This paper presents an efficient algorithm for reducing RLC power/ground network complexities by exploitation of the regularities in the power/ground networks. The new method first builds the equivalent models for man...This paper presents an efficient algorithm for reducing RLC power/ground network complexities by exploitation of the regularities in the power/ground networks. The new method first builds the equivalent models for many series RLC-current chains based on their Norton＇s form companion models in the original networks,and then the precondition conjugate gradient based iterative method is used to solve the reduced networks,which are symmetric positive definite. The solutions of the original networks are then back solved from those of the reduced networks.Experimental results show that the complexities of reduced networks are typically significantly smaller than those of the original circuits, which makes the new algorithm extremely fast. For instance, power/ground networks with more than one million branches can be solved in a few minutes on modern Sun workstations.展开更多
A CAD tool based on a group of efficient algorithms to verify,design,and optimize power/ground networks for standard cell model is presented.Nonlinear programming techniques,branch and bound algorithms and incomplete ...A CAD tool based on a group of efficient algorithms to verify,design,and optimize power/ground networks for standard cell model is presented.Nonlinear programming techniques,branch and bound algorithms and incomplete Cholesky decomposition conjugate gradient method (ICCG) are the three main parts of our work.Users can choose nonlinear programming method or branch and bound algorithm to satisfy their different requirements of precision and speed.The experimental results prove that the algorithms can run very fast with lower wiring resources consumption.As a result,the CAD tool based on these algorithms is able to cope with large-scale circuits.展开更多
Ensuring reliable power supply in urban distribution networks is a complex and critical task.To address the increased demand during extreme scenarios,this paper proposes an optimal dispatch strategy that considers the...Ensuring reliable power supply in urban distribution networks is a complex and critical task.To address the increased demand during extreme scenarios,this paper proposes an optimal dispatch strategy that considers the coordination with virtual power plants(VPPs).The proposed strategy improves systemflexibility and responsiveness by optimizing the power adjustment of flexible resources.In the proposed strategy,theGaussian Process Regression(GPR)is firstly employed to determine the adjustable range of aggregated power within the VPP,facilitating an assessment of its potential contribution to power supply support.Then,an optimal dispatch model based on a leader-follower game is developed to maximize the benefits of the VPP and flexible resources while guaranteeing the power balance at the same time.To solve the proposed optimal dispatch model efficiently,the constraints of the problem are reformulated and resolved using the Karush-Kuhn-Tucker(KKT)optimality conditions and linear programming duality theorem.The effectiveness of the strategy is illustrated through a detailed case study.展开更多
Multi-band optical networks are a potential technology for increasing network capacity.However,the strong interference and non-uniformity between wavelengths in multi-band optical networks have become a bottleneck res...Multi-band optical networks are a potential technology for increasing network capacity.However,the strong interference and non-uniformity between wavelengths in multi-band optical networks have become a bottleneck restricting the transmission capacity of multi-band optical networks.To overcome these challenges,it is particularly important to implement optical power optimization targeting wavelength differences.Therefore,based on the generalized Gaussian noise model,we first formulate an optimization model for the problems of routing,modulation format,wavelength,and power allocation in C+L+S multi-band optical networks.Our objective function is to maximize the average link capacity of the network while ensuring that the Optical Signal-to-Noise(OSNR)threshold of the service request is not exceeded.Next,we propose a NonLinear Interferenceaware(NLI-aware)routing,modulation format,wavelength,and power allocation algorithm.Finally,we conduct simulations under different test conditions.The simulation results indicate that our algorithm can effectively reduce the blocking probability by 23.5%and improve the average link capacity by 3.78%in C+L+S multi-band optical networks.展开更多
Considering the uncertainty of grid connection of electric vehicle charging stations and the uncertainty of new energy and residential electricity load,a spatio-temporal decoupling strategy of dynamic reactive power o...Considering the uncertainty of grid connection of electric vehicle charging stations and the uncertainty of new energy and residential electricity load,a spatio-temporal decoupling strategy of dynamic reactive power optimization based on clustering-local relaxation-correction is proposed.Firstly,the k-medoids clustering algorithm is used to divide the reduced power scene into periods.Then,the discrete variables and continuous variables are optimized in the same period of time.Finally,the number of input groups of parallel capacitor banks(CB)in multiple periods is fixed,and then the secondary static reactive power optimization correction is carried out by using the continuous reactive power output device based on the static reactive power compensation device(SVC),the new energy grid-connected inverter,and the electric vehicle charging station.According to the characteristics of the model,a hybrid optimization algorithm with a cross-feedback mechanism is used to solve different types of variables,and an improved artificial hummingbird algorithm based on tent chaotic mapping and adaptive mutation is proposed to improve the solution efficiency.The simulation results show that the proposed decoupling strategy can obtain satisfactory optimization resultswhile strictly guaranteeing the dynamic constraints of discrete variables,and the hybrid algorithm can effectively solve the mixed integer nonlinear optimization problem.展开更多
As the sixth generation network(6G)emerges,the Internet of remote things(IoRT)has become a critical issue.However,conventional terrestrial networks cannot meet the delay-sensitive data collection needs of IoRT network...As the sixth generation network(6G)emerges,the Internet of remote things(IoRT)has become a critical issue.However,conventional terrestrial networks cannot meet the delay-sensitive data collection needs of IoRT networks,and the Space-Air-Ground integrated network(SAGIN)holds promise.We propose a novel setup that integrates non-orthogonal multiple access(NOMA)and wireless power transfer(WPT)to collect latency-sensitive data from IoRT networks.To extend the lifetime of devices,we aim to minimize the maximum energy consumption among all IoRT devices.Due to the coupling between variables,the resulting problem is non-convex.We first decouple the variables and split the original problem into four subproblems.Then,we propose an iterative algorithm to solve the corresponding subproblems based on successive convex approximation(SCA)techniques and slack variables.Finally,simulation results show that the NOMA strategy has a tremendous advantage over the OMA scheme in terms of network lifetime and energy efficiency,providing valuable insights.展开更多
