Leading Talent Team (Grant No.2022LJRC0007)the Inner Mongolia Agricultural University Basic Research Project(BR22-12-04)the Program for Innovative Research Team in Universities of Inner Mongolia Autonomous Region (Grant No.NMGIRT2313)the Basic Scientific Research Project of Institutions of Higher(Grant No.JY20230090)。
文摘In conventional fi nite diff erence numerical simulation of seismic waves,regular grids in Cartesian coordinates are used to divide the calculated region.When simulating seismic wave fi elds under an irregular surface,such grids are unsuitable to realize the free boundary condition.They also easily generate false scattered waves at the corners of the grids owing to the approximation of the stepped grids.These issues affect the simulation accuracy.This study introduces an orthogonal body-fitted grid generation technique in computational fl uid dynamics for generating grids in transversely isotropic(TI)media under an irregular surface.The fi rst-order velocity-stress equation in curvilinear coordinates is calculated using the optimized nonstaggered grids finite difference method.The point oscillation generated by the nonstaggered grids difference is eliminated by selective filtering.The orthogonal body-fitted grids can accurately describe the irregular surface.Further,the orthogonality of the grids allows the implementation of free boundary conditions without complicated coordinate transformation and interpolation operations.Numerical examples show that the numerical solutions obtained by this method agree well with the analytical solutions.By comparing the simulation results of the proposed method with those of the regular grid difference method,the proposed method can eff ectively eliminate the false scattered waves caused by the stepped grids under the condition of the same grid spacing.Thus,the accuracy of the numerical simulation is improved.In addition,the simulation results of the three-layer TI media model on an irregular surface show that the proposed method is also suitable for complex models.
文摘Ensuring the reliability of power systems in microgrids is critical,particularly under contingency conditions that can disrupt power flow and system stability.This study investigates the application of Security-Constrained Optimal Power Flow(SCOPF)using the Line Outage Distribution Factor(LODF)to enhance resilience in a renewable energy-integrated microgrid.The research examines a 30-bus system with 14 generators and an 8669 MW load demand,optimizing both single-objective and multi-objective scenarios.The single-objective opti-mization achieves a total generation cost of$47,738,while the multi-objective approach reduces costs to$47,614 and minimizes battery power output to 165.02 kW.Under contingency conditions,failures in transmission lines 1,22,and 35 lead to complete power loss in those lines,requiring a redistribution strategy.Implementing SCOPF mitigates these disruptions by adjusting power flows,ensuring no line exceeds its capacity.Specifically,in contingency 1,power in channel 4 is reduced from 59 to 32 kW,while overall load shedding is minimized to 0.278 MW.These results demonstrate the effectiveness of SCOPF in maintaining stability and reducing economic losses.Unlike prior studies,this work integrates LODF into SCOPF for large-scale microgrid applications,offering a computationally efficient contingency management framework that enhances grid resilience and supports renewable energy adoption.
基金funding for this study from the European Union’s Horizon 2020 research and innovation programme under grant agreement No.957843The research was supported by the MAESHA project.More information can be found at the Horizon 2020 website:https://cordis.europa.eu/project/id/957843/fr(accessed on 28 September 2025).
文摘Isolated power systems,such as those on islands,face acute challenges in balancing energy demand with limited generation resources,making them particularly vulnerable to disruptions.This paper addresses these challenges by proposing a novel control and simulation framework based on a holonic multi-agent architecture,specifically developed as a digital twin for the Mayotte island grid.The primary contribution is a multi-objective optimization model,driven by a genetic algorithm,designed to enhance grid resilience through intelligent,decentralized decisionmaking.The efficacy of this architecture is validated through three distinct simulation scenarios:(1)a baseline scenario establishing nominal grid operation;(2)a critical disruption involving the failure of a major power plant;and(3)a localized fault resulting in the complete disconnection of a regional sub-grid.The major results demonstrate the system’s dual resilience mechanisms.In the plant failure scenario,the top-level holon successfully managed a global energy deficit by optimally reallocating shared resources,prioritizing grid stability over complete demand satisfaction.In the disconnection scenario,the affected holon demonstrated true autonomy,transitioning seamlessly into a selfsufficient islanded microgrid to prevent a cascading failure.Collectively,these findings validate the holonic model as a robust decision-support tool capable of managing both systemic and localized faults,thereby significantly enhancing the operational resilience and stability of isolated smart grids.
基金Supported by the National Natural Science Foundation of China(Grant No.12471298)the Shaanxi Fundamental Science Research Project for Mathematics and Physics(Grant No.23JSQ031)the Shaanxi Province College Student Innovation and Entrepreneurship Training Program(Grant Nos.S202210699481 and S202310699324X).