Given the grave local and international network security landscape,a national strategic level analysis indicates that the modernization and advancement within the Industry 4.0 era are closely correlated with overall c...Given the grave local and international network security landscape,a national strategic level analysis indicates that the modernization and advancement within the Industry 4.0 era are closely correlated with overall competitive strength.Consequently,China proposed a strategy for the integration of industrialization and informatization,optimizing and adjusting its industrial structure to swiftly achieve transformation and upgrading in the Industry 4.0 era,thereby enhancing the sophistication of intelligent industrial control systems.The distributed control system in a nuclear power plant functions as an industrial control system,overseeing the operational status of the physical process.Its ability to ensure safe and reliable operation is directly linked to nuclear safety and the cybersecurity of the facility.The management of network security in distributed control systems(DCS)is crucial for achieving this objective.Due to the varying network settings and parameters of the DCS implemented in each nuclear power plant,the network security status of the system sometimes diverges from expectations.During system operation,it will undoubtedly encounter network security issues.Consequently,nuclear power plants utilize the technical criteria outlined in GB/T 22239 to formulate a network security management program aimed at enhancing the operational security of DCS within these facilities.This study utilizes existing network security regulations and standards as a reference to analyze the network security control standards based on the nuclear power plant’s control system.It delineates the fundamental requirements for network security management,facilitating integration with the entire life cycle of the research,development,and application of the nuclear power plant’s distributed control system,thereby establishing a network security management methodology that satisfies the control requirements of the nuclear power plant.Initially,it presents DCS and network security management,outlines current domestic and international network security legislation and standards,and specifies the standards pertinent to the administration of DCS in nuclear power plants.Secondly,the design of network security management for DCS is executed in conjunction with the specific context of nuclear power plants.This encompasses the deployment of network security apparatus,validation of the network security management strategy,and optimization adjustments.Consequently,recommendations beneficial to the network security management of nuclear power plants are compiled,aimed at establishing a management system and incorporating the concept of full life cycle management,which is predicated on system requirements,system design,and both software and hardware considerations.Conversely,it presents the notion of comprehensive life cycle management and suggests network security management strategies encompassing system requirements,system architecture,detailed hardware and software design and implementation,procurement,internal system integration,system validation and acceptance testing,system installation,operational maintenance,system modifications,and decommissioning.We will consistently enhance the performance and functionality of DCS in nuclear power plants,establish a safe and secure operational environment,and thereby facilitate the implementation of DCS in nuclear facilities while ensuring robust network security in the future.展开更多
Solar energy is a pivotal clean energy source in the transition to carbon neutrality from fossil fuels.However,the intermittent and stochastic characteristics of solar radiation pose challenges for accurate simulation...Solar energy is a pivotal clean energy source in the transition to carbon neutrality from fossil fuels.However,the intermittent and stochastic characteristics of solar radiation pose challenges for accurate simulation and prediction.Accurately simulating and predicting solar radiation and its variability are crucial for optimizing solar energy utilization.This study conducted simulation experiments using the WRF-Solar model from 25 June to 25 July 2022,to evaluate the accuracy and performance of the simulated solar radiation across China.The simulations covered the whole country with a grid spacing of 27 km and were compared with ground observation network data from the Chinese Ecosystem Research Network.The results indicated that WRF-Solar can accurately capture the spatiotemporal patterns of global horizontal irradiance over China,but there is still an overestimation of solar radiation,and the model underestimates the total cloud cover.The root-mean-square error ranged from 92.83 to 188.13 W m^(-2) and the mean bias(MB)ranged from 21.05 to 56.22 W m^(-2).The simulation showed the smallest MB at Lhasa on the Qinghai–Tibet Plateau,while the largest MB was observed in Southeast China.To enhance the accuracy of solar radiation simulation,the authors compared the Fast All-sky Radiation Model for Solar with the Rapid Radiative Transfer Model for General Circulation Models and found that the former provides better simulation.展开更多
This study addresses the pressing challenge of generating realistic strong ground motion data for simulating earthquakes,a crucial component in pre-earthquake risk assessments and post-earthquake disaster evaluations,...This study addresses the pressing challenge of generating realistic strong ground motion data for simulating earthquakes,a crucial component in pre-earthquake risk assessments and post-earthquake disaster evaluations,particularly suited for regions with limited seismic data.Herein,we report a generative adversarial network(GAN)framework capable of simulating strong ground motions under various environmental conditions using only a small set of real earthquake records.The constructed GAN model generates ground motions based on continuous physical variables such as source distance,site conditions,and magnitude,effectively capturing the complexity and diversity of ground motions under different scenarios.This capability allows the proposed model to approximate real seismic data,making it applicable to a wide range of engineering purposes.Using the Shandong Pingyuan earthquake as an example,a specialized dataset was constructed based on regional real ground motion records.The response spectrum at target locations was obtained through inverse distance-weighted interpolation of actual response spectra,followed by continuous wavelet transform to derive the ground motion time histories at these locations.Through iterative parameter adjustments,the constructed GAN model learned the probability distribution of strong-motion data for this event.The trained model generated three-component ground-motion time histories with clear P-wave and S-wave characteristics,accurately reflecting the non-stationary nature of seismic records.Statistical comparisons between synthetic and real response spectra,waveform envelopes,and peak ground acceleration show a high degree of similarity,underscoring the effectiveness of the model in replicating both the statistical and physical characteristics of real ground motions.These findings validate the feasibility of GANs for generating realistic earthquake data in data-scarce regions,providing a reliable approach for enriching regional ground motion databases.Additionally,the results suggest that GAN-based networks are a powerful tool for building predictive models in seismic hazard analysis.展开更多
This study addresses the critical challenge of reconfiguration in unbalanced power distribution networks(UPDNs),focusing on the complex 123-Bus test system.Three scenarios are investigated:(1)simultaneous power loss r...This study addresses the critical challenge of reconfiguration in unbalanced power distribution networks(UPDNs),focusing on the complex 123-Bus test system.Three scenarios are investigated:(1)simultaneous power loss reduction and voltage profile improvement,(2)minimization of voltage and current unbalance indices under various operational cases,and(3)multi-objective optimization using Pareto front analysis to concurrently optimize voltage unbalance index,active power loss,and current unbalance index.Unlike previous research that oftensimplified system components,this work maintains all equipment,including capacitor banks,transformers,and voltage regulators,to ensure realistic results.The study evaluates twelve metaheuristic algorithms to solve the reconfiguration problem(RecPrb)in UPDNs.A comprehensive statistical analysis is conducted to identify the most efficient algorithm for solving the RecPrb in the 123-Bus UPDN,employing multiple performance metrics and comparative techniques.The Artificial Hummingbird Algorithm emerges as the top-performing algorithm and is subsequently applied to address a multi-objective optimization challenge in the 123-Bus UPDN.This research contributes valuable insights for network operators and researchers in selecting suitable algorithms for specific reconfiguration scenarios,advancing the field of UPDN optimization and management.展开更多
The dynamics of network power response play a crucial role in system stability.However,the integration of power electronic equipment leads to amplitude and angular frequency(abbreviated as"frequency")time-va...The dynamics of network power response play a crucial role in system stability.However,the integration of power electronic equipment leads to amplitude and angular frequency(abbreviated as"frequency")time-varying characteristics of the node voltage during dynamic processes.As a result,traditional calcu-lation methods for and characteristics of the power response of the network based on phasor and impe-dance lose their validity.Therefore,this paper undertakes mathematical calculations to reveal the power response of a network under excitation by voltage with time-varying amplitude and frequency(TVAF),relying on the original mathematical relationships and superimposed step response.Then,the multi-timescale characteristics of both the active and reactive power of the network are explored physically.Additionally,this paper reveals a new phenomenon of storing and releasing the active and reactive power of the network.To meet practical engineering requirements,a simplified power expression is presented.Finally,the theoretical analysis is validated through time-domain simulations.展开更多
An appropriate spatial structure of a power battery supply network is crucial for the specialization and scale development of key components in new energy vehicles, accelerating the transformation and upgrade of the i...An appropriate spatial structure of a power battery supply network is crucial for the specialization and scale development of key components in new energy vehicles, accelerating the transformation and upgrade of the industry. This paper investigates the cooperative relationships among supply chain enterprises from the perspective of complex networks.Employing methodologies such as the gravity model and Moran's I analysis, it explores the spatial structural characteristics and correlation patterns of the power battery supply network in China and discusses the influencing factors using the quadratic assignment procedure,revealing the mechanisms behind the differences in the spatial distributions of the power battery supply network. The results indicate that the distribution of power battery enterprises is densely concentrated in the eastern and southern regions, whereas the western region has a sparse distribution. The spatial supply network consists of a four-tier linkage system, encompassing 135 prefecture-level cities, with Chongqing, Shanghai, Nanjing, and other cities particularly prominent. Overall, the degree of agglomeration is low, with coastal cities dominating the landscape and inland cities serving as complementary regions. Most areas are characterized as insignificant or low-high regions, and the regional linkage effect of core cities is not pronounced. There is a notable lack of significance and high spatial heterogeneity.Four types of factors—spatial factors, market factors, agglomeration economies, and innovation levels—jointly influence and shape the spatial structure of the power battery supply network.展开更多
In this paper,we propose a joint power and frequency allocation algorithm considering interference protection in the integrated satellite and terrestrial network(ISTN).We efficiently utilize spectrum resources by allo...In this paper,we propose a joint power and frequency allocation algorithm considering interference protection in the integrated satellite and terrestrial network(ISTN).We efficiently utilize spectrum resources by allowing user equipment(UE)of terrestrial networks to share frequencies with satellite networks.In order to protect the satellite terminal(ST),the base station(BS)needs to control the transmit power and frequency resources of the UE.The optimization problem involves maximizing the achievable throughput while satisfying the interference protection constraints of the ST and the quality of service(QoS)of the UE.However,this problem is highly nonconvex,and we decompose it into power allocation and frequency resource scheduling subproblems.In the power allocation subproblem,we propose a power allocation algorithm based on interference probability(PAIP)to address channel uncertainty.We obtain the suboptimal power allocation solution through iterative optimization.In the frequency resource scheduling subproblem,we develop a heuristic algorithm to handle the non-convexity of the problem.The simulation results show that the combination of power allocation and frequency resource scheduling algorithms can improve spectrum utilization.展开更多
The lack of communication infrastructure in remote regions presents significant obstacles to gathering data from smart power sensors(SPSs)in smart grid networks.In such cases,a space-air-ground integrated network serv...The lack of communication infrastructure in remote regions presents significant obstacles to gathering data from smart power sensors(SPSs)in smart grid networks.In such cases,a space-air-ground integrated network serves as an effective emergency solution.This study addresses the challenge of optimizing the energy efficiency of data transmission fromSPSs to low Earth orbit(LEO)satellites through unmanned aerial vehicles(UAVs),considering both effective capacity and fronthaul link capacity constraints.Due to the non-convex nature of the problem,the objective function is reformulated,and a delay-aware energy-efficient power allocation and UAV trajectory design(DEPATD)algorithm is proposed as a two-loop approach.Since the inner loop remains non-convex,the block coordinate descent(BCD)method is employed to decompose it into three subproblems:power allocation for SPSs,power allocation for UAVs,and UAV trajectory design.The first two subproblems are solved using the Lagrangian dual method,while the third is addressed with the successive convex approximation(SCA)technique.By iteratively solving these subproblems,an efficient algorithm is developed to resolve the inner loop issue.Simulation results demonstrate that the energy efficiency of the proposed DEPATD algorithm improves by 4.02% compared to the benchmark algorithm when the maximum transmission power of the SPSs increases from 0.1 to 0.45W.展开更多