文摘Fibonacci sequence,generated by summing the preceding two terms,is a classical sequence renowned for its elegant properties.In this paper,leveraging properties of generalized Fibonacci sequences and formulas for consecutive sums of equidistant sub-sequences,we investigate the ratio of the sum of numbers along main-diagonal and sub-diagonal of odd-order grids containing generalized Fibonacci sequences.We show that this ratio is solely dependent on the order of the grid,providing a concise and splendid identity.
基金supported by the National Natural Science Foundation of China(Grant No.62103349)the Henan Province Science and Technology Research Project(Grant No.232102210104).
文摘Edge computing has transformed smart grids by lowering latency,reducing network congestion,and enabling real-time decision-making.Nevertheless,devising an optimal task-offloading strategy remains challenging,as it must jointly minimise energy consumption and response time under fluctuating workloads and volatile network conditions.We cast the offloading problem as aMarkov Decision Process(MDP)and solve it with Deep Reinforcement Learning(DRL).Specifically,we present a three-tier architecture—end devices,edge nodes,and a cloud server—and enhance Proximal Policy Optimization(PPO)to learn adaptive,energy-aware policies.A Convolutional Neural Network(CNN)extracts high-level features from system states,enabling the agent to respond continually to changing conditions.Extensive simulations show that the proposed method reduces task latency and energy consumption far more than several baseline algorithms,thereby improving overall system performance.These results demonstrate the effectiveness and robustness of the framework for real-time task offloading in dynamic smart-grid environments.
基金supported by the Fujian University of Technology under Grant GYZ20016,GY-Z18183,and GY-Z19005partially supported by the National Science and Technology Council under Grant NSTC 113-2221-E-224-056-.
文摘To transmit customer power data collected by smart meters(SMs)to utility companies,data must first be transmitted to the corresponding data aggregation point(DAP)of the SM.The number of DAPs installed and the installation location greatly impact the whole network.For the traditional DAP placement algorithm,the number of DAPs must be set in advance,but determining the best number of DAPs is difficult,which undoubtedly reduces the overall performance of the network.Moreover,the excessive gap between the loads of different DAPs is also an important factor affecting the quality of the network.To address the above problems,this paper proposes a DAP placement algorithm,APSSA,based on the improved affinity propagation(AP)algorithm and sparrow search(SSA)algorithm,which can select the appropriate number of DAPs to be installed and the corresponding installation locations according to the number of SMs and their distribution locations in different environments.The algorithm adds an allocation mechanism to optimize the subnetwork in the SSA.APSSA is evaluated under three different areas and compared with other DAP placement algorithms.The experimental results validated that the method in this paper can reduce the network cost,shorten the average transmission distance,and reduce the load gap.
基金sponsored by National Natural Science Foundation(40474041)National Symposium of 863(2006AA06Z206)+1 种基金National Symposium of 973(2007CB209605)CNPC Geophysical Key Laboratory of the China University of Petroleum (East China) Research Department
文摘Compared with other migration methods, reverse-time migration is based on a precise wave equation, not an approximation, and performs extrapolation in the depth domain rather than the time domain. It is highly accurate and not affected by strong subsurface structure complexity and horizontal velocity variations. The difference method based on triangular grids maintains the simplicity of the difference method and the precision of the finite element method. It can be used directly for forward modeling on models with complex top surfaces and migration without statics preprocessing. We apply a finite difference method based on triangular grids for post-stack reverse-time migration for the first time. Tests on model data verify that the combination of the two methods can achieve near-perfect results in application.
文摘For a complex flow about multi-element airfoils a mixed grid method is set up. C-type grids are produced on each element′s body and in their wakes at first, O-type grids are given in the outmost area, and H-type grids are used in middle additional areas. An algebra method is used to produce the initial grids in each area. And the girds are optimized by elliptical differential equation method. Then C-O-H zonal patched grids around multi-element airfoils are produced automatically and efficiently. A time accurate finite-volume integration method is used to solve the compressible laminar and turbulent Navier-Stokes (N-S) equations on the grids. Computational results prove the method to be effective.
文摘In this paper the growing process of China power grid from formation of local power grids to nationwide interconnection is reviewed. The scale and structure of power grid construction in the near future, especially the planning on sending power from west to east, North-South supplementation and nationwide interconnection are introduced. In addition, the technologies to be extended in future grid development are briefed, such as HVDC, FACTS and compact transmission line, etc.
基金The National Natural Science Foundation of China(No60673054,90412012)
文摘To achieve high quality of service （QoS） on computational grids, the QoS-aware job scheduling is investigated for a hierarchical decentralized grid architecture that consists of multilevel schedulers. An integrated QoS-aware job dispatching policy is proposed, which correlates priorities of incoming jobs used for job selecting at the local scheduler of the grid node with the job dispatching policies at the global scheduler for computational grids. The stochastic high-level Petri net （SHLPN） model of a two-level hierarchy computational grid architecture is presented, and a model refinement is made to reduce the complexity of the model solution. A performance analysis technique based on the SHLPN is proposed to investigate the QoS-aware job scheduling policy. Numerical results show that the QoS-aware job dispatching policy outperforms the QoS-unaware job dispatching policy in balancing the high-priority jobs, and thus enables priority-based QoS.