Conventional droop control in multi-parallel grid-forming inverters exhibits poor reactive power sharing accuracy due to line impedance mismatches.In this study,we proposed a coordination control strategy integrating ...Conventional droop control in multi-parallel grid-forming inverters exhibits poor reactive power sharing accuracy due to line impedance mismatches.In this study,we proposed a coordination control strategy integrating adaptive virtual impedance with dynamic Q-V droop regulation to overcome this issue.We established a coupling model between the line impedance and power allocation to determine the quantitative relationship between reactive power deviation and impedance difference and to analyze the mechanism of reactive power deviation formation.Based on this,we proposed a transformer neural network-based online identification method for adaptive virtual impedance and dynamic droop coefficients.The self-attention mechanism dynamically characterizes the spatial distribution features of the impedance parameters considering the real-time voltage/reactive power time-series data as inputs to realize the dynamic impedance compensation without communication interaction.The contradiction constraint between the voltage drop and distribution accuracy caused by the introduction of conventional virtual impedance is improved by dynamic droop coefficient reconstruction.Lastly,we established a hardware-in-the-loop simulation platform to experimentally validate the operational efficacy and dynamic performance of the proposed control strategy under various grid scenarios.展开更多
In recent years,intensified environmental pollution and climate change have increasingly exposed the world to natural disasters such as earthquakes and floods,resulting in substantial economic losses[1].These disaster...In recent years,intensified environmental pollution and climate change have increasingly exposed the world to natural disasters such as earthquakes and floods,resulting in substantial economic losses[1].These disasters frequently damage terrestrial communication infrastructures,making the rapid deployment of emergency communication networks in affected areas critical in increasing rescue efficiency[2].展开更多
In order to improve the estimation accuracy of the battery＇s state of charge（SOC） for the hybrid electric vehicle（HEV）,the SOC estimation algorithm based on advanced wavelet neural network（WNN） is presented.Bas...In order to improve the estimation accuracy of the battery＇s state of charge（SOC） for the hybrid electric vehicle（HEV）,the SOC estimation algorithm based on advanced wavelet neural network（WNN） is presented.Based on advanced WNN,the SOC estimation model of a lithium-ion power battery for the HEV is first established.Then,the convergence of the advanced WNN algorithm is proved by mathematical deduction.Finally,using an adequate data sample of various charging and discharging of HEV batteries,the neural network is trained.The simulation results indicate that the proposed algorithm can effectively decrease the estimation errors of the lithium-ion power battery SOC from the range of ±8% to ±1.5%,compared with the traditional SOC estimation methods.展开更多
In order to save the energy and reduce the latency of the end-to-end transmission in mobile ad hoc networks an adaptive and distance-driven power control ADPC scheme is proposed by means of distance research in random...In order to save the energy and reduce the latency of the end-to-end transmission in mobile ad hoc networks an adaptive and distance-driven power control ADPC scheme is proposed by means of distance research in random geometrics. Through mathematical proof the optimal number of relay nodes and the optimal location of each node for data transmission can be obtained when a distance is given.In the ADPC first the source node computes the optimal number and the sites of the relay nodes between the source and the destination nodes.Then it searches feasible relay nodes around the optimal virtual relay-sites and selects one link with the minimal total transmission energy consumption for data transmission.Simulation results show that the ADPC can reduce both the energy dissipation and the end-to-end latency of the transmission.展开更多
A novel behavioral model using three-layer time-delay feed-forward neural networks （TDFFNN）is adopted to model radio frequency （RF）power amplifiers exhibiting memory nonlinearities. In order to extract the paramet...A novel behavioral model using three-layer time-delay feed-forward neural networks （TDFFNN）is adopted to model radio frequency （RF）power amplifiers exhibiting memory nonlinearities. In order to extract the parameters, the back- propagation algorithm is applied to train the proposed neural networks. The proposed model is verified by the typical odd- order-only memory polynomial model in simulation, and the performance is compared with different numbers of taped delay lines（TDLs） and perceptrons of the hidden layer. For validating the TDFFNN model by experiments, a digital test bench is set up to collect input and output data of power amplifiers at a 60 × 10^6 sample/s sampling rate. The 3.75 MHz 16-QAM signal generated in the vector signal generator（VSG） is chosen as the input signal, when measuring the dynamic AM/AM and AM/PM characteristics of power amplifiers. By comparisons and analyses, the presented model provides a good performance in convergence, accuracy and efficiency, which is approved by simulation results and experimental results in the time domain and frequency domain.展开更多
In light of the situation that the nationwide interconnection of power networks in China in the coming years will take shape, it is imperative to emphasize the importance of setting up rational power network configura...In light of the situation that the nationwide interconnection of power networks in China in the coming years will take shape, it is imperative to emphasize the importance of setting up rational power network configuration. Combined with the characteristics of regional power networks in China, problems in network planning that need to be solved are put forward in this paper, such as, the access of power plants to grid by layers and zones, the share of external power in the load of local network, the power network configuration study in-depth in planning and design stage, and enforcement of receiving-end power network trunk etc. The background of these problems and their countermeasures are also analyzed in the paper.展开更多
文摘This paper presents an efficient algorithm for reducing RLC power/ground network complexities by exploitation of the regularities in the power/ground networks. The new method first builds the equivalent models for many series RLC-current chains based on their Norton＇s form companion models in the original networks,and then the precondition conjugate gradient based iterative method is used to solve the reduced networks,which are symmetric positive definite. The solutions of the original networks are then back solved from those of the reduced networks.Experimental results show that the complexities of reduced networks are typically significantly smaller than those of the original circuits, which makes the new algorithm extremely fast. For instance, power/ground networks with more than one million branches can be solved in a few minutes on modern Sun workstations.
文摘A CAD tool based on a group of efficient algorithms to verify,design,and optimize power/ground networks for standard cell model is presented.Nonlinear programming techniques,branch and bound algorithms and incomplete Cholesky decomposition conjugate gradient method (ICCG) are the three main parts of our work.Users can choose nonlinear programming method or branch and bound algorithm to satisfy their different requirements of precision and speed.The experimental results prove that the algorithms can run very fast with lower wiring resources consumption.As a result,the CAD tool based on these algorithms is able to cope with large-scale circuits.
基金supported by the Science and Technology Project of Sichuan Electric Power Company“Power Supply Guarantee Strategy for Urban Distribution Networks Considering Coordination with Virtual Power Plant during Extreme Weather Event”(No.521920230003).
文摘Ensuring reliable power supply in urban distribution networks is a complex and critical task.To address the increased demand during extreme scenarios,this paper proposes an optimal dispatch strategy that considers the coordination with virtual power plants(VPPs).The proposed strategy improves systemflexibility and responsiveness by optimizing the power adjustment of flexible resources.In the proposed strategy,theGaussian Process Regression(GPR)is firstly employed to determine the adjustable range of aggregated power within the VPP,facilitating an assessment of its potential contribution to power supply support.Then,an optimal dispatch model based on a leader-follower game is developed to maximize the benefits of the VPP and flexible resources while guaranteeing the power balance at the same time.To solve the proposed optimal dispatch model efficiently,the constraints of the problem are reformulated and resolved using the Karush-Kuhn-Tucker(KKT)optimality conditions and linear programming duality theorem.The effectiveness of the strategy is illustrated through a detailed case study.
基金supported in part by the National Natural Science Foundation of China under Grants U21B2005,62201105,62331017,U24B20134,62222103,and 62025105in part by the Chongqing Municipal Education Commission under Grants KJQN202400621,KJQN202100643,and KJZDK202400608+1 种基金in part by the China Postdoctoral Science Foundation under Grant 2021M700563in part by the Chongqing Postdoctoral Funding Project under Grant 2021XM3052。
文摘Multi-band optical networks are a potential technology for increasing network capacity.However,the strong interference and non-uniformity between wavelengths in multi-band optical networks have become a bottleneck restricting the transmission capacity of multi-band optical networks.To overcome these challenges,it is particularly important to implement optical power optimization targeting wavelength differences.Therefore,based on the generalized Gaussian noise model,we first formulate an optimization model for the problems of routing,modulation format,wavelength,and power allocation in C+L+S multi-band optical networks.Our objective function is to maximize the average link capacity of the network while ensuring that the Optical Signal-to-Noise(OSNR)threshold of the service request is not exceeded.Next,we propose a NonLinear Interferenceaware(NLI-aware)routing,modulation format,wavelength,and power allocation algorithm.Finally,we conduct simulations under different test conditions.The simulation results indicate that our algorithm can effectively reduce the blocking probability by 23.5%and improve the average link capacity by 3.78%in C+L+S multi-band optical networks.
基金funded by the“Research and Application Project of Collaborative Optimization Control Technology for Distribution Station Area for High Proportion Distributed PV Consumption(4000-202318079A-1-1-ZN)”of the Headquarters of the State Grid Corporation.
文摘Considering the uncertainty of grid connection of electric vehicle charging stations and the uncertainty of new energy and residential electricity load,a spatio-temporal decoupling strategy of dynamic reactive power optimization based on clustering-local relaxation-correction is proposed.Firstly,the k-medoids clustering algorithm is used to divide the reduced power scene into periods.Then,the discrete variables and continuous variables are optimized in the same period of time.Finally,the number of input groups of parallel capacitor banks(CB)in multiple periods is fixed,and then the secondary static reactive power optimization correction is carried out by using the continuous reactive power output device based on the static reactive power compensation device(SVC),the new energy grid-connected inverter,and the electric vehicle charging station.According to the characteristics of the model,a hybrid optimization algorithm with a cross-feedback mechanism is used to solve different types of variables,and an improved artificial hummingbird algorithm based on tent chaotic mapping and adaptive mutation is proposed to improve the solution efficiency.The simulation results show that the proposed decoupling strategy can obtain satisfactory optimization resultswhile strictly guaranteeing the dynamic constraints of discrete variables,and the hybrid algorithm can effectively solve the mixed integer nonlinear optimization problem.
基金supported by National Natural Science Foundation of China(No.62171158)the project“The Major Key Project of PCL(PCL2021A03-1)”from Peng Cheng Laboratorysupported by the Science and the Research Fund Program of Guangdong Key Laboratory of Aerospace Communication and Networking Technology(2018B030322004).