文摘The informatization of the grid,i.e.,the incorporation of sensing,communications,data platforms,analytics,and automation in the running of power systems,has turned out to be a vital facilitator of environmental mitigation as power systems increasingly take up larger proportions of variable renewables,distributed energy resources(DERs),and electrified end uses.The review summarizes the worldwide evidence related to the ability of informatization-based smart grid applications to lower the environmental impact in six pathways,namely efficiency improvement,flexibility activation,renewable integration,DER coordination,electrification management,and resilience enhancement.Across regions,the most consistently reported benefits arise from reducing waste and improving operational control,including loss reduction,volt/VAR optimization,conservation voltage reduction,and distribution automation,particularly in systems with high baseline losses or frequent outages.Demand response,dynamic pricing,and managed electric vehicle(EV)charging can further lower emissions when they displace high-emitting marginal generation or align consumption with time-varying low-carbon supply;however,outcomes are highly sensitive to marginal emissions profiles and accounting methods.In highrenewable systems,forecasting,congestion management,and curtailment reduction emerge as high-leverage mechanisms,while distributed energy resource management systems/virtual power plant(DERMS/VPP)-enabled coordination can expand hosting capacity and substitute distributed flexibility for carbon-intensive balancing,contingent on interoperability and constraint-aware control.The review also highlights trade-offs that shape net benefits,including embodied impacts and e-waste from digital hardware,information and communication technologies(ICT)energy use,rebound and equity effects,and cyber-physical risks.We conclude with governance and research priorities for verifiable,secure,and lifecyclesustainable informatization.
文摘https://www.sciencedirect.com/journal/energy-and-buildings/vol/354/suppl/C Volume 354,1 March 2026[OA](1)Rule-based peak shaving strategy with battery storage:Evaluating socio-economic impacts in regional grids by Md Masud Rana,Huadong Mo,Mohd Fakhizan Romlie,et al,Article 116983 Abstract:The Australian electricity framework includes several demand tariff structures,with peak demand charges constituting a significant cost component for consumers.Efficient peak load shaving techniques can mitigate these charges,leading to substantial economic benefits to the power suppliers,consumers,and society.
基金funding this research work through the project number(PSAU/2025/01/38318).
文摘The fast-changing trajectory of energy systems toward renewables requires flexible,low-emission technologies that can buffer supply intermittently and offer large-scale energy storage systems.Moreso,hydrogen is increasingly viewed as a multi-scale flexibility resource capable of supporting deep decarbonization in renewable-dominated power systems,yet existing reviews often treat production,storage,and conversion technologies in isolation.Hydrogen offers the ability to convert,store and reconvert energy on various timescales.This review critically analyses the current literature of hydrogen production and storage in relation to power systems integration,synthesizing technical,economic and operational advances.The study synthesizes recent advances in electrolysis,particularly PEM and high-temperature SOEC systems,together with emerging PEC routes,biomass-to-hydrogen processes,and long-duration storage technologies.It considers,for storage,the performance and maturity of compressed gas,liquid hydrogen,metal and complex hydrides,liquid organic hydrogen carriers,and geological formations.Integration studies show that the value of hydrogen is enhanced as the share of renewables increases,providing seasonal storage,grid balancing,and sector coupling via power-to-hydrogen-to-power configurations.Yet technical,economic and other hurdles such as conversion losses,infrastructure requirements,and safety considerations are still holding back widespread implementation.The review also underlines the value of policy frameworks,such as country-level hydrogen strategies,carbon pricing,tax incentives,and harmonized safety standards to speed up adoption and reduce barriers to costs.The review synthesizes offer planners,operators,and policymakers a clear roadmap for aligning hydrogen deployment strategies with evolving technical requirements and high-renewable power-system conditions.By summarizing what is known and discussing opportunities for the future,this review is intended to be a roadmap towards maximizing hydrogen in reaching a flexible,resilient and carbon free power system.
基金supported by the Hundred-person Program of Chinese Academy of Sciences and the National Natural Science Foundation of China(No.11905074).