文摘As the sixth generation network(6G)emerges,the Internet of remote things(IoRT)has become a critical issue.However,conventional terrestrial networks cannot meet the delay-sensitive data collection needs of IoRT networks,and the Space-Air-Ground integrated network(SAGIN)holds promise.We propose a novel setup that integrates non-orthogonal multiple access(NOMA)and wireless power transfer(WPT)to collect latency-sensitive data from IoRT networks.To extend the lifetime of devices,we aim to minimize the maximum energy consumption among all IoRT devices.Due to the coupling between variables,the resulting problem is non-convex.We first decouple the variables and split the original problem into four subproblems.Then,we propose an iterative algorithm to solve the corresponding subproblems based on successive convex approximation(SCA)techniques and slack variables.Finally,simulation results show that the NOMA strategy has a tremendous advantage over the OMA scheme in terms of network lifetime and energy efficiency,providing valuable insights.
文摘Given the grave local and international network security landscape,a national strategic level analysis indicates that the modernization and advancement within the Industry 4.0 era are closely correlated with overall competitive strength.Consequently,China proposed a strategy for the integration of industrialization and informatization,optimizing and adjusting its industrial structure to swiftly achieve transformation and upgrading in the Industry 4.0 era,thereby enhancing the sophistication of intelligent industrial control systems.The distributed control system in a nuclear power plant functions as an industrial control system,overseeing the operational status of the physical process.Its ability to ensure safe and reliable operation is directly linked to nuclear safety and the cybersecurity of the facility.The management of network security in distributed control systems(DCS)is crucial for achieving this objective.Due to the varying network settings and parameters of the DCS implemented in each nuclear power plant,the network security status of the system sometimes diverges from expectations.During system operation,it will undoubtedly encounter network security issues.Consequently,nuclear power plants utilize the technical criteria outlined in GB/T 22239 to formulate a network security management program aimed at enhancing the operational security of DCS within these facilities.This study utilizes existing network security regulations and standards as a reference to analyze the network security control standards based on the nuclear power plant’s control system.It delineates the fundamental requirements for network security management,facilitating integration with the entire life cycle of the research,development,and application of the nuclear power plant’s distributed control system,thereby establishing a network security management methodology that satisfies the control requirements of the nuclear power plant.Initially,it presents DCS and network security management,outlines current domestic and international network security legislation and standards,and specifies the standards pertinent to the administration of DCS in nuclear power plants.Secondly,the design of network security management for DCS is executed in conjunction with the specific context of nuclear power plants.This encompasses the deployment of network security apparatus,validation of the network security management strategy,and optimization adjustments.Consequently,recommendations beneficial to the network security management of nuclear power plants are compiled,aimed at establishing a management system and incorporating the concept of full life cycle management,which is predicated on system requirements,system design,and both software and hardware considerations.Conversely,it presents the notion of comprehensive life cycle management and suggests network security management strategies encompassing system requirements,system architecture,detailed hardware and software design and implementation,procurement,internal system integration,system validation and acceptance testing,system installation,operational maintenance,system modifications,and decommissioning.We will consistently enhance the performance and functionality of DCS in nuclear power plants,establish a safe and secure operational environment,and thereby facilitate the implementation of DCS in nuclear facilities while ensuring robust network security in the future.
基金supported by the National Natural Science Foundation of China[grant number 42175132]the National Key R&D Program[grant number 2020YFA0607802]the CAS Information Technology Program[grant number CAS-WX2021SF-0107-02]。
文摘Solar energy is a pivotal clean energy source in the transition to carbon neutrality from fossil fuels.However,the intermittent and stochastic characteristics of solar radiation pose challenges for accurate simulation and prediction.Accurately simulating and predicting solar radiation and its variability are crucial for optimizing solar energy utilization.This study conducted simulation experiments using the WRF-Solar model from 25 June to 25 July 2022,to evaluate the accuracy and performance of the simulated solar radiation across China.The simulations covered the whole country with a grid spacing of 27 km and were compared with ground observation network data from the Chinese Ecosystem Research Network.The results indicated that WRF-Solar can accurately capture the spatiotemporal patterns of global horizontal irradiance over China,but there is still an overestimation of solar radiation,and the model underestimates the total cloud cover.The root-mean-square error ranged from 92.83 to 188.13 W m^(-2) and the mean bias(MB)ranged from 21.05 to 56.22 W m^(-2).The simulation showed the smallest MB at Lhasa on the Qinghai–Tibet Plateau,while the largest MB was observed in Southeast China.To enhance the accuracy of solar radiation simulation,the authors compared the Fast All-sky Radiation Model for Solar with the Rapid Radiative Transfer Model for General Circulation Models and found that the former provides better simulation.
基金Funded by the National Key Research and Development Program(2022YFC3003502).
文摘This study addresses the pressing challenge of generating realistic strong ground motion data for simulating earthquakes,a crucial component in pre-earthquake risk assessments and post-earthquake disaster evaluations,particularly suited for regions with limited seismic data.Herein,we report a generative adversarial network(GAN)framework capable of simulating strong ground motions under various environmental conditions using only a small set of real earthquake records.The constructed GAN model generates ground motions based on continuous physical variables such as source distance,site conditions,and magnitude,effectively capturing the complexity and diversity of ground motions under different scenarios.This capability allows the proposed model to approximate real seismic data,making it applicable to a wide range of engineering purposes.Using the Shandong Pingyuan earthquake as an example,a specialized dataset was constructed based on regional real ground motion records.The response spectrum at target locations was obtained through inverse distance-weighted interpolation of actual response spectra,followed by continuous wavelet transform to derive the ground motion time histories at these locations.Through iterative parameter adjustments,the constructed GAN model learned the probability distribution of strong-motion data for this event.The trained model generated three-component ground-motion time histories with clear P-wave and S-wave characteristics,accurately reflecting the non-stationary nature of seismic records.Statistical comparisons between synthetic and real response spectra,waveform envelopes,and peak ground acceleration show a high degree of similarity,underscoring the effectiveness of the model in replicating both the statistical and physical characteristics of real ground motions.These findings validate the feasibility of GANs for generating realistic earthquake data in data-scarce regions,providing a reliable approach for enriching regional ground motion databases.Additionally,the results suggest that GAN-based networks are a powerful tool for building predictive models in seismic hazard analysis.