文摘Electron beam injectors are pivotal components of large-scale scientific instruments,such as synchrotron radiation sources,free-electron lasers,and electron-positron colliders.The quality of the electron beam produced by the injector critically influences the performance of the entire accelerator-based scientific research apparatus.The injectors of such facilities usually use photocathode and thermionic-cathode electron guns.Although the photocathode injector can produce electron beams of excellent quality,its associated laser system is massive and intricate.The thermionic-cathode electron gun,especially the gridded electron gun injector,has a simple structure capable of generating numerous electron beams.However,its emittance is typically high.In this study,methods to reduce beam emittance are explored through a comprehensive analysis of various grid structures and preliminary design results,examining the evolution of beam phase space at different grid positions.An optimization method for reducing the emittance of a gridded thermionic-cathode electron gun is proposed through theoretical derivation,electromagnetic-field simulation,and beam-dynamics simulation.A 50%reduction in emittance was achieved for a 50 keV,1.7 A electron gun,laying the foundation for the subsequent design of a high-current,low-emittance injector.
基金supported by National Natural Science Foundation of China(51977155 and 61833008).
文摘According to the dynamic interaction process between cyber flow and power flow in grid cyber-physical systems(GCPS),attackers could gradually trigger large-scale power failures through cooperative cyber-attacks,subsequently forming cross-domain cascading failures(CDCF)that cross cyber-domain and power-domain and endanger the stable running of GCPS.To reveal the evolutionary mechanism of CDCF,an optimal attack scheme evaluation method is proposed,considering the spatiotemporal synergy of multiple attack-event-chains.First,in accordance with the spatiotemporal synergy of multiple attack-event-chains,the CDCF evolutionary mechanism is analyzed from the attackers'perspective,and a CDCF mathematical model is established.Furthermore,an attack graph model of CDCF evolution and its hazard calculation method are proposed.Then,the attackers'decision-making process for the optimal attack scheme of CDCF is deduced based on the attack graph model.Finally,both the evaluation and implementation processes of the optimal attack scheme are simulated in the GCPS experimental system based on IEEE-39 bus systems.
基金supported by the Beijing Natural Science Foundation under Grant L253002.
文摘For 5G millimeter wave(mm-Wave)user equipments(UEs),all test cases must be evaluated in Over-The-Air(OTA)manner.Test time increases dramatically compared to Sub-6 GHz.Therefore,test time reduction is of great significance for 5G mm-Wave OTA testing.Among all test cases,beam peak search is the most time-consuming,taking up the majority of the overall test time.Therefore,the objective of this work is to determine a suitable beam peak search grid for 5G mm-Wave UEs with satisfactory accuracy and efficiency.Through radiation property investigation of 5G mm-Wave commercial UEs,more reasonable reference array configuration(4×2)and reference deployment scenario(composite beam)are proposed for beam peak search grid analysis.The effect of different grid configurations on beam peak search precision are characterized quantitatively.The determination of associated measurement uncertainty(MU)term along with quantitative analysis approach are proposed based on statistical analysis.Finally,the recommended minimum number of beam peak search grid points is 182 based on the proposed 4×2 array under composite beam scenario.Compared with currently-required 1106 points in 3GPP/CTIA specifications,over 80%reduction can be achieved without increasing the MU limit.The feasibility of the proposed MU analysis as well as the recommended grids is demonstrated through measurements.
基金the financial support from National Natural Science Foundation of China(No.52474029)Strategic and Applied Scientific Research Project of PetroChina Company Limited(2023ZZ18,2023ZZ18YJ04).
文摘In the development of coalbed methane(CBM)reservoirs using multistage fractured horizontal wells,there often exist areas that are either repeatedly stimulated or completely unstimulated between fracturing stages,leading to suboptimal reservoir performance.Currently,there is no well-established method for accurately evaluating the effectiveness of such stimulation.This study introduces,for the first time,the concept of the Fracture Network Bridging Coefficient(FNBC)as a novel metric to assess stimulation performance.By quantitatively coupling the proportions of unstimulated and overstimulated volumes,the FNBC effectively characterizes the connectivity and efficiency of the fracture network.A background grid calibration method is developed to quantify the stage-controlled volume,effectively stimulated volume,unstimulated volume,and repeatedly stimulated volume among different stages of horizontal wells.Furthermore,an optimization model is constructed by taking the FNBC as the objective function and the fracturing injection rate and fluid volume as optimization variables.The Simultaneous Perturbation Stochastic Approximation(SPSA)algorithm is employed to iteratively perturb and optimize these variables,progressively improving the FNBC until the optimal displacement rate and fluid volume corresponding to the maximum FNBC are obtained.Field application in a typical CBM multistage fractured horizontal well in China demonstrates that the FNBC increased from 0.358 to 0.539(a 50.6% improvement),with the injection rate rising from 16 m^(3)/min to 24 m^(3)/min and the average fluid volume per stage increasing from 2490 m^(3) to 3192 m^(3),significantly enhancing the stimulation effectiveness.This research provides theoretical support for designing high-efficiency stimulation strategies in unconventional reservoirs under dynamic limits.