基金supported by the Scientific and Technological Research Council of Turkey(TUBITAK)under Grant No.124E002(1001-Project).
文摘This study addresses the critical challenge of reconfiguration in unbalanced power distribution networks(UPDNs),focusing on the complex 123-Bus test system.Three scenarios are investigated:(1)simultaneous power loss reduction and voltage profile improvement,(2)minimization of voltage and current unbalance indices under various operational cases,and(3)multi-objective optimization using Pareto front analysis to concurrently optimize voltage unbalance index,active power loss,and current unbalance index.Unlike previous research that oftensimplified system components,this work maintains all equipment,including capacitor banks,transformers,and voltage regulators,to ensure realistic results.The study evaluates twelve metaheuristic algorithms to solve the reconfiguration problem(RecPrb)in UPDNs.A comprehensive statistical analysis is conducted to identify the most efficient algorithm for solving the RecPrb in the 123-Bus UPDN,employing multiple performance metrics and comparative techniques.The Artificial Hummingbird Algorithm emerges as the top-performing algorithm and is subsequently applied to address a multi-objective optimization challenge in the 123-Bus UPDN.This research contributes valuable insights for network operators and researchers in selecting suitable algorithms for specific reconfiguration scenarios,advancing the field of UPDN optimization and management.
基金supported in part by the National Natural Science Fundation of China(52225704 and 52107096).
文摘The dynamics of network power response play a crucial role in system stability.However,the integration of power electronic equipment leads to amplitude and angular frequency(abbreviated as"frequency")time-varying characteristics of the node voltage during dynamic processes.As a result,traditional calcu-lation methods for and characteristics of the power response of the network based on phasor and impe-dance lose their validity.Therefore,this paper undertakes mathematical calculations to reveal the power response of a network under excitation by voltage with time-varying amplitude and frequency(TVAF),relying on the original mathematical relationships and superimposed step response.Then,the multi-timescale characteristics of both the active and reactive power of the network are explored physically.Additionally,this paper reveals a new phenomenon of storing and releasing the active and reactive power of the network.To meet practical engineering requirements,a simplified power expression is presented.Finally,the theoretical analysis is validated through time-domain simulations.
基金Humanities and Social Sciences Project of the Ministry of Education of China,No.23YJCZH195Scientific Research Program funded by the Shaanxi Provincial Education Department,No.20JK0358, No.21JK0908+2 种基金Natural Science Basic Research Program of Shaanxi,No.2024JC-YBQN-0738, No.2023-JC-QN-0560Shaanxi Provincial Education Science Planning Project,No.SGH23Y2484China Logistics Society&China Federation of Logistics and Purchasing Research Fund,No.2023CSLKT3-220。
文摘An appropriate spatial structure of a power battery supply network is crucial for the specialization and scale development of key components in new energy vehicles, accelerating the transformation and upgrade of the industry. This paper investigates the cooperative relationships among supply chain enterprises from the perspective of complex networks.Employing methodologies such as the gravity model and Moran's I analysis, it explores the spatial structural characteristics and correlation patterns of the power battery supply network in China and discusses the influencing factors using the quadratic assignment procedure,revealing the mechanisms behind the differences in the spatial distributions of the power battery supply network. The results indicate that the distribution of power battery enterprises is densely concentrated in the eastern and southern regions, whereas the western region has a sparse distribution. The spatial supply network consists of a four-tier linkage system, encompassing 135 prefecture-level cities, with Chongqing, Shanghai, Nanjing, and other cities particularly prominent. Overall, the degree of agglomeration is low, with coastal cities dominating the landscape and inland cities serving as complementary regions. Most areas are characterized as insignificant or low-high regions, and the regional linkage effect of core cities is not pronounced. There is a notable lack of significance and high spatial heterogeneity.Four types of factors—spatial factors, market factors, agglomeration economies, and innovation levels—jointly influence and shape the spatial structure of the power battery supply network.
基金funded by State Key Laboratory of Micro-Spacecraft Rapid Design and Intelligent Cluster under Grant MS01240103the National Natural Science Foundation of China under Grant 62071146National 2011 Collaborative Innovation Center of Wireless Communication Technologies under Grant 2242022k60006.
文摘In this paper,we propose a joint power and frequency allocation algorithm considering interference protection in the integrated satellite and terrestrial network(ISTN).We efficiently utilize spectrum resources by allowing user equipment(UE)of terrestrial networks to share frequencies with satellite networks.In order to protect the satellite terminal(ST),the base station(BS)needs to control the transmit power and frequency resources of the UE.The optimization problem involves maximizing the achievable throughput while satisfying the interference protection constraints of the ST and the quality of service(QoS)of the UE.However,this problem is highly nonconvex,and we decompose it into power allocation and frequency resource scheduling subproblems.In the power allocation subproblem,we propose a power allocation algorithm based on interference probability(PAIP)to address channel uncertainty.We obtain the suboptimal power allocation solution through iterative optimization.In the frequency resource scheduling subproblem,we develop a heuristic algorithm to handle the non-convexity of the problem.The simulation results show that the combination of power allocation and frequency resource scheduling algorithms can improve spectrum utilization.
基金Supported by the Self-funded Research Project of Beijing FibrLink Communications Co.Ltd.“Research on Key Technologies forUnifiedManagement of Air-to-Earth Integrated CommunicationNetworks(546826230034).”。
文摘The lack of communication infrastructure in remote regions presents significant obstacles to gathering data from smart power sensors(SPSs)in smart grid networks.In such cases,a space-air-ground integrated network serves as an effective emergency solution.This study addresses the challenge of optimizing the energy efficiency of data transmission fromSPSs to low Earth orbit(LEO)satellites through unmanned aerial vehicles(UAVs),considering both effective capacity and fronthaul link capacity constraints.Due to the non-convex nature of the problem,the objective function is reformulated,and a delay-aware energy-efficient power allocation and UAV trajectory design(DEPATD)algorithm is proposed as a two-loop approach.Since the inner loop remains non-convex,the block coordinate descent(BCD)method is employed to decompose it into three subproblems:power allocation for SPSs,power allocation for UAVs,and UAV trajectory design.The first two subproblems are solved using the Lagrangian dual method,while the third is addressed with the successive convex approximation(SCA)technique.By iteratively solving these subproblems,an efficient algorithm is developed to resolve the inner loop issue.Simulation results demonstrate that the energy efficiency of the proposed DEPATD algorithm improves by 4.02% compared to the benchmark algorithm when the maximum transmission power of the SPSs increases from 0.1 to 0.45W.
基金supported by the National Natural Science Foundation of China(No.62063016)the Science and Technology Plan of Gansu Province(No.25JRRA088).
文摘Conventional droop control in multi-parallel grid-forming inverters exhibits poor reactive power sharing accuracy due to line impedance mismatches.In this study,we proposed a coordination control strategy integrating adaptive virtual impedance with dynamic Q-V droop regulation to overcome this issue.We established a coupling model between the line impedance and power allocation to determine the quantitative relationship between reactive power deviation and impedance difference and to analyze the mechanism of reactive power deviation formation.Based on this,we proposed a transformer neural network-based online identification method for adaptive virtual impedance and dynamic droop coefficients.The self-attention mechanism dynamically characterizes the spatial distribution features of the impedance parameters considering the real-time voltage/reactive power time-series data as inputs to realize the dynamic impedance compensation without communication interaction.The contradiction constraint between the voltage drop and distribution accuracy caused by the introduction of conventional virtual impedance is improved by dynamic droop coefficient reconstruction.Lastly,we established a hardware-in-the-loop simulation platform to experimentally validate the operational efficacy and dynamic performance of the proposed control strategy under various grid scenarios.
基金supported in part by the National Natural Science Foundation of China(U2441226).
文摘In recent years,intensified environmental pollution and climate change have increasingly exposed the world to natural disasters such as earthquakes and floods,resulting in substantial economic losses[1].These disasters frequently damage terrestrial communication infrastructures,making the rapid deployment of emergency communication networks in affected areas critical in increasing rescue efficiency[2].
基金The National Natural Science Foundation of China (No.60904023)
文摘In order to improve the estimation accuracy of the battery＇s state of charge（SOC） for the hybrid electric vehicle（HEV）,the SOC estimation algorithm based on advanced wavelet neural network（WNN） is presented.Based on advanced WNN,the SOC estimation model of a lithium-ion power battery for the HEV is first established.Then,the convergence of the advanced WNN algorithm is proved by mathematical deduction.Finally,using an adequate data sample of various charging and discharging of HEV batteries,the neural network is trained.The simulation results indicate that the proposed algorithm can effectively decrease the estimation errors of the lithium-ion power battery SOC from the range of ±8% to ±1.5%,compared with the traditional SOC estimation methods.
基金The National Basic Research Program of China(973 Program)(No.2009CB320501)the National Natural Science Foundation of China(No.61370209,61272532)the Natural Science Foundation of Jiangsu Province(No.BK2010414,BK2011335)
文摘In order to save the energy and reduce the latency of the end-to-end transmission in mobile ad hoc networks an adaptive and distance-driven power control ADPC scheme is proposed by means of distance research in random geometrics. Through mathematical proof the optimal number of relay nodes and the optimal location of each node for data transmission can be obtained when a distance is given.In the ADPC first the source node computes the optimal number and the sites of the relay nodes between the source and the destination nodes.Then it searches feasible relay nodes around the optimal virtual relay-sites and selects one link with the minimal total transmission energy consumption for data transmission.Simulation results show that the ADPC can reduce both the energy dissipation and the end-to-end latency of the transmission.
基金The National Natural Science Foundation of China(No.60621002)the National High Technology Research and Development Pro-gram of China(863 Program)(No.2007AA01Z2B4).
文摘A novel behavioral model using three-layer time-delay feed-forward neural networks （TDFFNN）is adopted to model radio frequency （RF）power amplifiers exhibiting memory nonlinearities. In order to extract the parameters, the back- propagation algorithm is applied to train the proposed neural networks. The proposed model is verified by the typical odd- order-only memory polynomial model in simulation, and the performance is compared with different numbers of taped delay lines（TDLs） and perceptrons of the hidden layer. For validating the TDFFNN model by experiments, a digital test bench is set up to collect input and output data of power amplifiers at a 60 × 10^6 sample/s sampling rate. The 3.75 MHz 16-QAM signal generated in the vector signal generator（VSG） is chosen as the input signal, when measuring the dynamic AM/AM and AM/PM characteristics of power amplifiers. By comparisons and analyses, the presented model provides a good performance in convergence, accuracy and efficiency, which is approved by simulation results and experimental results in the time domain and frequency domain.
文摘In light of the situation that the nationwide interconnection of power networks in China in the coming years will take shape, it is imperative to emphasize the importance of setting up rational power network configuration. Combined with the characteristics of regional power networks in China, problems in network planning that need to be solved are put forward in this paper, such as, the access of power plants to grid by layers and zones, the share of external power in the load of local network, the power network configuration study in-depth in planning and design stage, and enforcement of receiving-end power network trunk etc. The background of these problems and their countermeasures are also analyzed in the paper.
